T ECHNICAL P ROGRAM
Sunday, 16.00-17.30
SA-50
Sunday, 16.00-17.30 - Plenaries room
Opening Session
Stream: Plenary Sessions
Invited session
1
MA-01
IFORS 2014 - Barcelona
Monday, 8:30-10:00
MA-01
Monday, 8:30-10:00 - Room 118
Railway Scheduling Problems
Stream: Railway and Metro Transportation
Invited session
Chair: Thomas Schlechte
1 - Maintenance in the Rolling Stock Rescheduling
Model
Joris Wagenaar
In this paper we propose a formulation to take maintenance into account in disruption management models for passenger railway transportation. During a disruption part(s) of the railway infrastructure can
no longer be used. To uphold as much of the passenger service as possible, a new rolling stock schedule should be created as soon as possible. A selected amount of the allocated rolling stock units are scheduled to have a maintenance check somewhere during the operations.
That is why we propose an integrated formulation to take maintenance
right from the start of the disruption into account.
2 - The Demand Balancing Problem in Rail Freight Service
Hanno Schülldorf
One major issue in rail freight service is the volatility of the demand
matrix. Optimization models usually try to handle this using stochastic
optimization techniques or robust optimization. We propose a different
approach in optimizing the demand matrix. We try to find a balanced
matrix by asking some customers to ship another day or from a different terminal (if possible), so the problem we try to solve is: which
customer should we ask and what should we offer him for his inconvenience? We will discuss some modelling issues on this problem and
present some results on real-life instances.
3 - A Decomposition Method for Multi-Period Network
Expansion
Andreas Bärmann, Alexander Martin
We present a mixed-integer model for the expansion of the edge capacities in a multi-commodity flow network over multiple periods. It
allows several different types of upgrades per edge with varying implementation times. Its output is a schedule indicating the expansions
to be realized in each period to maximize the throughput. For the solution of this large-scale problem, we propose a timewise decomposition
scheme to obtain high quality solutions. The method is applied to data
for the German railway network and traffic forecasts until 2030 from
our partner Deutsche Bahn AG.
4 - Optimization Based Real-Time Decision Support at
Motorail Terminals
Pascal Lutter, Brigitte Werners
Motorail transportation deals with long distance transportation of passengers along with their vehicles on a train. Vehicles are loaded onto
special motorail transportation wagons at motorail terminals which differ from container terminals regarding layout, storage space and transport goods. Due to limited loading time, shunting and loading operations have to be performed very fast. A mathematical optimization
model is developed to select subsets of vehicles for rapid shunting and
loading operations. We present the implementation and show results
of our real-world decision support system.
MA-02
Monday, 8:30-10:00 - Room 111
Routing Problems with Profits and Other
Applications
Stream: Vehicle Routing
Invited session
Chair: José Manuel Belenguer
2
1 - A New Vehicle Routing Problem: Models and Algorithm
Qie He, Ricardo Fukasawa, Yongjia Song
We study a capacitated vehicle routing problem (CVRP) where the objective is to minimize the total energy consumption. Different from
the traditional CVRP, the objective is a nonlinear function of the edge
variables. Further, we proposed two formulations for the problem: a
one-commodity flow formulation and a set partitioning formulation.
We compare the strength of the LP relaxations of the two formulations
and other related formulations. Finally, we also provide some preliminary computational results based on the two formulations.
2 - Routing for Blood Supply Management
Ali Ekici, Okan Ozener
In this paper, motivated by the practices in blood supply management, we study a variant of the vehicle routing problem. Considering
processing requirements of donated whole blood in order to extract
platelets, we analyze the pickup operations from donation centers and
develop algorithms to maximize the platelet production.
3 - Modeling and Solving the Traveling Salesman Problem with Priority Prizes
Reinaldo Morabito, Henrique Luna, Vitoria Pureza
The Traveling Salesman Problem with Priority Prizes (TSPPP) is an
extension of the classical TSP where the node visitation orders are
taken into account in the objective function. A representation of
the TSPPP is here grounded in the point of view of Koopmans and
Beckmann (1957), where the TSPPP is viewed as a special case of
a quadratic assignment problem. The objective is to find a maximal profit sequence of the client visitations considering the collecting
prizes and traveling costs. Mixed-integer programming formulations
and an ant colony heuristic are presented to cope with the TSPPP.
4 - A Branch-and-Cut Algorithm for the Capacitated
Team Orienteering Problem
Jose M. Belenguer
In the capacitated team orienteering problem, a given set of potential
customers, each one with a demand and a profit, can be collected by a
fleet of capacitated vehicles. The task is to select a subset of customers
with maximum profit and to design a set of routes to collect them in
such a way that constraints on the demand collected and the maximum
time duration of each route are satisfied. Based on a new two-index
formulation, a branch-and-cut algorithm is implemented. The model is
strengthened by new families of constraints. Computational results on
benchmark data sets are reported.
MA-03
Monday, 8:30-10:00 - Room 001
Airline/Airport Optimisation in Operations
and Scheduling
Stream: Aviation
Invited session
Chair: Cheng-Lung Wu
1 - An Operational-Safety Oriented Optimization of Airport Gate Assignment
Yi Gao, Wei Dongxuan
Capacities of many international airports are constrained by shortages
of available gates for arrival flights. This study considers operational
efficiency as well as operational safety, particularly the potential conflict between adjacent gates, in assigning aircraft to airport gates. Instead of relying on ad hoc adjustment to push back timing at gate, we
proposed a model that proactively avoids potential conflicts without
significantly sacrificing efficiency. The testing based on scenarios of
different scales proved that the method is effective in solving conventional gate assignment problem.
IFORS 2014 - Barcelona
2 - The Single Day Aircraft Maintenance Routing Problem
Stephen Maher, Guy Desaulniers, Francois Soumis
Aircraft maintenance planning is of critical importance to the safe and
efficient operations of an airline. Unfortunately, it is common for maintenance plans to become infeasible due to schedule perturbations. This
talk presents a novel approach that ensures a sufficient number of aircraft routes are provided each day to satisfy maintenance requirements
that night. Solving this problem each day nulls the effects of schedule
perturbations from preceding days. The results demonstrate the ability
of this novel planning approach to improve the maintenance plan for a
variety of schedules.
3 - Constraint Programming Model of Integrated Recovery for Aircraft and Crew of Irregular Flight Schedules
Jinfu Zhu, Bo Zhu
The minimum total recovery cost is taken as objective function, the
essential constraint conditions are considered, and the constraint programming model of integrated schedule recovery for aircraft and crew
is built. The searching algorithm is designed by using mixed set programming method. Then examples were analyzed with POEM, the
results show that the total flight delay of the recovered schedule given
by the proposed model were reduced by about 25% compared with the
sequential recovery method and at least one satisfactory solution can
be obtained for all examples.
4 - Auto ID Enhanced Management of Ground Service
Equipment in Concurrent Aircraft Turnarounds
Maurizio Tomasella, Katerina Kalamara, Alan Thorne,
Duncan McFarlane
We study the problem of coordinating ground service equipment in
multiple aircraft turnarounds at the same airport. We quantify the potential for improving operational performance by adopting technologies for automated identification and data capture (Auto-ID), more
precisely Radio Frequency Identification and Real Time Locating Systems. We study the impact of Auto-ID on performance indicators such
as turnaround delays per flight and number of delayed flights per day.
We show results from a discrete event simulation study of the operations of a European Low-Cost-Carrier at a major UK airport.
MA-04
Monday, 8:30-10:00 - Room 119
Supply Chain Planning 1
Stream: Supply Chain Management
Invited session
Chair: Achim Koberstein
1 - Designing a Planning System for Suppliers of the Machine Building Industry
Nicolas Justus, Herbert Meyr
MA-05
3 - A Production Model for an Automobile Plant with
Multiple Main Stages to Support the Bid Process with
a Coordinated Cost Estimation
Andrea Borenich, Peter Greistorfer, Marc Reimann
In the automobile supplier industry companies frequently need to make
bids, typically based on cost estimates for the production process, to
obtain incoming orders. This process is executed in several main stages
which are linked by intra-plant logistics. We consider two separate
optimization approaches as cost estimates: (1) Optimize all the main
stages via a central authority. (2) Inspired by current practice, where
each main stage makes its own cost estimate, we analyze different
mechanisms to coordinate this decentralized approach. The resulting
MILPs are solved with Cplex.
4 - A Stochastic Programming Approach to Determine
Robust Delivery Profiles in Area Forwarding Inbound
Logistics Networks
Achim Koberstein, Tim Schöneberg, Leena Suhl
One technique to coordinate the suppliers’ and the producers’ production plans in a supply chain is the use of delivery profiles, which
provide fixed delivery frequencies for all suppliers. In this work,
we present a two-stage stochastic mixed integer linear programming
model to determine robust delivery profile assignments under uncertain and infrequent demands and complex tariff systems in area forwarding based inbound logistics networks. We evaluate our approach
using real-world data from the automotive industry.
MA-05
Monday, 8:30-10:00 - Room 002
Offshore Upstream Logistics
Stream: Petroleum Logistics
Invited session
Chair: Irina Gribkovskaia
1 - Modelling of Supply Vessel Operations With Simulation
Yauhen Maisiuk, Irina Gribkovskaia
Supply vessel schedules are generated according to service requirements of offshore installations characterized by cargo demand and
weekly visit frequency. Stochastic factors such as weather uncertainty
influence on the execution of schedules so that some visits are not performed. We consider several strategies how the cargo not delivered
as planned may be shipped later. To compare the strategies and analyze their performance a discrete-event simulation model is developed.
Tests on real data illustrate how application of these strategies for annual horizon reduces the number of delayed visits.
2 - Offshore Oilfield Design
Yury Redutskiy
ERP-based (Enterprise Resource Planning) advanced planning systems
use Operations Research methods for solving planning tasks within
ERP-systems as optimal as possible. The companies using such planning systems mostly make quite diverse demands on them. Still in
most cases it is possible to find a number of common demands for a
group of companies which operate in the same industry sector. The
dissertation analyzes how the planning tasks of the Supply Chain Matrix can be modeled for such a planning system taking into account the
specific demands of the machine building industry.
We address modeling and optimization tools behind the Smart Oilfield technology, dominantly used for unconventional wells in offshore
oil production. Decision upon location of the intra-oilfield pipelines
network is made during the design phase of the oilfield development
project. We apply a multi-stage combinatorial optimization algorithm
for the pipelines structure design and for determining pipelines’ capacities. The algorithm is used to analyze how decisions made on different
stages of the pipeline network design influence production efficiency
during the phase of exploiting the reservoir.
2 - Analysis, Design and Optimization of the Transport
of Less than Container Load (LCL) Shipments for Intercontinental Sea Freight
Cornelia Warmer
3 - Evaluating Robustness of Speed Optimized Supply
Vessel Schedules
Aliaksandr Hubin, Ellen Karoline Norlund, Irina
Gribkovskaia
The presentation proposes an appropriate mathematical formulation
for a real case scenario of the Hub Location Problem. The real-case
problem of a leading global supplier of technology deals with the transport of LCL shipments from suppliers (external as well as internal) to
consignee plants while the transport between the consolidation points
is by sea. To set up a worldwide consolidation network, different potential consolidation points can be chosen and nonlinear costs are considered. The presentation compares a path and a stage oriented formulation for real life situations.
Offshore installations need supply vessel services on a regular basis.
Weather uncertainty impacts on how service is performed. We incorporate different robustness and speed optimization strategies into
the two-phase optimization procedure for generation of supply vessel
schedules. To compare performance of these strategies by evaluating
robustness of generated schedules with different service parameters a
discrete-event simulation model is developed. Based on results from
simulation strategies for improving robustness incorporated into the
simulation model are applied to modify the schedules.
3
MA-06
IFORS 2014 - Barcelona
4 - Robust Supply Vessel Planning with Speed Optimization
Irina Gribkovskaia, Ellen Karoline Norlund
The oil and gas industry needs reliable transport of cargo between onshore bases and offshore installations. Weather uncertainty and sailing
speed should be taken into account in supply vessel planning. To address the problem of generating robust and green supply vessel schedules a method combining discrete-event simulation with speed optimization algorithms for voyage generation and applying stochastic optimization for schedule construction is developed. Results of tests on
real instances show increased robustness and reduced emissions compared to deterministic planning with constant speed.
MA-06
are used to estimate potential travel time savings for shifting commercial vehicle movements to off-peak hours. The study concludes with a
discussion of the predictions from big data based analysis and network
simulation model.
MA-07
Monday, 8:30-10:00 - Room 003
Models for Gas and Electricity Markets
Stream: Equilibrium Problems in Energy
Invited session
Chair: Asgeir Tomasgard
Monday, 8:30-10:00 - Room 211
City Logistic Operations
Stream: City Logistics and Freight Demand Modeling
Invited session
Chair: Eiichi Taniguchi
1 - Parking Slot Assignment for Urban Distribution:
Models and Formulations
Mireia Roca-Riu, Elena Fernandez, Miquel Estrada
The adequate management of parking space, particularly loading and
unloading areas, is a key element in urban distribution. An in-advance
booking system can be very useful for city councils and transport operators. The Parking Slot Assignment Problem is defined to aid the
implementation of such a system. Mathematical programming formulations are presented for different optimization criteria. Models are
analyzed and compared among them, also through extensive computational experience, which provides quantitative indicators of the quality
of each formulation.
2 - Evaluating City Logistics Measures for Efficient Management of Road Network Using Multi-agent Systems Model and Geographic Information Systems
Joel S-E Teo, Eiichi Taniguchi, Ali Qureshi
The road authorities in many countries are placing more emphasis on
freight traffic and their impacts on the current road infrastructure in recent years due to the effects of rapid urbanization. This research seeks
to provide the road authorities with a decision tool using a multi-agent
systems approach. The tool incorporates the vehicle routing problem
with time window models and is supported by geographic information
systems. The evaluated city logistics measures are mainly associated
with road infrastructure and network management to achieve an overall
benefit for all stakeholders.
3 - Assessing Impacts Of Sustainable Freight Transport
Measures On Urban Areas
Carina Thaller, Uwe Clausen
In agglomerations a growth of population and economic activities is
observed. The consequences are an increase in handling of goods and
urban freight transport. To assess and simulate the impacts on environment, valid models should be developed to identify effective sustainable transport and logistics measures. Therefore, the authors present an
evaluation of system dynamics and freight transport models. Outcome
is that it is necessary to enable a combination. Hence, the forecast
capability of system dynamics and the detailed resolution of transport
simulation could be used mutually.
4 - Network Simulation versus Big Data: A Case Study
of Traffic Impact Analysis for Off-Hour Deliveries in
New York City
Kaan Ozbay, Ender Morgul
In this paper estimation of the impacts of an Off-Hours Delivery
(OHD) program to the traffic network of Manhattan and the New York
metropolitan area are studied. First, a transportation network simulation is used to simulate the effects of the OHD program on the entire
NYC network. Then, GPS data collected from delivery trucks and taxis
4
1 - A Multi-Period Stochastic Equilibrium Model for
Global Energy Markets
Zhonghua Su, Ruud Egging, Asgeir Tomasgard
We present a multi-period stochastic equilibrium model for global energy markets with players in the supply chains of various fuels. By using multi-horizon scenario trees, uncertainties are classified into longterm and short-term, both of which affect strategic investment decisions and operational decisions. Further, we suppose that all players
have symmetric information of scenarios and that upstream producers
are Cournot players. By solving this one-level game model, equilibriums are reached, which are contingent on scenarios. Finally, a case
study of Chinese CO2 cap policy is discussed.
2 - Market Power in the German Electricity Market - Increasing Renewable Shares and Congestion Management
Jonas Egerer
Market power has been an important research question for electricity market models, since the market liberalization in the 1990s. Since
then, the increasing share of renewable generation has altered the possibilities to execute market power in Germany. We analyze the effects
for the German electricity market with an equilibrium model representing a Cournot market. The model is applied to different market
designs, including uniform pricing, zonal pricing and nodal pricing
schemes.
3 - Modeling Renewable Energy Support Policies for the
European Power Sector
Christian Skar, Per Ivar Helgesen, Asgeir Tomasgard
We present a capacity investment model for the European power sector,
formulated as a two-stage stochastic game between generation companies. The aim is to analyse different support policies for renewable
power production, and how size and location of new capacity investments are affected by the policy scheme selected. The model is tested
on three scenarios: a European wide green certificate market, a European wide feed-in tariff system, and a mixed scheme where each nation
define independent policies.
4 - Interaction Between Energy Systems Models and
Computable General Equilibrium Models
Per Ivar Helgesen, Asgeir Tomasgard
Bottom up energy system models are often solved using linear programming techniques in order to minimize the costs of producing the
projected energy demand. It is desirable to complement such models
with top-down Computable General Equilibrium models. These are
usually formulated and solved as Mixed Complementarity problems.
Empirical models are usually linked by a heuristic approach. The purpose of an integrated approach is twofold: 1) Check whether heuristic approaches are able to find equilibrium solutions, and 2) Replace
heuristic linking by integrated models.
IFORS 2014 - Barcelona
MA-08
Monday, 8:30-10:00 - Room 120
Energy and Environmental Management
Stream: Energy Economics, Environmental Management and Multicriteria Decision Making
Invited session
Chair: Peter Letmathe
Chair: Wolf Fichtner
1 - Classification of Power Quality Considering Voltage
Sags Occurred in Feeders
Pedro Steiner Neto, Anderson Roges Teixeira Goes, Maria
Teresinha Arns Steiner
In this paper we propose a methodology to classify Power Quality for
feeders, based on sags and by the use of KDD technique, establishing
a quality level printed in labels. To support the methodology, it was applied to feeders on a substation located in Curitiba, Paraná, Brazil. The
attributes considered were sag length, duration and frequency (number
of occurrences) on a given period of time. On the Data Mining phase,
three different techniques were used comparatively: ANN; SVM and
GA. With this kind of work, the utilities companies can get better organized for mitigation procedures.
2 - Long-term Effects of Power-to-Gas Storage Technology on Power Plant Dispatch Optimisation in Germany
Tobias Heffels, Russell McKenna, Wolf Fichtner
In the context of structural changes within the German power system,
the bottom-up optimisation model PERSEUS-NET performs an integrated long-term dispatch and expansion planning of the power plant
mix, considering transmission network restrictions. Since the size of
the optimisation problem restricts the temporal resolution and the possibility to model non-linear dependencies, a more detailed dispatch
model, based on a rolling horizon approach and a higher temporal resolution, is developed to analyse the effects of storage capacity, especially power-to-gas, on the power system in detail.
3 - Optimization Methods for the Dimensioning of Distributed Energy Systems
Sabrina Ried, Melanie Reuter, Birte Carstens, Patrick Jochem,
Wolf Fichtner
Distributed energy systems (DES) generate electricity close to the demand centers. They can be grid-connected or not, but they usually
always aim at a high degree of self-sufficiency by integrating renewable energy sources. When planning a new DES, dimensioning the
system is the first step of the technical and financial planning. This
contribution gives an overview on different approaches for the dimensioning of the components of DES based on a literature review. An
analysis is conducted on the suitability of the different approaches and
their advantages and disadvantages.
4 - Synthetic Generation of Solar Radiation Data Sets
John Boland
The evaluation of the performance of a system governed by climate
variables is best achieved by mathematical models of the performance
of the system. The climate inputs to the model must be realistic, representing the climate plus weather variations where the system will be
installed. The most effective way of creating test data sets is the construction of synthetic sequences of climatic variables. I model a solar
radiation time series and from that construct an algorithm to generate
any number of years of synthetic data, using methods in Magnano and
Boland (2007) and Huang et al. (2013).
MA-09
Monday, 8:30-10:00 - Room 121
Dynamical Systems and Mathematical
Modelling
Stream: Dynamical Systems and Mathematical Modelling in OR
Invited session
Chair: Gerhard-Wilhelm Weber
MA-10
Chair: Yutaka Kimura
Chair: Yukihiro Maruyama
1 - Optimal Control of Treatment of HIV Infection Using
Neural Network
Samir Talssi
We developed a new approach for optimal control of drug treatment
of HIV infection using neural network techniques. This approach provides us with an independent perspective mechanism of ideas specific
to the therapy, and has allowed rapid understanding of the behavior
of HIV during treatment, this speed will help us to make good decisions with the aim of reducing the cost of treatment and avoid critical
infection. A numerical simulation was performed to demonstrate the
efficiency of this neuronal approach.
2 - A New Statement of the Optimal Control Problem of
the Metal Crystallization Process in Casting
Alla Albu, Vladimir Zubov
An optimal control problem of the metal crystallization process is investigated for a new model of the furnace. The mathematical model is
based on a three-dimensional two-phase initial-boundary problem of
the Stefan type. The problem was solved numerically using the gradient methods. To calculate the gradient of the cost function the Fast
Automatic Differentiation methodology was used. It is shown that the
new model of the furnace leads to a much better crystallization process. This work was supported by RFBR N12-01-00572- and by the
Program for Fundamental Research of Presidium of RAS P18.
3 - Maintenance Policies for Modular Monotonic MultiState Systems
Michael Krause
Modular monotonic multi-state systems consist of several components
(modularity), where the maintenance of one component does not impair the performance of the system (monotonicity) and every component may have n states. We assume that the structure function, the
stochastic processes for the deterioration of the single components,
and the (opportunity) cost for the deterioration of the system performance and for repairs are known. We seek a component-specific strategy which minimizes the sum of the costs for maintenance and deterioration of the system performance in the planning horizon.
MA-10
Monday, 8:30-10:00 - Room 122
Optimization Methods for Smartgrid
Management
Stream: Optimization Models and Algorithms in Energy
Industry
Invited session
Chair: Cristina Corchero
Chair: Miguel Cruz-Zambrano
1 - Optimal Energy Management System for a Residential Microgrid
Cristina Corchero, Lucia Igualada, Miguel Cruz-Zambrano
The optimal management algorithm presented in this work covers from
short-term decisions to the real-time ones. Starting with a 24 hours
horizon discretized in quarter-hourly intervals, the algorithm solves a
problem based on a Unit Commitment and Economic Dispatch problems. The management system takes measures at real time to correct
the deviations regarding to the initial forecast data. The corrections are
optimally computed every 30 seconds, and they are recalculated before
to send the set-points every 3 second to the microgrid.
5
MA-11
IFORS 2014 - Barcelona
2 - Cooperative Day-Ahead DSM for Expected Cost Minimization in Microgrids
Italo Atzeni, Luis G. Ordóñez, Gesualdo Scutari, Daniel
Palomar, Javier Fonollosa
provided by a problem relaxation. A final refinement is also applied
that inserts connectivity cuts in a heuristic way. All methods are tested
on benchmark instances and compared to state of art algorithms. We
solve to optimality all open instances.
Microgrids are the local-level building blocks of the smart power grid
that intelligently integrate renewable sources and enable customer participation. We discuss a holistic-based, distributed day-ahead DSM
method where the subscribers of a microgrid derive the bidding, dispatchable production, and storage strategies that minimize their overall
expected monetary expense. In this setting, we propose a cooperative
algorithm providing such optimal strategies in a distributed fashion.
We show that collaboration yields greater savings with respect to the
corresponding user-oriented optimization.
3 - A Large Neighborhood Search based Matheuristic for
a Real Life Vehicle Routing Problem
Simona Mancini
3 - Operational Planning in Smart Grids: Concept and
Recent Developments
Julio Usaola
Smart Grids and Operational Planning are a challenge for Operational
Research. This planning assesses the benefits of the smart grid technology before the implementation of new control technologies for distribution grids. Operational planning includes generation of random
profiles of prosumers including the output of REN and DER resources
and the probabilistic scheduling for customers with a given level of
flexibility. This schedule must comply with grid constraints. Methods
for solving these problems will be presented and the results of ongoing
research within an EU project.
4 - Optimal Sizing of EV Fast Charging Stations Including Energy Storage and PV Systems
Lucia Igualada, Miguel Cruz-Zambrano, Cristina Corchero
This work focuses on the optimal design of electric vehicle fast charging stations, including storage systems and PV generation for reducing its impact on the electricity distribution network. The mathematical model includes system CAPEX, OPEX and technical constraints.
Different energy cost, usage levels and meteorological scenarios are
considered. The technical viability and cost-effectiveness of installing
storage systems and PV panels for supporting EV fast charging stations
are analyzed and compared for each scenario.
In this paper a new Vehicle Routing Problem arising in real life context is introduced and formalized. The problem goal is to minimize the
total delivery cost. An heterogeneous fleet is considered and a limit on
the maximum route duration is imposed. For each customer is known
the set of periods in which the delivery may be carried out. A Large
Neighborhood Search (LNS) based Matheuristic is proposed, in which
the neighborhood exploration is performed by the means of the MIP
formulation that is able to find the optimal solution in the neighborhood within very few seconds.
4 - An Exact Branch-and-Price Algorithm for the FixedCharge Transportation Problem
Roberto Roberti, Enrico Bartolini, Aristide Mingozzi
In the Fixed-Charge Transportation Problem, destinations request
goods from origins, and a flow from an origin to a destination implies
a variable cost plus a fixed cost. The objective is to minimize the total
cost for serving the destinations. In this talk, we propose a branchand-price algorithm based on a new formulation with exponentially
many variables and a pseudo-polynomial number of constraints. The
resulting exact algorithm is able to solve instances with more than 100
origins and 100 destinations, outperforming the state-of-the-art exact
algorithms from the literature.
MA-12
Monday, 8:30-10:00 - Room 004
Graphs and Networks I
Stream: Graphs and Networks
Invited session
MA-11
Monday, 8:30-10:00 - Room 113
Optimization Methods in Transportation
Systems
Stream: Combinatorial Optimization
Invited session
Chair: Aristide Mingozzi
Chair: Roberto Roberti
1 - The Multiple Vehicle Pickup and Delivery Problem
with LIFO Constraints
Enrique Benavent, Mercedes Landete, Enrique Mota,
Gregorio Tirado
In this paper we consider a time constrained multi-vehicle pickup and
delivery routing problem with LIFO (last-in-first-out) rule of service
and capacity constraints. We propose two mixed integer formulations
of this problem and a tabu search heuristic. The first formulation is a
compact one, that is, the number of variables and constraints is polynomial in the number of requests, while the second one contains an
exponential number of constraints and is used as the basis of a branchand-cut algorithm. The proposed methods are able to optimally solve
medium size instances with up to 61 nodes.
2 - New Results for the Directed Profitable Rural Postman Problem
Renata Mansini, Marco Colombi
In the Directed Profitable Rural Postman Problem some required arcs
may not be served provided that penalty costs are paid. The problem
looks for a tour visiting the selected service arcs while minimizing both
traveling and penalty costs. We develop a branch and cut algorithm using new valid inequalities and a matheuristic exploiting information
6
Chair: Marc Demange
1 - On City Logistics Pickup and Delivery Systems
Abdelkader Sbihi, Marc Demange, Juan Carlos Espinoza
Garcia
City logistic problems aim to use the existent city infrastructure to improve the transportations network for goods delivery to the city centres. In this work, we attempt to build a model for the transportation of
goods in a city with existing tramlines. Each car being a rack where to
store containers, we consider the problem of organizing the containers
in each tram so as to make the delivery possible. We first investigate
very simple tram networks. The underlying problem leads to some
Coloring Problems in particular classes of permutation graphs. We
present some first complexity results.
2 - Pursuit-Evasion Games
David Ellison
The cops and robber game is played on a given graph G by one robber
and a set of cops. The cops work together in order to catch the robber.
First, the cops choose their initial positions on vertices of G, then the
robber does the same. During the cops’ turn, each cop makes a move
along an edge. Then the robber also makes a move along an edge, and
so on. The objective is to determine the minimum number of cops required to catch the robber. 1-cop-win completely looped graphs have
been characterised. In this work, we consider partially looped graphs
for which more complex behaviours may arise.
3 - Complexity of Recognition Algorithms for G-Graphs
Jean-François Culus, Cerasela Tanasescu, Marc Demange,
Ruxandra Marinescu-Ghemeci
We will explore some results about complexity of recognising GGraphs. Like Cayley Graphs, G-Graphs are defined using a group G.
Here, we analyze some properties of G-graphs’ structure, in the case
where G is an abelian group. These properties lead to a polynomial
recognition algorithm for G-graphs.
IFORS 2014 - Barcelona
4 - An Optimal Level of Placing a Liaison with Long
Communication Lengths between All Members of the
Same Level in an Organization Structure of a Complete K-ary Tree
Kiyoshi Sawada
This study proposes a model of placing a liaison which forms relations to all members of the same level in an organization structure of a
complete K-ary tree of height H such that the communication of information between every member in the organization becomes the most
efficient. When lengths of edges between the liaison and the other
members are more than those of edges between members except the
liaison, we have obtained an optimal level which minimizes the total
distance which is the sum of lengths of shortest paths between every
pair of all nodes in a complete K-ary tree.
MA-13
Monday, 8:30-10:00 - Room 123
Scheduling Cluster Tools
Stream: Scheduling
Invited session
Chair: Yuchul Lim
1 - Feedback control of cluster tools for wafer delay regulation
Chulhan Kim, Lee Tae-Eog
As a wafer gets bigger and thinner, quality of a wafer has become an
important factor to consider as well as productivity. In a cluster tool,
variation of wafer delay (waiting time after processing) in each process module has to be kept as low as possible in order to improve and
standardise the quality of wafers. In this study, we suggest a feedback
control technique to operate cluster tools while maintaining the level
of wafer delay. In addition, conditions required for a feasible feedback
control are presented. Finally, we examine the minimum wafer delay
that satisfies the conditions.
2 - Scheduling of Cluster Tools with Complex Scheduling Requirements
Taesun Yu, Lee Tae-Eog
As technology evolves, new types of cluster tools have been invented in
semiconductor manufacturing. A quad-armed cluster tool is the most
advanced equipment that involves complex scheduling requirements
such as four robot arms, chamber cleaning, and input/output modules.
In this study, we examine a robot scheduling problem for quad-armed
cluster tools. We develop an optimization model and derive properties
of the optimal schedule. In addition, we suggest rule based scheduling
techniques to improve the computational efficiency. Finally, the tool
performance is compared with conventional tools.
3 - Efficient Scheduling of Inline Cluster Tools by Decomposition Method
Yuchul Lim, Lee Tae-Eog
An inline cluster tool is a multi-cluster tool that consists of linearly
arranged radial type cluster tools. The architecture of an inline cluster
tool is much more complicated compared to those of traditional cluster tools due to multiple robots, chamber cleaning, and intermediate
buffers between two adjacent tools. In this study, a cyclic scheduling problem of an inline cluster tool is examined. First, the system is
simplified using decomposition method. Then, we suggest an efficient
algorithm to obtain near-optimal and minimum-cycle schedules from
the decomposed models.
4 - Optimizing the Job Shop Scheduling Problem - a
Neuro-Genetic Approach
Tomas Eloy Salais Fierro, Jania Saucedo, Giovanni Lizarraga
The purpose of this work is to make use of fuzzy adaptive resonance
theory to look for patterns in data generated by a genetic algorithm
performing a scheduling operation. Fuzzy ART approximates the genetic algorithm’s output developing a rule set scheduler. In using a
genetic algorithm for job shop scheduling, the solution is an operational sequence for resource allocation. The knowledge acquired by
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the ANN is applied in solving similar problems duplicating the genetic
algorithm’s performance and provides solutions that may be superior
to simple dispatching rules for similar problems.
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Monday, 8:30-10:00 - Room 124
Realistic Production Scheduling
Stream: Realistic Production Scheduling
Invited session
Chair: Ruben Ruiz
1 - Bi-Criteria Scheduling on a Batching Machine to Minimize Maximum Lateness and Makespan
Edgar Possani, Marta Cabo Nodar
We study the problem of scheduling n jobs on a batching machine to
minimize the maximum lateness and makespan simultaneously, motivated by the burn-in operations of semiconductors. The batching machine has a restricted batch size of b < n, and the processing time of
a batch is equal to the largest processing time of all jobs in a batch.
We present an exponential neighborhood that can be searched in polynomial time for the maximum lateness objective. Based on this, we
develop dynamic programming algorithms to approximate and/or find
the Pareto optimal solutions for the bi-criteria problem.
2 - On Generic Approaches to Prove NP-Hardness and
to Construct Efficient Algorithms for some Scheduling Problems
Radoslaw Rudek, Agnieszka Rudek
A generic approach to prove NP-hardness of some scheduling problems with variable job processing times is proposed. Although it does
not follow "use a formula", but it significantly supports the construction of relevant transformations. Additionally, some sufficient and acceptable simplifications are discussed, which bring closer the idea. The
considered method is depicted on the basis of examples. Furthermore,
to make the results complement, some approaches to construct efficient
algorithms for such problems are provided and analysed.
3 - New Results for the Distributed Permutation Flowshop Problem
Ruben Ruiz, Bahman Naderi
The distributed permutation flowshop problem has been recently proposed as a generalization of the regular flowshop setting where more
than one factory is available to process jobs. Despite being recently
introduced, this interesting scheduling problem has attracted attention
and several heuristic and metaheuristic methods have been proposed in
the literature. In this paper we present a scatter search (SS) method for
this problem to optimize makespan. A comprehensive computational
comparison against 10 existing methods shows that the proposed algorithms produces the best results.
4 - Bottleneck Based CONWIP System in Make-to-Order
Manufacturing
Uğur Kahya, Nihal Erginel
CONWIP (CONstant Work-In-Process) has proposed a system by considering both push-based MRP and pull-based Kanban systems. In this
work, a bottleneck based CONWIP (B-CONWIP) mathematical model
is developed to make-to-order manufacturing environment to aim create backlog list which has scheduled orders. The mathematical model
which emerges production scheduling and lot sizes with using bottleneck machine’s data is proposed. Its objective function has lateness as
manufacturing cost and unbalanced workload cost as the requirements
of B-CONWIP. It is solved with a real world data by CPLEX.
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Monday, 8:30-10:00 - Room 125
Network Pricing
Stream: Revenue Management I
Invited session
Chair: Patrice Marcotte
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IFORS 2014 - Barcelona
Chair: Rob Zuidwijk
1 - Bilevel Modelling of Energy Pricing Problem
Luce Brotcorne, Sezin Afsar, Patrice Marcotte, Gilles Savard
Pricing models for demand side management methods are traditionally used to control energy demand which became quite irregular with
the recent technological developments and resulted in fluctuations and
inefficiency in supply. We propose several bilevel models along with
exact and approximate solution procedures to explore the relation and
conflict between energy suppliers and customers who are interconnected via smart meters. Besides, this approach enables to integrate
customer response into the optimization process of supplier who aims
to maximize revenue or minimize capacity requirements.
2 - Joint Design and Pricing of Intermodal PortHinterland Network Services:
Considering
Economies of Scale and Service Time Constraints
Panagiotis Ypsilantis, Rob Zuidwijk
Container terminal operators actively participate in landside transport
networks to enhance their connectivity to inland destinations. They
have developed so-called extended gates in which sea port container
terminals are connected to inland container terminals via frequent services via river vessel and train. We formulate the joint design and
pricing of such intermodal freight network services as a bi-level MIP.
We consider the intermodal nature of the problem by considering frequency dependent economies of scale and service times. A solution
approach and managerial insights are presented.
3 - A Branch-and-Price Algorithm for the Network Pricing Problem with Connected Toll Arcs
Alessia Violin, Bernard Fortz, Martine Labbé
We propose a branch-and-price approach to solve a pricing problem
on a network with connected toll arcs. The model is obtained with
a Dantzig-Wolfe reformulation, and a column generation algorithm is
used to solve the linear relaxation. Various techniques have been considered to improve the efficiency of the solving algorithm, such as stabilisation and different branching strategies. Numerical results show
the effectiveness of this approach.
4 - A Mathematical Programming Approach to Compute Booking Limits under a Non-Parametric Choice
Model
Gilles Savard, Morad Hosseinalifam, Patrice Marcotte
We present a new customer choice-based approach for computing
booking limits in revenue management. The mathematical formulation
is based on the CDLP linear model, where customer behavior is characterized by preference lists, and where additional constraints enforce
that booking limits be nested. We propose for its solution a column
generation procedure based on the efficient (heuristic) solution of the
NP-hard subproblem. Computational results show that this approach
outperforms alternatives from the current literature.
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Monday, 8:30-10:00 - Room 127
Copositive and Polynomial Optimization I
Stream: Copositive and Polynomial Optimization
Invited session
Chair: Mohab Safey El Din
2 - Exact Safety Verification of Hybrid Systems Based
on Bilinear SOS Representation
Zhengfeng Yang
In this talk, we address the problem of safety verification of hybrid systems. A symbolic-numeric method is presented to compute inequality
invariants of hybrid systems efficiently. Some numerical invariants of
a hybrid system can be obtained by solving a bilinear SOS programming via PENBMI solver or iterative method, then the modified Newton refinement and rational vector recovery are applied to obtain exact
polynomial invariants with rational coefficients, which satisfy the conditions of invariants. Experiments on some benchmarks are given to
illustrate the efficiency of our algorithm.
3 - Border Basis Relaxation for Polynomial Optimization
Marta Abril Bucero
A relaxation method based on border basis reduction which improves
the efficiency of Lasserre’s approach is proposed to compute the optimum of a polynomial function on a basic closed semi algebraic set. A
new stopping criteria is given to detect when the relaxation sequence
reaches the minimum, using a sparse flat extension criteria. We also
provide a new algorithm to reconstruct a finite sum of weighted Dirac
measures from a truncated sequence of moments. We propose a new
algorithm to compute zero-dimensional minimizer ideals and the minimizer points or zero-dimensional G-radical ideals.
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Monday, 8:30-10:00 - Room 005
Global Optimization, Modelling and Data
Mining
Stream: Global Optimization
Invited session
Chair: David Gao
Chair: Inci Batmaz
1 - The Problem of Covering Solids by Spheres of Different Diameters
Marilis Venceslau, Renan Pinto, Helder Venceslau, Nelson
Maculan
An alternative mathematical programming model for the problem of
covering solids by spheres of different diameters will be presented.
Given a set of spheres, possibly with different diameters, and a solid,
the goal is to locate the spheres in such a way that their union forms a
coverage for this solid, using the smallest possible number of spheres
of this set. This problem has a specific application in the radiosurgical treatment planning known as Gamma Knife and can be formulated
as a nonconvex optimization problem with quadratic constraints and a
linear objective function.
2 - External Sensors for Monitoring of Domains
Sergey Astrakov
Let the scope of the sensor be a disc. Then a model of domain monitoring is a cover of a region S by a set of disks C. The cover density is
defined as the ratio of the area of all disks C to the area of S. We determine a min-density of external cover where the disc’s centers shall
not be inside the domain. It is shown that the best external monitoring
models of the circular area use three or four sensors. In both cases it is
possible to achieve a minimum density D=3. The best external monitoring model of the square area uses four sensors and determines the
minimum density D=3/42,3562.
1 - Computing Efficiently Real Points on Determinantal
Varieties
Simone Naldi, Didier Henrion, Mohab Safey El Din
3 - Adaptive Artificial Bee Colony Algorithm for Global
Optimization
Erdal Emel, Alkin Yurtkuran
We are interested in the study of algebraic varieties defined by rank
constraints on matrices whose entries are linear forms with rational
coefficients. Our main contribution concerns the construction of efficient exact algorithms for finding real points in every connected component of these determinantal varieties. Solving this problem in a good
complexity class, taking advantage of the geometric structure of the
problem, is required in many scientific areas, like convex optimization
or convex algebraic geometry. I will present a joint work with Didier
Henrion and Mohab Safey El Din.
Artificial bee colony (ABC) algorithm is one of the most popular
swarm based meta-heuristic algorithms. ABC simulates the intelligent
foraging behavior of honeybee swarms. This study proposes a modified ABC algorithm that benefits from a variety of search strategies
in literature to balance exploration and exploitation. In the modified
version of the ABC algorithm, an adaptive search strategy selection
mechanism is used in each cycle. Proposed algorithm is tested on wellknown benchmark functions and computational results reveal that the
proposed technique is very efficient.
8
IFORS 2014 - Barcelona
4 - Predicting the Amount of Precipitation of Eastern
Black Sea Region by VARMA Models
Ceyda Yazici, Ceylan Yozgatligil
Global warming has many effects on climate including droughts, extreme weather events, changes in temperature, etc.. Extreme amount
of precipitation, which is experienced frequently in the last years, can
cause floods, harm on crops and damage on urban areas. Thus, it is
important to predict the amount of precipitation to take precautions if
possible. There are several methods used for this purpose in the literature. In this study, VARMA, which is a time series model, is used
to predict the amount of precipitation of Eastern Black Sea Region of
Turkey.
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Monday, 8:30-10:00 - Room 112
Multiobjective Optimization in Practice
Stream: Multiobjective Optimization - Theory, Methods
and Applications
Invited session
Chair: Karl-Heinz Kuefer
Chair: Volker Maag
1 - Multiobjective Layout Planning of Photovoltaic
Power Plants
Martin Bischoff, Ingmar Schüle, Kai Plociennik
We present an innovative layout planning and optimization concept for
large-scale ground-mounted photovoltaic power plants. By analyzing
multiple technical and economical quality measures for a set of automatically generated candidate solutions, planners obtain an overview
on the solution space. We highlight interaction functionalities at various stages of the workflow, which facilitate attaining the best projectspecific planning result with little effort of time. We have realized
this concept in the software PVplanet, which is succesfully used by
Siemens engineers since more than two years.
2 - A Ray Tracing Technique for the Pareto Set Navigation
Dimitri Nowak
In practice, we often encounter the problem of choosing between solutions determined by multiple conflicting criteria. The goal is to identify
the non-dominated solutions and present them to the decision maker.
A good presentation of such Pareto frontier is essential.
We introduce a new interactive approach to navigate the decision
maker on a possibly non-convex approximation of the Pareto frontier.
Given a finite number of precalculated Pareto solutions, we generate
an adapted Delaunay triangulation. Combining this with a ray tracing
technique, we obtain a new navigation method.
3 - Multiple Criteria Decision-Making in Medical Treatment Planning - is Pareto Efficiency Enough?
Philipp Süss
Planning an intensity-modulated radiation therapy (IMRT) is to determine an energy fluence to so that the resulting dose in the patient’s
body balances the potential for treatment success and risk of sideeffects. The planning problem can be formulated as a convex optimization problem with multiple criteria and several methods to balance
the involved trade-offs exist. However, can multicriteria optimization
solve real-life problems? We focus on practical aspects of decision
support in IMRT planning and present mathematical approaches for
modern multicriteria treatment planning.
4 - A Dimension Reduction Approach for the Nondominated Set Approximation
Volker Maag
For a interactive presentation of the non-dominated set of a non-trivial
MCO problem it is often necessary to replace the original set by an
approximation. This is the more difficult to get the more objectives
there are. In the talk we present an approach for convex MCO problems to reduce the number of dimensions by introducing a new, lowerdimensional space for the approximation. This space is obtained by
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a clever projection of the original image space, which minimizes the
error introduced by the loss of dimensions. The approach is illustrated
by numerical examples from radiation therapy.
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Monday, 8:30-10:00 - Room 128
Retail Shelf and Inventory Planning
Stream: Demand and Supply Planning in Consumer
Goods and Retailing
Invited session
Chair: Heinrich Kuhn
1 - A Decision Support System for Retail Assortment
Planning with Substitution Effects
Alexander Hübner, Heinrich Kuhn
As the increasing product variety in the retail trade is in conflict with
the limited shelf space available, managing assortment and shelf space
is a core Problem in retailing. We identify the underlying planning
problems and develop a Newsvendor-based capacitated assortment
problem with stochastic demand and substitution effects. Our numerical examples reveal, that out-of-assortment and out-of-stock substitution effects have a significant impact on total profit and solution structure. We show that our model is scalable to practically relevant problem sizes.
2 - A New MIP Formulation for the Location and Allocation of Products and Product Families on Retail
Shelves
Teresa Bianchi-Aguiar, Elsa Silva, Luis Guimarães, Maria
Antónia Carravilla, José Fernando Oliveira
We present a new formulation for the location and allocation of products on shelves. Besides deciding the number of facings for each product, the model includes products’ sequencing and positioning, respecting real word constraints such as product families grouping in rectangular shapes. We shifted from traditional literature formulations based
on the multi-knapsack to commodity flow formulations and used goal
programming to handle nonlinearities. An extension to the formulation
considers multi-level product grouping. We embedded the formulation
in a matheuristic to derive faster solutions.
3 - Data-Driven Order Policies with Censored Demand
and Substitution in Retailing
Anna-Lena Sachs, Stefan Minner
We formulate a data-driven model for perishable products that takes
prevalent retail characteristics into account. The model integrates forecasting and inventory optimization by considering the effects of external factors on demand, unobservable lost sales and substitution behavior. Our numerical study and real data from a large European retail
chain show that the model achieves higher profits than existing approaches. We find that fitting the model on highly censored data yields
higher profits since more can be learnt about substitution behavior than
based on data with almost no censoring.
4 - A Conic Optimization Approach for SKU Rationalization
Tanguy Kegelart, Mathieu Van Vyve
This paper develops a mixed-integer nonlinear mathematical program
to support efficient product portfolio reductions. In our model, the
fixed costs elimination and the risk-pooling effects balance the demand
contraction due to customer dissatisfaction. Off-the-shelve MIQP
solver provides optimal solution to the proposed conic quadratic reformulation, and a real-life industrial case illustrates the program and
the algorithm efficiency. Findings show that our mathematical programming subject to various assumptions and estimations is efficient
to rationalize portfolios up to at least 400 SKUs.
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IFORS 2014 - Barcelona
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IFORS Prize for OR in Development 2014 1
Optimization Modeling Software &
Systems 1
Stream: IFORS Prize for OR in Development 2014
Award Competition session
Stream: Optimization Modeling in OR/MS
Invited session
Monday, 8:30-10:00 - Room 129
Chair: Andrés Weintraub
1 - Emergency Engineering Rescue Scheduling and its
Application in Disaster Relief Operations in China
Zheng Yu-Jun
Disaster relief operations typically involve a large number of engineering rescue tasks, the completion of which is vital to the success of
the operations. The paper establishes a model of emergency engineering rescue scheduling, which involves multiple rescue teams and tasks,
different and perhaps fuzzy processing times, as well as different importance weights of the tasks. We then propose a solution method
based on biogeography-based optimization (BBO), develop effective
migration and mutation operators, and employ a multiobjective optimization approach for provide a set of candidate solutions for decision
support. Computational experiments demonstrate that our approach
can provide competitive performance in test problems. The proposed
model and method have been successfully applied to the very recent
2013 Dixi Earthquake occurred in China. Keywords: Emergency engineering rescue scheduling, multi-expert decision, multiobjective optimization (MOO), biogeography-based optimization (BBO).
2 - A Multi-Period Fleet Allocation Model for the Santiago Fire Department
Juan Perez, Sebastian Maldonado
The city of Santiago de Chile has experienced significant but uneven
growth in the last few decades, while the location of fire stations and
their resources have experienced little change. Additionally, the lack
of a centralized and coordinated assignment of resources has caused
a significant increment in the average response times in some zones,
leading to inefficient and inequitable service. In this study we propose
a multi-period fleet assignment model for the Santiago Fire Department. In order to include the seasonal effects observed in the data,
a time-series analysis is also presented for forecasting the occurrence
of future events, and used as input for the mathematical programming
problem. According to our results, an improvement of 10% can be
achieved in terms of response time compared to the current scenario
by reallocating the existing resources in an optimal way, without the
need of adding more fire engines.
3 - Public Transit Planning and Scheduling Based on
AVL Data in China
Yindong Shen
The public transit operation planning process commonly includes the
following activities: network route design, service planning (frequency
setting and timetabling) and scheduling (vehicle scheduling, crew
scheduling and rostering). However, the network route design is generally the only one widely recognized, whilst the service planning and
scheduling are often ignored in China. This leads to the lack of elaborate timetables and schedules, hence, transit operation is often in disorder with high operating cost. To raise the service level and the utilization of resources, this paper presents an applied study for three cities
in China, focusing on the enhancement of the cognition and means of
public transit planning and scheduling. A comprehensive framework
of public transit planning is first proposed, which is composed of Chinese traditional three items (i.e., network route design, land use for
depots and equipment with vehicles) and the following newly added
items: intelligent public transit system (IPTS) planning, service planning and scheduling. This is pioneering work in China, during which
an IPTS is planned and a random model and solution methods for vehicle scheduling based on AVL data are developed. Experiments under the actual projects show that vehicle schedules with high on-time
probability and low cost were compiled, while the essential input parameters such as headways and trip times were set automatically. It is
anticipated that the research fruits and practical experiences obtained
would be of great benefit in increasing service and management level
and resource use to the public transport in China and some other developing countries.
10
Monday, 8:30-10:00 - Room 006
Chair: Robert Fourer
1 - Recent Enhancements in GAMS
Toni Lastusilta
From the beginning in the 1970s at the World Bank till today, GAMS,
the General Algebraic Modeling System, has evolved continuously in
response to user requirements, changes in computing environments
and advances in the theory and practice of mathematical programing.
We will outline several recent enhancements of GAMS supporting efficient and productive development of optimization based decision support applications.
2 - Network Algorithms, Constraint Programming, and
Decomposition in the SAS/OR OPTMODEL Modeling
Language
Leo Lopes, Rob Pratt, Jack Rouse
We present three new features of the OPTMODEL modeling language
in SAS/OR software: solving many network-based problems, including Linear Assignment, Minimum-Cost Network Flow, Shortest Path,
and Traveling Salesman, without requiring any formulation at all; solving Constraint Logic Programming problems; and solving problems
with block-angular structure that is either detected automatically or
conveyed by the user with a minimal amount of syntax.
3 - New AMPL Interfaces for Enhanced Development
and Deployment of Optimization Models
Robert Fourer
Although modeling languages are best known for providing a highlevel interface to optimization solvers, it is just as important that they
interface well with users and with applications. This presentation describes new interfaces that have been developed to meet the interface
needs of the AMPL modeling language and system. AMPL IDE provides an integrated command interpreter and file editor for model development. AMPL API supports model deployment by enabling applications to invoke many AMPL functions directly, using calls written in
popular programming and analytics languages.
4 - Supporting Business Decision Making
Sofiane Oussedik
This presentation will give you an insight into some of the latest clients
use cases using IBM ILOG Optimization, and in which decision aid
to support the user making the decision was key. The use cases developments have been driven by the need to accomplish key business
objectives and deploy the right flexible solution to the user. The presentation will include details on the business problem solved and the
challenges faced, as well as the need for a seamless integration with
existing systems and processes.
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Monday, 8:30-10:00 - Room 007
Stochastic Models
Stream: Health Care Data Analytics
Invited session
Chair: Kelvin Yau
1 - A Simulation Approach to Assess the Adequacy
of Survival Mixture Models: Application to Public
Health
Andy Lee, Kelvin Yau, Yer Van Hui
IFORS 2014 - Barcelona
The Weibull proportional hazards model is commonly used in survival
analysis. It is important to determine adequacy of the fitted model,
yet formal testing is lacking, as residual-based measures are inappropriate for censored data. This study develops a diagnostic method for
assessing the adequacy of Weibull survival mixture models with random effects. An assessment procedure using Cox-Snell residuals is
constructed based on a simulated envelope approach, with further simulations performed to investigate the validity of the procedure. The
method is illustrated with public health applications.
2 - A POMDP Model to Evaluate the Inclusion of HPVDNA Test for Cervical Cancer Screening
Raha Akhavan-Tabatabaei, Esma Gel, Martha Isabel Namen
Leon
Cervical cancer is one of the main causes of death among women in
developing countries. Different screening polices have been proposed
in order to prevent this disease, in the medical community. One of the
newest and most popular is the HPV-DNA test as primary screening.
This paper proposes a POMDP model in order to evaluate the inclusion
of HPV-DNA as co-testing along with cytology, and also to determine
the optimal number of tests to be performed in the lifetime of a patient.
Age-specific cost-effective optimal policies comparing both QALYs
and the costs of tests are presented.
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3 - How to Conduct Behavioural OR Studies: A Typology
L. Alberto Franco, Etienne Rouwette
In this presentation we discuss a typology of four approaches for conducting Behavioural OR studies. Although the four approaches could
be seen as representing competing perspectives, we see them as being complementary. Each approach provides a different -yet partialunderstanding of the behavioural dimension of OR. We argue that coordinating the pluralistic insights from the four approaches can provide
a richer understanding of Behavioural OR as a field.
4 - An Outlook on Behavioural OR — Three Tasks, Three
Pitfalls and One Definition
Kai Helge Becker
In their recent paper, Hämäläinen, Luoma and Saarinen (2013) have
made a strong case for the importance of Behavioural OR. With the
motivation to contribute to a broad academic outlook in this emerging
discipline, my rather programmatic talk intends to further the discussion by describing three types of research questions I envision as the
primary focus of Behavioural OR. Moreover, by relating Behavioural
OR to similar academic endeavours, I will discuss three potential pitfalls Behavioural OR should avoid. I will sum up all points addressed
by suggesting a definition of Behavioural OR.
3 - Admission Policies for Walk-in Patients at a Diagnostic Clinic
Nomesh Bolia, Naman Garg, Rahul Malhotra
This paper identifies a walk-in admission policy to minimize revenue
loss in case of appointment no-shows in diagnostic scan centers. A dynamic programming model helps decide whether to admit a walk-in,
for each state of the system, that is, for all values of system time and
walk-in queue length. The optimal choice is obtained by comparing
the expected reward contingent on such a choice. A simulation is run
after introducing additional stochasticity in the model and the admission policy is compared with alternative heuristics. Results favor the
use of the dynamic programming model in practice.
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Monday, 8:30-10:00 - Room 008
Perspectives on Behavioural Operations
Research
Stream: Behavioural Operational Research
Invited session
Chair: L. Alberto Franco
1 - On the Importantance of Behavioural Operations Research
Raimo P. Hämäläinen
We describe Behavioral Operational Research (BOR), a new research
area, defined as the study of behavioral aspects related to the use of
operational research (OR) methods in modeling, problem solving and
decision support. We need controlled comparative studies on the OR
process. Interesting BOR topics include: Model building; Communication with and about models; Behavioral biases and cognitive aspects;
Personal, social and group processes in OR facilitation; People in problem solving situations; Learning; Bounded rationality; Comparative
analysis of procedures and best practices; Teaching.
2 - Have I been doing Behavioural OR for the Last 20
Years?
Stewart Robinson
Recently there has been much interest in Behavioural OR, possibly following the developments in Behavioural Economics and Behavioural
Operations Management. However, the exact nature of what Behavioural OR involves is not well determined. In this paper we shall
explore the concept of Behavioural OR. This shall be done with reference to research, primarily in simulation, that I have undertaken over
the past 20 years that broadly fit with the motivations of Behavioural
OR. What will emerge are two types of Behavioural OR: modelling
people behaviour and the behaviour of people with models.
MA-24
Monday, 8:30-10:00 - Room 212
Preference Learning I
Stream: Preference Learning
Invited session
Chair: Salvatore Greco
1 - Deriving Rankings from Incomplete Preference Information: A Comparison of Different Approaches
Rudolf Vetschera
We compare central parameter methods and volume-based methods
for decision making under incomplete information. Central parameter
methods directly lead to a complete ranking of alternatives. We formulate models to derive ranking from probabilistic preference information (rank distributions and preference probabilities) obtained from
volume-based methods. In a computational study, we compare the resulting rankings and analyze information anomalies, i.e., situations in
which more information leads to worse results. Preliminary results indicate a high level of correspondence between methods.
2 - Testing for the Multivariate Stochastic Order among
Ordered Populations with Application to Ranking and
Selection Problems
Ori Davidov
The comparison and ranking of two or more ordered populations based
on multivariate data is common in a variety of applications. We develop a nonparametric methodology for analyzing such data. In particular we propose a global K sample nonparametric test for order among
vector valued outcomes. The testing procedure can also be used in a
post-hoc fashion to answer questions about the ordering of subgroups
and/or single outcomes within any subset of groups. The tests can be
also used for ranking and selecting the best among K populations.
3 - Handing Inequity Averse Preferences
Alec Morton, Nikolaos Argyris, Ozlem Karsu
We investigate the situation where there is interest in selecting a subset
of "good" distributions across a population, where there is some limited information about the Decision Maker (DM)’s preferences. We
discuss the unanimity relation when DM’s utility function is assumed
to belong to any one of the following sets: additive, concave, quasiconcave or S-concave. We propose solution approaches that incorporate DM’s preference information to obtain a most preferred solution
or a subset of good solutions. The approaches are based on tractable
linear programming formulations.
11
IFORS 2014 - Barcelona
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4 - Inducing Probability Distributions on the Set of Value
Functions
Salvatore Greco, Salvatore Corrente, Milosz Kadzinski,
Roman Slowinski
Recently Stochastic Multicriteria Acceptability Analysis (SMAA) has
been coupled with Robust Ordinal Regression (ROR) with the aim of
measuring the set of compatible value functions for which alternative
a is preferred to alternative b, or for which alternative a is ranked in the
k-th position. Usually, the distribution of compatible value functions
is supposed to be uniform, which is, in general, not true. We propose a
methodology for inducing a distribution of probability on the space of
value functions depending on the preferences of the Decision Maker
(DM).
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Monday, 8:30-10:00 - Room 009
Infinite-Horizon Problems of Mathematical
Economics
Stream: Mathematical Economics
Invited session
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Monday, 8:30-10:00 - Room 010
Fuzzy Goal Programming
Stream: Fuzzy Decision Support Systems, Soft Computing, Neural Network
Invited session
Chair: Mariano Jimenez-Lopez
1 - Model and Algorithms to Generate Group-Rankings
from Interval Fuzzy Preference Relations
María Luisa Martínez, Esther Dopazo, Mauricio Ruiz-Tagle
This paper presents a model and algorithms for the group-ranking
problem based on interval fuzzy preference relations given by various
stakeholders. The problem is formulated as an optimization problem
for constructing a consensus priority weight vector. The proposed approach is made operational by using goal programming techniques.
Moreover, the proposed framework provides performance measures to
evaluate and visualize the effectiveness of the solution and the deviations from the preferences of the individual stakeholders. To illustrate
the methodology a numerical example is presented.
2 - A Fuzzy Goal Programming Approach for the Assignment Problem in Textile Rotary Printing Processes
Manuel Díaz-Madroñero, Josefa Mula, Raul Poler
Chair: Alexander Zaslavski
1 - Infinite-Horizon Variational Problems and Oscillations
Joel Blot
We consider infinite-horizon variational problems in presence of a discount rate where the initial value is fixed, as in macroeconomic optimal growth models, and when the unknown function belongs to special
classes of functions from the nonnegative real numbers set into a finitedimensional normed space, as the class of the bounded functions, the
class of the almost periodic functions. We present results of existence
and results on the solutions of the associated Lagrangian systems.
2 - Infinite-Horizon Differential Games in the DiscreteTime Case
Naila Hayek
We propose a fuzzy goal programming (FGP) approach to solve an assignment problem of production orders in a textile rotary printing company. The model contemplates the trade-off between the setup times
and the waiting time for orders to be processed. We also present an interactive solution methodology to convert this FGP model into an auxiliary crisp single-objective integer model and to find a preferred compromise solution in an interactive fashion. For illustration purposes, an
example based on a real-world industrial problem is presented.
3 - Ordinary Goal Programming with Fuzzy Goals
Mariano Jimenez-Lopez, Amelia Bilbao-Terol, Mar
Arenas-Parra
We study infinite-horizon differential games in the discrete-time case
and use Pontryagin principles on the infinite-horizon optimal control
problems associated to the differential games. We give an application
to a management problem of competition between two internet service
providers, for which a unique Markov-Nash equilibrium is obtained.
A goal programming (GP) variant, in which some goals can be fuzzy, is
proposed. In it, contrary to what happens in ordinary fuzzy GP (FGP)
approaches, the tolerance thresholds of the fuzzy goals (FGs) can be
surpassed. By an alternative formulation of FGs membership functions a new GP model is built. The objective values not exceeding
their threshold are positively valued, accordingly to their membership
degree to the FG, like in a FGP approach, otherwise their deviation regarding the threshold are penalized, like in an ordinary GP approach.
An application to portfolio selection is shown.
3 - Optimal Control Problems with Infinite Horizon and
Budget Constraints
Sabine Pickenhain
4 - Fractional Transportation Problem with Fuzzy Parameters
Shiang-Tai Liu
We consider a class of infinite horizon optimal control problems. This
special class of problems arises in the theory of economic growth and
in processes where the time T is an exponentially distributed random
variable. Budget constraints are also typical for this applications. We
show that in natural way the state and control variable belongs to a
Weighted Sobolev space and Lebesgue space, respectively. In this
spaces the problem can be treated by Hilbert space methods.
4 - Optimal Control
Turnpikes
Alexander Zaslavski
Problems
with
Nonsingleton-
We study stability of the turnpike phenomenon for approximate solutions for a general class of discrete-time optimal control problems with
nonsingleton-turnpikes and with a compact metric space of states. This
class of optimal control problems is identified with a complete metric
space of objective functions. We show that the turnpike phenomenon
is stable under perturbations of an objective function if the corresponding infinite horizon optimal control problem possesses an asymptotic
turnpike property.
This paper investigates the fractional transportation problem (FTP)
where the cost coefficients and right-hand sides are represented by
fuzzy parameters. Based on Zadeh’s extension principle, a pair of
two-level mathematical programs is formulated to calculate the fuzzy
objective value of the FTP with fuzzy parameters. By applying the
dual formulation and variable substitution techniques, the two-level
mathematical programs are transformed into ordinary one-level linear
programs to solve. Solving the pair of linear programs produces the
bounds of the objective value of the fuzzy FTP.
MA-27
Monday, 8:30-10:00 - Room 213
OR in Quality Management I
Stream: OR in Quality Management
Invited session
Chair: Hafize Yılmaz
12
IFORS 2014 - Barcelona
1 - Determination of Premium for Service Contracts
Amitava Mitra
Services span a variety of functions such as the transportation of raw
materials, assemblies, and sub-assemblies of products to manufacturers. We assume customers may purchase damage protection insurance based on product value. The service company makes every effort
to protect the goods and may adopt a system whereby highly-valued
goods are provided adequate protection against damage. In this paper
we create a model to determine the premium to be charged assuming
that it is a function of product value. Further, we assume that a volume
discount is given to the purchasing company.
2 - Important Performance among Perceived Service
Quality, Customer Attitudes, Satisfaction and Revisit
Intention in Traditional Cultural Facility at the IIAC
Changhee Kim, Soo Wook Kim
Today duty-free shops in airports make a lot of profits in the airports
where they are located. As a result, managers of duty-free shops can
experience profit growth, sale increase, and improvement of service
quality. Thanks to this, an airport can experience profit and sales
rise; ultimately, a nation can get enhanced and improved national images and GDP rise. This study found some key factors for Traditional
Cultural Facilities at airport that improve service quality for customer
satisfaction and induce intention of revisit via Important Performance
Analysis (IPA).
3 - Bi-Objective Modelling Approach for New Product
Development using the Belief Rule-Based Methodology: A Case Study from the Pastry and Confectionery Specialties Industry
Emanuel Savan, Jian-Bo Yang, Dong-Ling Xu, Yu-Wang
Chen
In this paper, a bi-objective modelling approach is employed for supporting the decision making in the context of NPD for traditional
sponge cakes. Given the features of the industry, modelling both the
production prices and the quality of the cakes, was considered essential. A BRB methodology was developed to predict the cake quality
based on the different recipes tested; a panel consisting of three cooking chefs was employed to assess the sensory attributes and the overall
quality. An additional panel of experts was involved in selecting the
optimal solution from the generated Pareto front.
4 - A Decision Model For Assessment of the Firms’
Competiviness Level in Terms of Quality
Hafize Yılmaz, Sait Gül, Umut H. Inan
The ferocious competition enforces firms to impose quality management system (QMS). QMS provides many opportunities for improvement of process efficiency and customer satisfaction. With this study,
we aim to build a decision model for ordering the selected packaging firms with respect to the conditions of a QMS and to determine
the competitiveness of firms in the view of QMS understanding. We
utilized Simos’ procedure to determine the importance of the criteria
(conditions of QMS) and VIKOR method to order them in terms of
their scores obtained from the quality consultants.
MA-28
Monday, 8:30-10:00 - Room 130
Challenge ROADEF/EURO 1
Stream: Challenge ROADEF/EURO
Award Competition session
Chair: Christian Artigues
1 - Decision Support for Rolling Stock Management — A
Contribution to the 2014 EURO/ROADEF Challenge
Sebastian Langton, Martin Josef Geiger, Sandra Huber,
Marius Leschik, Christian Lindorf, Ulrich Tüshaus
The 2014 EURO/ROADEF Challenge describes an optimization problem arising in the operative management of trains in a station. It includes the assignment of arriving trains to departures as well as the
MA-29
planning of parking, maintenance and shunting activities. We contribute with a recently developed decision support system using a set
of heuristics, each of which tries to optimize a sub-aspect of the problem. In the talk, besides a short description of the solution approach,
our computational results on the datasets of the EURO/ROADEF 2014
Challenge and the main insights gained will be presented.
2 - A Math-Heuristic Approach for the Roadef Challenge
2014
Jørgen Thorlund Haahr, Simon Bull
Handling all train operations between arrivals and departures at large
terminal train stations can easily become a difficult task. Every train
unit must be assigned a non-conflicting route through the available
shared resources, with consideration given to operational costs. We
propose a solution method for the ROADEF/EURO 2014 Challenge.
We present a heuristic framework which decomposes the problem into
subproblems and solves the subproblems sequentially, using a combination of MIP formulations, column generation, and heuristic methods.
We present results for the provided test instances.
3 - Solving a Train Assignment Problem by Decomposition
Gregoire Spiers
The optimization problem formulated in the 2014 ROADEF Challenge
consists in assigning arrival trains to departures. Since it contains various constraints and many decisions have to be taken for the path of
each train, we propose an approach that decomposes the problem into
smaller ones. These smaller problems are designed in order to reveal
well-known mathematical structures such as the hitting set problem,
the shortest path problem or all different constraints and are then solved
iteratively to converge toward local minima of the problem.
MA-29
Monday, 8:30-10:00 - Room 011
Behavioral Economics and Finance
Stream: Financial Optimization
Invited session
Chair: Xuedong He
1 - Cost-Efficient Contingent Claims under Knightian
Uncertainty: A Distributional Analysis
Mario Ghossoub
In complete frictionless securities markets, no-arbitrage implies a
unique linear positive pricing rule inducing a state-price density. Dybvig (1988) showed that the cheapest way to acquire a certain distribution of a security is when this security is anti-comonotonic with the
state-price density. We examine a related problem in a market where
pricing is via a Choquet integral as in Cerreia-Vioglio et al. (2013),
representing some ambiguity in the market. We show that the cheapest
derivative instrument Y on an underlying X is anti-comonotonic with
X. Finally, we consider a simple example.
2 - Equilibrium Asset Pricing with Rational and Irrational
Investors
Jing Guo, Xuedong He
We study a multi-period equilibrium asset problem with a rational investor and an irrational investor. The rational investor maximizes expected log utility and the irrational investor has additional realization
utility evaluated by cumulative prospect theory. We prove the existence and uniqueness of the equilibrium price. We derive a stock performance measure and show that the irrational investor invests less in
the risky stock than the rational if and only if his loss aversion degree is higher than this measure. We also find that the rational investor
dominates the market in the long run.
3 - Quantile Formulation: A Link between Rank Dependent Utility Theory and Expected Utility Theory
Zuo Quan Xu
13
MA-30
IFORS 2014 - Barcelona
Under monotonicity assumptions, several schemes to solve quantile
optimization problem are proposed in the literature. We propose a
change-of-variable and relaxation method to solve the problem without making any assumptions. We show that solving a portfolio choice
problem under rank-dependent utility theory (RDUT) reduces to solving a Merton’s problem under expected utility theory. With this, the
feasibility, well-posedness, attainability and uniqueness issues for the
portfolio choice problem under RDUT are solved. The method is applicable to general models with law-invariant measures.
4 - A Processing-Consistent Non-Bayesian Inference
Model
Xuedong He, Di Xiao
We consider in the dynamic setting a generic inference model, which
is a generalization of the Bayesian inference model by applying distortion on the prior density and replacing the likelihood with the so-called
quasi-likelihood. We show that this model is processing consistent,
i.e., the posterior density resulting from this model does not depend on
how the samples are grouped and processed, if and only if there is no
distortion on the prior density at any time except for the initial time
and the quasi-likelihood satisfies the so-called product rule.
MA-30
Monday, 8:30-10:00 - Room 012
Advances in Financial Mathematics,
Economics and OR
Stream: Financial Mathematics and OR
Invited session
Chair: Gerhard-Wilhelm Weber
Chair: Thomas Burkhardt
1 - Multiobjective Optimization of Credit Capital Allocation in Financial Insitutions
Kamil Mizgier, Joseph Pasia
Financial firms allocate capital to business divisions in order to withstand the materializing credit losses and to measure performance of
various business lines. We introduce a methodology for optimal credit
capital allocation in financial institutions based on Operations Research approach. In particular, we focus on the efficient allocation
of economic capital to business divisions characterized by credit risk
losses. We compare different allocation methods and provide a rationale behind using OR approach.
2 - Dependence of the Oil Companies’ Financial Results
on Volatility of the World Oil Price
Elena Kuchina
This paper is focused on the econometric analysis of the differences
in responses of the financial results of the world biggest oil companies
to the changing volatility of the world oil price. As control variables,
some other qualitative factors are used, e.g., the headquarters’ or parent company’s location, the volume of oil production, company’s policy and etc. Panel data of 15 oil companies from 11 countries from the
1st quarter of 2006 to the 3rd quarter of 2013 are used for this analysis.
3 - Effectiveness of Different Trading Strategies for
Price-Takers
Lyudmila Egorova
We introduce simulation models of stock exchange to explore which
traders are successful and how their strategies influence to their wealth
and probability of bankruptcy. The results of our experiments show
that there is a critical level of agent’s experience such that agents with
this or higher level almost sure will survive on the market in the long
run. This critical level is just slightly higher and such small value
explains why so many people try to trade on the stock exchange.
4 - Portfolio Optimization Using Forecast and Data Envelopment Analysis
Fernando Salomon, Edson Pamplona, Paulo Rotela Junior
14
This paper aims to analyze the behavior of assets portfolio selected using forecasting techniques associated with Data Envelopment Analysis
and optimized by the Sharpe approach. The research method used was
mathematical modeling and followed the Box-Jenkins methodology to
forecast return, variance, beta, and others indicators using the ARIMA
model. These indicators were used as input and output variables in
Data Envelopment Analysis model to evaluate the efficiency of Sao
Paulo Stock Exchange assets. Finally, we used the Sharpe approach to
optimize the composition of the portfolio.
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Monday, 8:30-10:00 - Room 013
Elicitation
Stream: Decision Processes
Invited session
Chair: Love Ekenberg
1 - Cardinal Ranking as a Means for Efficient Elicitation
Mats Danielson
The elicitation of preference information in MCDA processes and the
lack of practical means supporting it is a significant problem in real-life
applications of MCDA. There is obviously a need of methods that neither require formal decision analysis knowledge, nor is too cognitively
demanding by forcing people to express unrealistic precision or to state
more than they are able to. We suggest a method that tries to balance
between the need of simplicity and the requirement of accuracy. The
method uses ordinal knowledge.
2 - A Verbal-Numerical Scale for the Evaluation of the
ICT Contribution to Development in a Developing
Country Context
Florence Kivunike
Typically the use of ICT to support decision making is highly dependent on stakeholder participation. However the situation changes if the
aim is to adopt decision making techniques to facilitate the evaluation
of the ICT contribution to development (in a developing country context). In essence this requires the adaptation of the elicit action process
to suit the developing country context. It is envisaged that stakeholder
perceptions can be sought through questionnaires or interviews, aggregated and input into the decision support systems for analysis and
evaluation.
3 - Interval Criteria Weights Trough a Slider: The CROC
Way
Aron Larsson
Many elicitation methods are cognitively demanding. This may be
remedied by an inference engine facilitating interactive use supported
by simple visualizations representing imprecise input statements, but
still representing these statements quantitatively and formally enabling
for quantitative decision evaluation conforming to common decision
rules. We show a design for weight elicitation called CROC, using
rank-orders supplemented with imprecise cardinal information accessible through a one-dimensional slider.
4 - Participation, Elicitation and Democracy
Love Ekenberg
Simply enabling more participation will not result in enhanced democracy by itself and an adequate mechanism for participation exercises
is vital regardless of the democracy model. Furthermore, it seems reasonable that various new media are of relevance in this context. There
have been some suggestions lately, but contemporary methods are to a
large extent locked into traditional ways of using computer-based texts
and images that largely hamper the capacity for communicating and
we will discuss how this might be changed.
IFORS 2014 - Barcelona
MA-32
Monday, 8:30-10:00 - Room 014
Decision Analysis and Intelligence
Processing
Stream: Humanitarian Operations Research
Invited session
Chair: Erik Kropat
Chair: Silja Meyer-Nieberg
Chair: Moshe Kress
1 - A Structured War-Gaming Framework to Support
Collective Preparedness for Managing Extreme
Risks
Shuang Liu
Characterized by high impacts and low probability, extreme risks pose
challenges for conventional risk analysis. We describe an innovative
approach to improve the efficiency and effectiveness of management
of such risks and applied it in a case of biosecurity management.
Our framework integrates a war-game model and a structured decision
making approach, and the two are integrative as the role of the model
is to serve as an aid to group learning and decision-making. Through
this interaction, stakeholders developed a better understanding of the
risk and reached consensus in how to manage it.
2 - On Evaluating Conflict and Power of Players within
Coalition Formation Games
Kentaro Kojima
This paper aims to construct mathematical methods to analyze conflict
and power within coalition formation games. It is one of important
topics of game theory that we know how deep conflict of a game is
and how much power each player has. Constructing indices to evaluate these factors will help decision making. A coalition formation
game is modeled by a game in strategic form associated with a hedonic game. The proposed index evaluates interest opposition on players’
preferences and influence of players as a real number. Some numerical
examples of the proposed index are provided in this paper.
3 - Finding the Needles in the Haystack: Efficient Intelligence Processing
Moshe Kress, Ned Dimitrov
The advent of computer, communication and sensing technologies has
resulted in unprecedented capabilities to gather defense intelligence
data from communication networks. As a result, the main intelligence
challenge has shifted from collecting data to efficiently processing it.
We propose a methodology for searching for relevant data on a social
network. The novelty of this methodology is two-fold: (1) a knowledge accumulation model for intelligence processors, and (2) an efficient prioritization algorithm based on graphical models and Bayesian
learning.
4 - Strategic Allocation of Medical Surplus
Wee Meng Yeo
Medical surplus recovery organizations engage in take-back program
for the benefits of underserved hospitals in developing world. The goal
is to bridge the gap between surplus and need. With game theory, we
analyse the interactions among recipients when MSRO operates under
the pull model that provides inventory transparency. Next, we analyse a push model where the MSRO pushes shipment to the recipients.
With the shift of strategic intent from being profit-driven to welfare
provision, we present several reversals associated with choice between
push and pull within the realm humanitarian OM.
MA-33
Monday, 8:30-10:00 - Room 015
Stochastic Inventory Models with
Environmental Constraints
Stream: Environmental Sustainability in Supply Chain
Invited session
Chair: Peter Kischka
MA-34
1 - Newsvendor Model with a Second Order Opportunity
and Consideration of Transport Emissions
Katja Rettke
One reason for integrating environmental issues into operations management are numerous regulations related to pollutant emissions
caused by economic activities. In this study a newsvendor model is
developed in which a company faces stochastic demand when ordering a product from two different supply modes and can still improve
its forecast by observing a market signal during the sales period. In
addition, the company has to comply with an environmental regulation concerning transport emissions. The optimal order quantities are
determined and analyzed with respect to relevant model parameters.
2 - The Single Period Inventory Model Under Dual Sourcing and Product Carbon Footprint Constraint
Emel Arikan, Werner Jammernegg
We present a single period inventory control model under a product
carbon footprint constraint with an emergency supply option. An upper bound for the carbon footprint is specified as benchmark derived
either from the company’s environmental target or from an industry
standard. While the first order requires long lead times, the emergency
order can be supplied in short notice either by an onshore supplier or
by an offshore supplier through a faster transportation mode. By comparing the two scenarios, the tradeoff between economic and environmental performance is discussed.
3 - Inventory Models with Transshipment and Environmental Constraint
Peter Kischka, Werner Jammernegg
We consider a single period inventory model with centralized distribution of a product to two retailers. The impact of transshipment with
respect to the joint demand distribution is analyzed for different dependency structures. The environmental constraint includes emissions
from production, transportation, transshipment and leftovers. At first
glance the distribution system with transshipment leads to higher expected profit but also to higher product carbon footprint because of
additional transportation operations. In this framework we investigate
the potential benefits of transshipment.
4 - Inventory Control with Environmental Criteria and
Stochastic Lead Times
Jörg Ries, Johannes Fichtinger
The consideration of environmental impacts has become an increasingly important concern for companies, where major causes of GHG
emissions are storage and transportation activities. Additionally, the
management of lead times and inherent uncertainties, which are a result of variable transportation times and cause variable emissions, becomes important from an economic as well as an environmental perspective. Thus, we present a multi period inventory control model with
stochastic lead times and discuss the impact of lead time uncertainty
on the environmental performance of the inventory system.
MA-34
Monday, 8:30-10:00 - Room 016
Big Data and Network Methods
Stream: Data Mining in Finance and Commodities
Invited session
Chair: Dejan Stokic
Chair: Marcus Hildmann
1 - Community Structure in Networks and Modularity
Leonidas Pitsoulis, Theodoros Gevezes
Community structure in a graph is an important large scale characteristic and detection of community structure remains up to this date
a computationally challenging problem. The modularity value of a
set of vertex clusters in a graph is a widely used quality measure for
community structure. In this talk we prove that modularity can fail to
detect community structure by showing the existence of a family of
graphs upon which modularity maximization underestimates the number of clusters. We also examine alternative quality functions based on
a random model.
15
MA-35
IFORS 2014 - Barcelona
2 - Nonlinear Profile Monitoring using MARS (Multivariate Adaptive Regression Splines)
JaeYeol Hong, Seung Hwan Park, Daewoong An, Jun-Geol
Baek
The signal generated in the process over the time has a certain type.
Because this signal has a time-varying average and non-uniform variance, the problem occurs when the signal is applied to the Statistical
Process Chart (SPC). In our paper, to solve this problem, the nonlinear
profile monitoring chart is proposed using Multivariate Adaptive Regression Splines (MARS). First, the center line of the control chart is
constructed by using MARS. Second, Box-Jenkins model is used to set
the control limit. Also, comparative experiment is performed between
proposed method and SPC chart
3 - Fast Search in Big Data without Indexing
Alexander Ponomarenko
A standard approach for searching data distributed across the Internet
is to use a search engine which builds an index for it. So two copies
of data appear. It leads the index to become irrelevant over time. In
this talk we propose a novel approach how to organize data for further search without building a traditional index. We suggest that data
should be organized into a data structure which is designed for search
in a higher dimensional metric space. We build an overlay network on
the level of separate information objects such as HTML pages or RDF
triples, based on similarity between them.
4 - User recommendations for discovering consensus
temporal patterns
Cheng-kui Huang
The aggregation of individuals’ preferences into a consensus is a decision support problem. A new type of preference aggregation model
was proposed to provide temporal relationships between items; for example, b can occur during the duration of c, or c can occur before
a. The idea of this model stemmed from the approach of mining sequential patterns to reveal only two point-based relations, i.e., the cooccurrence and order of items. However, in real life, there are lots
of interval-based circumstances, which can describe the temporal relations of items more precisely.
scenarios and their impacts on ecosystem service provision. To overcome described weaknesses we suggest to apply Principal Component
Analysis and Multiple Logistic Regression Models. We will demonstrate potential use of them for identifying explanatory value of different drivers and how to combine them for scenario building.
3 - Economic Evaluation of Self-Monitoring of Blood
Glucose as a Key Component for Type-2 Diabetes
Treatment in Mexico Using Stochastic Simulation
David Munoz, Olivo Omar Zanela, Hermilo Cabra
We report the development and application of a simulation model
that was used to estimate the effects on the level of glycosylated
hemoglobin (HbA1c) and the cumulative costs of four different
regimes of self-monitoring of blood glucose (SMBG) with type-2 diabetes (T2D) in a typical Mexican public health institution (MPHI). The
simulation model was designed to imitate the individual experience of
a patient with T2D at a MPHI; the main drivers for cost computation
were HbA1c evolution and its effect on the incidence and treatment (or
not) of comorbidities, complications and acute events.
4 - Modeling Artificial Neural Networks and Fuzzy Support Vector Machine for Heart Disease Detection
Memmedaga Memmedli, Ozer Ozdemir
Artificial neural networks become effective tool for researchers by determining medical diagnosis correctly in recent years. In many medical diagnosis applications, heart disease detection has become more
important than others nowadays. So, we aimed to use artificial neural
network models such as multilayer perceptron, radial basis function
neural network and generalized regression neural networks for heart
disease detection. We also used a fuzzy support vector machine to
compare with artificial neural network models. Empirical results are
shown at the end of the study.
MA-36
Monday, 8:30-10:00 - Room 132
Fisheries
MA-35
Monday, 8:30-10:00 - Room 131
Stochastic Modeling and Simulation
Stream: Stochastic Modeling and Simulation in Engineering, Management and Science
Invited session
Chair:
Chair:
Chair:
Chair:
Zeev (Vladimir) Volkovich
Erik Kropat
Ayse Özmen
Manuela Maria de Oliveira
1 - The Phycotoxins’ Impact in the Technical Efficiency
of the Portuguese Artisanal Dredge Fleet
Manuela Maria de Oliveira, Ana Camanho, Miguel B. Gaspar
The bivalve dredge fleet, considered as one of the most important artisanal fleets, essentially due to the high value of the catches, is by far
the most extensively studied among the Portuguese artisanal segment.
In the growing presence of marine phycotoxins, this study explores
its impact in the technical efficiency of the fleet which operates in the
Portugal mainland using stochastic frontier analysis models. Considering as exogenous variables, the phycotoxins presence and the mean
wave height, the results allowed to clarify interesting issues about the
performance of the fleets by area.
Stream: OR in Agriculture, Forestry and Fisheries
Invited session
Chair: Stein Ivar Steinshamn
1 - Sustainable Harvest of a Native Species and Control
of an Invasive Species: A Bioeconomic Model of a
Commercial Fishery Invaded by a Space Competitor
Marjolaine Fresard, Carole Ropars-Collet
This paper deals with the control of an invasive species, void of market
value, and acting as a space competitor for a valuable native harvested
species. It presents a theoretical bioeconomic model describing the interacting dynamics of the two species and accounting for the undesirable consequences of native stock harvesters’ behaviour on the spread
of invasion. Dynamic optimisation of the model displays the existence
of a time-path leading to an optimal stationary steady-state solution.
Then, the optimal control model is applied to the bay of Saint-Brieuc
scallop fishery (France).
2 - Big Gain, Little Pain: A Multi-Species Competition
Model of Pelagic Fisheries
Nils-Arne Ekerhovd, Stein Ivar Steinshamn
2 - Driver Sensitive Modeling of Spatio-Temporal Drivers
of Land use Land Cover Change (LULCC)
Gülendam Baysal, Christine Fürst
The main objective is to maximize the net present value from the herring, mackerel and blue whiting fisheries in the North East Atlantic
using an aggregated biomass three-species bioeconomic model. The
value could have been about 50% higher if the stocks had been optimally managed from a multi-species perspective. An initial low harvest of mackerel to build the stock up to almost twice the initial level
accompanied by stabilization of both stock and harvest of the other two
stocks around their initial levels achieves this.
Modeling LULCC based on time series provided by remote sensing
data poses the problem of insufficient differentiation of drivers which
might provoke a severe shortcoming in projection of reliable scenarios.
Main purpose of the study is developing statistically based LULCC
3 - Harvesting in a Fishery with Stochastic Growth and
a Mean-Reverting Price
Sturla Kvamsdal
16
IFORS 2014 - Barcelona
We analyze a continuous, nonlinear bioeconomic model to demonstrate how stochasticity in the growth of fish stocks affects the optimal exploitation policy when prices are stochastic, mean-reverting and
harvest dependent. Price stochasticity induces conservative exploitation with little or no biological uncertainty, but has no strong effect
when the biological uncertainty is larger. We observe that resource exploitation should be conservative when the price reverts slowly to the
mean. We simulate the system to observe long run system behavior
under the optimal solution.
4 - A Continuous-Time Age-Structured Bioeconomic
Model for Optimal Resource Management
Stein Ivar Steinshamn, Peter Golubtsov
An age-structured bioeconomic model, continuous in state and time,
is developed. The model is used for bioecomic analysis and optimization. The objective is to investigate how optimal harvesting patterns
vary under different assumptions. The purpose is to find out how persistent pulse fishing patterns are with this kind of modeling framework.
Emphasis is put on cost and demand parameters. The main results are
that pulse fishing patterns are sensitive both to cost and demand parameters, and pulse fishing tends to disappear when there is a significant
relationship between price and quantity.
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4 - Identification and Evaluation of the Effective Criteria
in Customer Satisfaction, Case Study: Wood Furniture Market
Majid Azizi, Alireza Deghan
Identifying the amount of customer satisfaction and informed of the
field of strength and weakness in this regard, helps wooden furniture
manager programming in line with customers better maintenance and
planning future sales programs with the purposes of admirable competitive advantages. After investigation and interviews with experts in
furniture designing and manufacturing industry 37 criteria and sub criteria collected. The priority rates were determined by AHP. Results
shows price, fame, quality, durability and resistance and paying conditions have the highest priority respectively.
MA-38
Monday, 8:30-10:00 - Room 214
Biomass-Based Supply Chains I
Stream: Biomass-Based Supply Chains
Invited session
MA-37
Monday, 8:30-10:00 - Room 017
AHP
Stream: AHP (Analytic Hierarchy Process) /ANP (Analytical Network Process)
Invited session
Chair: Michele Lundy
1 - A Clustering Approach to Measure Inconsistency in
Pairwise Comparison Judgements
Michele Lundy, Sajid Siraj
Measuring/improving the inconsistency in pairwise comparison judgements is a much debated issue. We propose a method for measuring
inconsistency using a graph-theoretic approach that helps gain insights
into the provided judgements, and also give some suggestions for improving the level of inconsistency in these judgements. Firstly, the set
of all possible preferences is generated, and then cluster analysis is
performed to detect whether the decision maker has two (or more) different sets of preferences in mind. We suggest exploiting this mindset
information for better decision making.
2 - Application of an Analytic Hierarchy Process (AHP)
Model to Assess Academic Corruption and Values in
the Nigerian Educational System
Adebola Adekoya, Olanrewaju Sulaimon Adebiyi, Olateju
Emmanuel Oyatoye, Bilqis Amole
Education contributes to the growth and development of any nation
but allowing corruption in such a sector will be a bane to such expected growth and development contribution. This paper used the AHP
to build a hierarchical model for the eradication of corruption in the
Nigerian educational system using selected universities. Five main elements were used as criteria while three main possible outcomes were
used as the alternatives. 400 questionnaires were filled out correctly
and returned. It was revealed that corrupt elements are present but the
magnitude differs among the universities.
3 - Market Attractiveness Evaluation of Sub-Saharan
Africa by Using SWOT Analysis and AHP Methods
Peter Nganga
The aim of this study is to evaluate the market attractiveness in SubSaharan African countries. Literature review and the Analytical Hierarchy Process Method were applied for the complex multi-criteria
decisions with respect to global macro environment indicators. Statistical data from various sources was adopted for the weights calculation
in sub criteria level. Absolute measurement criteria were weighted independently of the evaluation of the alternatives. The resulting priorities indicated that, in standalone market attractiveness Mauritius have
integrated social cultural and politics with
Chair: Christian Trinks
1 - Requirements of a Mathematical Approach for Optimizing Biomass Value Chains for Material and Energetic Utilization
Ann-Kathrin Mueller, Magnus Fröhling, Frank Schultmann
Biomass is a renewable feedstock which can be used for multiple purposes. Their supply chains face many challenges: low energy density,
high transportation costs, large collection areas and seasonal availability. The objective is to analyze existing models with regard to the
sketched challenges in order to derive further research needs. Many
models only include a regional, technically specific value chain. Few
approaches model the essential storage of biomass. Future works will
develop a generic model which optimizes the location, technology and
capacity of biomass utilization plants.
2 - Design of Lcoal Biomann to Energy Supply Chains
with District Heating Systems under Uncertainty
Şebnem Yılmaz Balaman, Hasan Selim
To design biomass to energy supply chains efficiently, decision makers
should consider economical, environmental and social concerns and
uncertainties related with the decision environment. To handle these
issues, this study presents a multiobjective mixed-integer linear programming model for the planning of biomass to energy supply chains
in an uncertain decision environment. The model deals with the local supply chain design integrated with district heating system. Fuzzy
goal programming is used to incorporate the uncertainties in the problem parameters into the decision making process.
3 - Setting Priorities for the Performance Assessment of
a Biomass-Based Supply Chain
Christian Trinks
This work presents an approach to determine and aggregate the priorities of a relevant group of actors in order to assess the performance of
different woodchips supply chain configurations. Methodologically,
the study is based on a disproportionate stratified random sampling,
standardized stakeholder survey, Analytic Hierarchy Process and the
exact eigenvector method. The analysis will focus on organized smallscale forestry in the administrative districts of Bavaria and on forest
owner associations/forest management cooperatives as key decision
makers in the future woodchips supply network.
MA-39
Monday, 8:30-10:00 - Room 018
ORAHS I - Effectiveness & Performance
Stream: Health Care Applications
Invited session
Chair: Sally Brailsford
Chair: Marion Rauner
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IFORS 2014 - Barcelona
1 - Establishing a Framework for the Effective Evaluation of OR in Healthcare
Martin Pitt, Tom Monks
Evaluations of OR interventions in healthcare are a rare, but essential, component in the effective application of modelling solutions for
health improvement. The complex and dynamic nature of healthcare
requires an evaluation framework which accounts for the many different dimensions by which OR interventions can influence healthcare organisation. Against this background a stratified mixed methods
framework is proposed and a case study presented showing how successful evaluation has been applied to a simulation model used for the
re-design of the emergency stroke pathway at a UK hospital.
2 - Optimising the Operating Room Utilisation Rate and
the Patient Waiting Time in a Spanish Hospital
Francisco Ballestin, M. Angeles Pérez, Sacramento
Quintanilla, M.Pilar Lino, Vicente Valls
We study how to select the patients to operate on in the next two weeks
in a specific operating room in a Spanish hospital. We also decide at
what time to operate on each of these patients. We treat this problem
as a multi-objective problem as we maximize the utilisation rate of the
operating room and minimize the waiting time of patients. Patients
are classified according to the urgency of their operations. Several restrictions should be fulfilled: some operations must be performed by
a specific doctor, others belong to specialties and should be performed
in specific sessions, etc.
3 - Online Allocation and Routing for Blood Delivery in
Conditions of Variable and Insufficient Supply: A
Case Study in Thailand
Pornpimol Chaiwuttisak, Honora Smith, Yue Wu, Chris Potts
We consider the blood delivery problem to hospitals under variable and
insufficient supplies of blood. Hospitals are assigned either to fixed
routes or variable routes according to their location. Blood is supplied
weekly to hospitals in the fixed route, while the frequencies of blood
distribution to hospitals in the variable routes changes with the quantity
of blood available daily. We propose an online system for updating the
schedule over the planning horizon. Different policies for allocation
and routing are compared, with a case study in Thailand.
4 - Impact of Environmental Conditions on Efficiency of
Austrian Red Cross Departments: Data Envelopment
Analysis (DEA) & Second Stage Regression
Marion Rauner, Margit Sommersguter-Reichmann
The efficiency assessment of the 52 Austrian Red Cross departments
of one region is based on a three input (e.g., number of working hours,
number of vehicles) and two output (e.g., index on duration of rides
& number rides) radial and input-oriented variable returns-to-scale
(VRS) Data Envelopment Analysis (DEA) model. We performed a
second stage regression to account for environmental conditions (i.e.,
number of acute care hospital beds, share of citizens aged 64+, number
of ice days, size in km2 of the catchment area).
MA-40
Monday, 8:30-10:00 - Room 019
Scheduling and Lot Sizing Problems
Stream: Production and the Link with Supply Chain
Invited session
Chair: Farouk Yalaoui
Chair: Gonzalo Enrique Mejia Delgadillo
1 - Multiple-Stage Parallel-Machine Capacitated LotSizing and Scheduling with Sequence-Dependent
Setup: A Case Study in the Wheel Industry
Lalida Deeratanasrikul, Shinji Mizuno
We study a real-word problem of simultaneous lot-sizing and scheduling in a capacitated flow shop. This challenging case combines
two complicated characteristics in production which are multiplestage production with heterogeneous parallel machines and sequencedependent setup times. We proposed a MIP formulation with no subtour and tested on real data sets. The model takes several days to solve
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exactly and so MIP-based Relax and Fix heuristics are developed. Test
results show that the formulations are computationally effective and
the model schedule improves on that practiced at the plant.
2 - Optimization Model for Scheduling Steelmaking and
Continuous Casting Production
Eduardo Salazar
A generalized MILP model to scheduling orders in the steelmaking
and continuous casting production is developed. The general structure
of the production system considers an arbitrary number of machines
at each stage, producing orders of several steel grades and types (e.g.,
slabs and billets). Optimization criteria such as makespan and technological constraints such as continuous casting between batches and
in process time of liquid steel are discussed. For illustration purposes,
small sized problems are solved and further research on heuristics solution approaches are discussed.
3 - Lot-Sizing in an Export-Oriented Winery: Models and
Heuristics under the Principle of Postponement
Sergio Maturana, Mauricio Varas, Jorge Vera, Ignacio Vargas
The growth of exports and of private label brands forces exportoriented wineries to allocate their production across a variety of sales
channels with different labeling requirements, which complicates their
production planning. One way to deal with demand uncertainty is by
postponing product differentiation. A critical order decoupling point
for wineries is the labeling process. We present an MIP model for
determining the lot size on multiple production lines with decoupled
bottling and labeling stages. This model is tested on a rolling horizon
framework with error-prone demand forecasts.
MA-41
Monday, 8:30-10:00 - Room 216
Lot-Sizing and Related Topics 1
Stream: Lot-Sizing and Related Topics
Invited session
Chair: Grigory Pishchulov
1 - Production Inventory Model for Perishable Items
whose Deterioration Starts after a Fixed Time
Sarbjit Singh
In the last two decades’ study of deteriorating items has gained importance, but almost all the production models formulated for perishable items have considered that the deterioration of the items starts
immediately as the production starts, which is absurd. In this model
deterioration of inventory starts only after some fixed time. The optimal production schedule has been derived to obtain the minimum total
cost. The optimality of the model has been checked and numerical illustrations with sensitivity analysis are given to prove the validity of
the model.
2 - Continuous-Time Model for the Operational Pulp and
Paper Production Planning
Gonçalo Figueira, Pedro Amorim, Luis Guimarães, Mário
Lopes, Bernardo Almada-Lobo
Motivated by a real-world case study in the pulp and paper industry, we
tackle the operational multi-stage production planning and scheduling
in an integrated mill. We formulate a continuous-time model which
allows easily incorporating several practical constraints. The model is
solved with a fix-and-optimize method that applies different decomposition schemes. A post-optimization is performed to smooth production rates. These models are the core component of a decision support
system. The plans provided by our system are compared to those manually generated by the company’s staff.
IFORS 2014 - Barcelona
MA-44
3 - Supply Chain Contracting under Asymmetric Information and Partial Vertical Integration
Grigory Pishchulov, Knut Richter, Sougand Golesorkhi
1 - Penalizing Fractional Directions in the Integral Simplex Algorithm
Issmail Elhallaoui, Zaghrouti Abdelouahab
We study a bargaining problem in a partially integrated supply chain
where the buyer holds an equity stake in the supplier. Assuming information asymmetry and a principal-agent form of relationship in this
supply chain, we study optimal contracting between the parties within
the framework of the joint economic lot size model. We demonstrate
that the full vertical integration is not necessary to achieve supply chain
coordination in the presence of asymmetric information; a minority
stake may be capable of eliminating the transaction costs owing to information asymmetry and enable coordination.
The Integral Simplex Using Decomposition algorithm (ISUD) is a constructive method able to find optimal solutions to set partitioning problems via a sequence of basic integer solutions with decreasing costs.
ISUD solves iteratively a complementary problem to find an integer
descent direction, i.e., leading to an improving integer one. We introduce for the first time a technique that penalizes fractional directions
and hence helps obtain integer directions, most of the time without
any branching or cutting. Numerical results on bus driver and aircrew
scheduling problems show high potential.
MA-42
Monday, 8:30-10:00 - Room 215
Green Freight Transportation 1
Stream: Green and Humanitarian Logistics
Invited session
Chair: Emrah Demir
1 - A Conic Reformulation and a Local Search Heuristic
for the VRP with Controllable Travel Times
Sinan Gürel, Onur Can Saka, Tom Van Woensel
We examine the vehicle routing problem with controllable travel times,
which is also known as pollution routing problem. We consider multiple vehicle types and deadlines. We control travel times and fuel consumption by setting vehicle speeds. Fuel consumption is a nonlinear
function of speed. We show that the problem can be reformulated as a
mixed integer second order cone program. We propose a local search
heuristic for the problem. We present the results of computational experiments.
2 - The Time-Dependent Two-Echelon Capacitated Vehicle Routing Problem with Environmental Considerations
Mehmet Soysal, Jacqueline Bloemhof, Tolga Bektas
In two-echelon distribution systems, freight is delivered to customers
via intermediate depots rather than directly. This talk will present a
comprehensive MILP formulation for a time-dependent two-echelon
CVRP that accounts for vehicle type, distance, speed, load, multiple time zones, fuel and emissions. A case study in a supermarket
chain shows the applicability of the model to a real-life problem. The
results suggest that the two-echelon distribution system results in an
environmentally-friendly solution, but a single-echelon system provides the least-cost solution.
3 - Modelling and Solution Approach for the Environmental Travelling Salesman Problem
Georgios K.D. Saharidis, George Liberopoulos, George
Kolomvos
We consider the environmental traveling salesman problem in a connected graph driven by a novel cost function describing the impact of
environmental externalities over the routes. The cost function aims to
reflect the increase or decrease of fuel consumption for each route by
taking into account the special features of the route such as weather
conditions, use of air condition, speed, etc.. For the solution of the
TSP, we apply the 7 basic mixed integer linear formulations and compare the results. We apply Benders decomposition techniques and we
eventually test a new separation cut strategy.
MA-43
Monday, 8:30-10:00 - Room 217
Algorithms and Applications - 1
Stream: Algorithms and Computational Optimization
Invited session
Chair: Basak Akteke-Ozturk
Chair: Ulf Lorenz
2 - Improving ILP Solutions by Zooming around an Improving Direction
Zaghrouti Abdelouahab, Issmail Elhallaoui, Francois Soumis
The Integral Simplex Using Decomposition (ISUD) is an efficient primal algorithm that finds a decreasing sequence of integer solutions
leading to an optimal solution for the set partitioning problem. In
this paper, we introduce an approach that improves different aspects
of ISUD. The new approach improves a local solution by zooming
around an improving fractional direction. This zooming approach is
globally primal and exact and is locally dual on a reduced problem. It
works well on problems emanating from transportation industry.
3 - A Decision Support System for Optimization in the
Face of Uncertainty
Susara van den Heever, Ban Kawas, Marco Laumanns,
Chungmok Lee, Radu Marinescu, Martin Mevissen, Nicole
Taheri, Rudi Verago, Ali Koc
Optimization under uncertainty involves many challenges, such as
large numbers of scenarios, complex mathematical models and lack of
business user adoption. We describe a decision support system aimed
at addressing these challenges. This system includes a methodology
for soliciting information from practitioners, automated model conversion and visual analytics for trade-off analysis. We present the architecture of a prototype implemented as a plug-in to the IBM Decision
Optimization Center and demonstrate its use through an example involving unit commitment for power generation.
4 - MIP Generation for System Synthesis Tasks
Ulf Lorenz, Lena Altherr, Thorsten Ederer, Peter Pelz, Philipp
Pöttgen, Benjamin Saul, Wolf Zimmermann
Our research deals with synthesis tasks for fluid systems. A typical
job is to decide a system topology considering investment costs, operational costs and system control which again depends on various load
profiles. We present a stationary optimization model for a booster station. In principle, such a fluid system consists of a flow problem with
some non-linear constraints that are linearized. We also aim at an automatic conversion from Engineer’s language into this MIP. We present
the basics of such a domain specific language which enables us to utilize classic compiler techniques.
MA-44
Monday, 8:30-10:00 - Room 218
Simulation in Management Accounting
and Management Control I
Stream: Simulation in Management Accounting and
Management Control
Invited session
Chair: Friederike Wall
1 - A new Portfolio Risk Evaluation Model Including
Huge Loss Events Derived from Market Prices:
Continuous-Time Model
Yukio Muromachi
Recently we proposed a new risk evaluation model of a portfolio considering potential huge losses implied from market prices. Its numerical examples were consistent with typical features in the CDO market
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IFORS 2014 - Barcelona
during the financial crisis. However, it was a one-period model. Although many kinds of economic state were considered, its transition
was omitted. In this article, we propose a continuous-time version of
the model. The transition of the economic state is considered as a
stochastic "multiplier" process, and a simple but effective model of the
process and its simulation procedure are proposed.
2 - An Agent-Based Simulation of new Product Adoption
for Multiple Technology Generations
Markus Günther, Christian Stummer
Using the contextual setting of optimizing grid-level energy storage,
we study the effect of dimensionality (the number of storage devices)
on the performance of different approximation strategies, including
regularized stochastic decomposition and piecewise linear, separable approximations. We build on the algorithmic framework of approximate dynamic programming to introduce novel machine learning
strategies which overcome the curse of dimensionality inherent in scenario trees.
3 - Mitigating Uncertainty via Compromise Decisions
Suvrajeet Sen, Yifan Liu
When introducing new products that rely on multiple successive technology generations and, thus, have novel features, firms seek for insights in the adoption behavior of their potential consumers. Their
individual decision to adopt, postpone, or leapfrog the new product
generation is typically complicated by an uncertainty concerning the
performance and usefulness of the new features. Therefore, wordof-mouth communication within the customers’ social networks and
normative influences may play a distinctive role. We present an agentbased simulation that allows for investigating such effects.
We introduce a new concept which we refer to as the compromise decision which is applicable to sampling-and-replication-based convex
optimization algorithms. For such replicated optimization, we show
that the difference between an average solution, and a compromise decision provides a natural stopping rule. We demonstrate the practicality of this approach by reporting computations which cover a range of
applications, including a detailed study of SSN, a network planning instance which is known to be more challenging than other test instances
in the literature.
3 - A Simulation-Based Approach for the Analysis of Allocation Methods for Cost-Center Accounting
Sina Hocke, Matthias Meyer
4 - Parallelization and High Performance Computing Adjustment of the Cluster Benders Decomposition Algorithm
Francesc Solsona, Jordi Mateo, LluisM Pla, Josep Lluis
Lerida
Different allocation methods in cost accounting create a certain tolerance for the distribution of costs but the scope of their inaccuracies is
not quantified so far. In this paper, three allocation methods of German cost-center accounting are investigated with regard to accuracy
by using a simulation. The results suggest that for a small proportion
of mutual service exchange, the supposedly less precise method is to
be preferred. For practitioners, a medium degree of mutual service exchange would be enough to abdicate the more complex and apparently
not always more precise step-ladder method.
4 - Frequency and Mode of Changing the Management
Control System: Results of an Agent-Based Simulation
Friederike Wall
In this paper we investigate, whether, or not, frequent changes in the
management control system could induce improvements in organizational performance. We apply an agent-based simulation model based
on the framework of NK-fitness landscapes to compare the search processes of organizations with different types of change processes against
each other. The results indicate that changes in the management control system per se might increase organizational performance. Moreover, results suggest that value-driven changes may be more efficient
than purely time-triggered changes.
MA-45
Monday, 8:30-10:00 - Room 219
Computational Stochastic Programming
Stream: Stochastic Programming
Invited session
Chair: Suvrajeet Sen
1 - Sell or Hold: A Simple Two-Stage Stochastic Combinatorial Optimization Problem
George Nemhauser, Shabbir Ahmed, Qie He
The sell or hold problem (SHP) is to sell k out of n indivisible assets over two stages, with known first stage prices and random secondstage prices, to maximize the total expected revenue. We show that
SHP is NP-hard when the second-stage prices are realized as a finite
set of scenarios. We show that SHP is polynomially solvable when
the number of scenarios in the second stage is constant. A max1/2,
k/n-approximation algorithm is presented for the scenario-based SHP.
2 - Approximation Strategies for Multistage Stochastic
Programs
Tsvetan Asamov, Warren Powell
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This work proposes the parallelization of the Cluster Benders Decomposition proposed by Laureano et al., a newer and faster version of the
L-shaped algorithm. The parallel version has been implemented in a
multicore and in a cluster system, as the base frameworks of shared and
distributed HPC systems, respectively. Extensive performance evaluation and comparison of the computational costs between the serial and
parallel models in their execution in the HPC systems has been performed. The final goal is to apply this technique to solving real cases
with a minimal computational time.
IFORS 2014 - Barcelona
Monday, 10:30-12:00
1 - On the Distance-Constrained Generalized Directed
Rural Postman Problem
Isaac Plana, Thais Ávila, Angel Corberan, Jose Maria Sanchis
MB-01
The Generalized Directed Rural Postman Problem (GDRPP) has interesting real-life applications, such as routing for meter reading. In the
GDRPP, there is a family of arc subsets and the goal is to find a minimal
cost tour traversing an arc in each subset. The Distance-Constrained
GDRPP is a generalization in which a fleet of vehicles is available and
the goal is to minimize the sum of the costs of all the routes, provided
that no route exceeds a maximum distance. Here we introduce several
formulations, present different families of valid inequalities, and report
some computational results.
Monday, 10:30-12:00 - Room 118
Train Timetabling and Dispatching
Stream: Railway and Metro Transportation
Invited session
Chair: Thomas Schlechte
2 - Hybrid Arc Routing Models
Leonor S.Pinto, Luís Gouveia, Cândida Mourão
1 - Energy Efficient Freight Train Scheduling
Frederik Fiand, Uwe T. Zimmermann
Based on a real world problem we optimize energy efficiency in railway transportation. Our project partner, DB Germany, provides a set
of shipment requests and predefined train schedules that can be slightly
varied during the solution process. Energy efficiency is optimized by
assigning shipments to trains considering power consumption. The
tremendous problem size can be reduced via tailor-made preprocessing. This approach enables us to generate models that can be handled
with the help of large-scale Mixed-Integer Programming techniques.
(BMBF-supported joint project "e-motion")
2 - On Comparing Robustness
Timetabling
André Chassein, Marc Goerigk
Approaches
for
We consider the acyclic train timetabling problem that aims at minimizing weighted activity durations. As train schedules are highly susceptible to delays, various robustness approaches have been proposed.
Still, as each approach uses its own definition of robustness, it is an
open problem how to compare the quality of such solutions under uncertainty, and how to guide the practitioner deciding which robustness
approach to use. To this end, we propose a scenario-based performance
comparison for robust solutions and show the benefits and drawbacks
of robust formulations from the literature.
3 - Automatically and Quickly Planning Platform and
Route of Trains in Railway Stations
Peter Sels, Thijs Dewilde, Dirk Cattrysse, Pieter
Vansteenwegen
When creating a railway timetable, a sub-problem that occurs for every
station is the Train Platforming Problem (TPP). With our tool called
Leopard, we show that we are able to automatically and quickly solve
the TPP and create the platform and route plan for each of the 553 stations in Belgium, for all trains. Leopard also evaluates the plan created
by human planners, if it already exists. For both the human and the
Leopard created plan, we produce graphical images that are easily interpreted and compared by humans. As such Leopard both evaluates
and improves train platforming plans.
4 - A Real-Life Implementation of an Exact Train Dispatching Algorithm
Carlo Mannino
Train dispatching consists in managing railway traffic in real-time. In
recent works, we showed how, under "mild" assumptions on the instances, the real-time train dispatching problem can be solved to optimality, for relevant real life cases, by applying Benders’-like decompositions. As of February 2014, a system based on our exact decomposition approach has been put in operation on the Stavanger - Sira
line in western Norway. Implementing such system has required tackling cases where the above mild assumptions do not apply. We present
exact and heuristic techniques to handle this.
MB-02
Monday, 10:30-12:00 - Room 111
Models and Algorithms for Arc Routing
Problems
Stream: Vehicle Routing
Invited session
Chair: Marcos José Negreiros
MB-03
Arc routing studies have been recently increasing motivated by real
world applications. Our work derives from a waste collection routing
problem, and mixes the resolution of hybrid compact models (HCM)
with some heuristics. The HCM arise from a combination of two capacitated arc routing models: a valid one, that is able to solve medium
size instances, and a relaxation providing good lower bounds. In a
heuristic way some preliminary services are assigned to the vehicles,
in an attempt to reduce the instances dimensions. Computational results with data instances for a case-study are analysed.
3 - Studing Arc Routing Models
Cândida Mourão, Luís Gouveia, Leonor S.Pinto
New flow based compact models are proposed and studied for the
mixed capacitated arc routing problem (MCARP). These models, use
two sets of flow based variables, in contrast to a single set known from
previous works. The two sets permits us to obtain stronger linking
constraints. Some new side constraints, motivated by real world case
studies, are also handled. Computational results with some benchmark
instances are provided and discussed.
4 - New Heuristics for the Mixed General Routing Problem
Marcos José Negreiros
This work does a detailed description of new polynomial heuristic procedures based on the General Travelling Salesman Problem (GTSP)
and Generic Minimum Spanning Tree Problem (GMST) for the Mixed
General Routing Problem (MGRP). The procedures transform the
MGRP to a pure Directed Rural Postman Problem (DRPP) in polynomial time to obtain high quality solutions in reasonable time. The
instances used from the literature are evaluated. We show here we have
obtained some results that are better than the previously heuristics reported for the MRPP.
MB-03
Monday, 10:30-12:00 - Room 001
Air Traffic Management
Stream: Aviation
Invited session
Chair: Antony Evans
1 - Decision Support for Improving the SESAR Key Performance Areas
Krystsina Bakhrankova, Patrick Schittekat, Amela
Karahasanovic, Aslak Eide, Hans Erik Swendgaard, Volker
Grantz, Stian Støer Ødegård, Dag Kjenstad, Carlo Mannino
Productivity enhancement in the control room is needed to accommodate the expected growth in air traffic and meet demands for increased
safety, predictability and efficiency of Air Traffic Management (ATM)
systems. Following a four-step improvement process, an optimizationbased decision support tool is developed. The system is evaluated
based on the outcomes of a controlled experiment. The results indicate that active operational use of the tool provides direct economic
savings, greater flexibility, efficiency, overview and safety, while improving the SESAR Key Performance Areas.
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IFORS 2014 - Barcelona
2 - A Decision Theoretic Approach for Trajectory Planning with Risk Mitigation
Husni Idris
Constraint violation risk is a key factor in air traffic planning. Decision theory was used to measure the risk mitigation ability of a traffic
control strategy, by forming a discrete time-space reachable tree that
does not violate constraints such as safe separation requirements. The
ability to mitigate risk, measured by the expected number of feasible
trajectories available at each state, was maximized by a dynamic program to plan trajectories. Presented simulations showed that maximizing risk mitigation induced organized traffic and how strategies trade
between capacity and risk mitigation.
3 - Airline-Driven Performance-Based Air Traffic Management: Game Theoretic Models and Multi-Criteria
Evaluation
Antony Evans, Vikrant Vaze, Cynthia Barnhart
An important objective of future air traffic management (ATM) systems is to support airline business objectives. We propose several approaches for collecting inputs from airlines and for combining them
into ATM initiatives. We apply a game-theoretic approach to examine the potential for gaming, both theoretically and by simulating a
generic initiative and ground delay programs at Newark and LaGuardia
airports. We conclude that voting represents the most promising approach, allowing ATM initiatives to be designed that optimize system
performance while respecting the objectives of airlines.
4 - GRASP for Planning Multi-City Air Routes
Mariá C. V. Nascimento, Kátia Yoshime Nakamura
Nowadays, air transportation has been adopted by millions of people
over the world. A prior route planning by the customers makes necessary for better economical choices for purchasing air tickets. We
present a study of a mathematical formulation to provide a minimum
cost route with regard to the air tickets. To solve the problem a metaheuristic is proposed. Concerning the computational experiments, the
metaheuristic provided satisfactory results regarging the real test cases.
3 - Modeling Humanitarian Logistics in the Philippines
Brian Canlas Gozun, Arlyn Villanueva
The onslaught of the destructive and powerful Super Typhoon Haiyan
that devastated the central parts of the Philippines in November 2013
has shown the importance of an efficient and effective logistics system. The Philippines has its shares of natural disasters ranging from
typhoons to volcanic eruptions and earthquakes. The need for humanitarian logistics to address pre-and-post disaster logistics concerns to
serve the needs of the survivors is crucial. This study models the requirements for humanitarian logistics as well as the issues that arise
from its implementation.
4 - A New Integrated Forward and Reverse Logistics
Model: A Case Study
Mirko Vujosevic, Jasenka Djikanovic
A new integrated forward and reverse logistics model is presented. The
following three objectives are considered: (1) minimization of the total
cost in forward and reverse flows, (2) minimization of traveled distance
in forward and reverse flows, and (3) minimization of inventories in
plants in order to achieve just-in-time delivery. The optimization problems are solved using CPLEX and GUROBI solvers. A case study
based for a company which produces electrical household devices is
presented. The analysis is focused on the impact of changing recovery
rate of reversed products.
MB-05
Monday, 10:30-12:00 - Room 002
Oil and Gas Transportation
Stream: Petroleum Logistics
Invited session
Chair: Yury Shcherbanin
MB-04
Monday, 10:30-12:00 - Room 119
Supply Chain Planning 2
Stream: Supply Chain Management
Invited session
Chair: Mirko Vujosevic
1 - A Quasi-fixed Cyclic Production Scheme for a MultiItem Production System with Stochastic Demand
Philipp Zeise, Dirk Briskorn
We present a nested approach to generate a production scheme that
consists of a fixed periodic production sequence (cycle) whereby each
product may occur more than once in the sequence. Given a lot-sizing
strategy we decide when to use a facility for production, setup or idling
while the time between two successive completions of the cycle is
quasi-fixed, i.e., a target cycle length with boundaries. Complicating
factors are the sequence-dependent setup times, the limited stock space
and the stochastic demand. The results, using practical data, are compared to approaches from literature.
1 - Medium Term Forecasts of World Oil and Gas Consumption
Liudmila Studenikina
We assess the trends in global oil and gas demand and supply, and analyze changes in world energy consumption by sector and by fuel up to
2035. We compare the outlooks performed by an international energy
organization and a public oil company, and identify the differences in
forecasting. Both outlooks are based on large-scale simulation models designed to generate sector-by-sector and region-by-region prognoses. The results of the analysis demonstrate various research approaches to estimating future hydrocarbon consumption in the world
in the medium-term period.
2 - Changing Logistic Approaches in International Oil
Trade Movements
Anastasia Mikhaylova
We analyze the effect on the existing global oil trading patterns of the
changes in energy policy and the market structure of the leading oil
and gas consumers, mainly the USA which are becoming an oil and
gas exporter in the medium-term period. It calls for a need for new
logistic approaches in international oil trade movements. The assessment is based on the forecasts of the International Energy Agency and
the US Energy Information Administration, generated by simulation
tools. We study the implications of the changes in trading patterns on
the global oil supply chain architecture.
2 - Supply Chain Management using an OptimizationSimulation approach for the Pharmaceutical Distribution
Sara Martins, Pedro Amorim, Gonçalo Figueira, Luis
Guimarães, Bernardo Almada-Lobo
3 - Analysis of Logistics Capabilities for Gas Transportation in the Arctic
Yauheni Kisialiou, Yury Shcherbanin, Irina Gribkovskaia
Medlog is one of the leading distributors of pharmaceutical products
operating in Portugal. It commercializes approximately 17.000 products from over 300 different suppliers to more than 1500 pharmacies
using 5 warehouses. Nowadays Medlog has an improved supply chain
management as it was able to reduce their operating costs, while still
keeping similar customer fill rates thanks to an optimization-simulation
driven approach. In this talk we present the developed framework responsible for shaping and tuning the new supply chain management,
as well as the change management challenges faced.
Exploration of hydrocarbons reserves in the Arctic requires development of logistics capacities and transport infrastructure. Effect of the
global warming and year-around navigation on the Northern Sea Route
facilitate downstream transportation of gas extracted in the Arctic via
the route to Asia-Pacific markets. Using simulation model we study
the implications of the ice breaking fleet availability, climate conditions and regulations for navigation on the route throughput. Simulation is performed for several scenarios of LNG transportation between
different ports by different LNG carriers.
22
IFORS 2014 - Barcelona
4 - Oil Pipelines Transportation: Evaluation of Logistics
Expenses
Yury Shcherbanin
While crud oil is transported using pipelines logistics expenses are
evaluated not only taking into account tariffs and different other taxes.
Compounding of different types of crude oil, loses in the system etc.
influence on the final costs. The task is to try to evaluate the level of
such kind of expenses using methods of comparative analyses and statistical analyses. Previous dates illustrate quite high influence of paraffin crude oil over the maintaining of well known types and some new
logistics technologies could be used to maintain properties needed.
MB-06
Monday, 10:30-12:00 - Room 211
Strategic Freight Demand Models
Stream: City Logistics and Freight Demand Modeling
Invited session
Chair: Lorant Tavasszy
Chair: Jafar Rezaei
1 - Analytical Urban Freight Tour Models
Jose Holguin-Veras
The presentation will discuss recent developments in freight demand
modeling that, on the basis of formal mathematical models, are able to
capture urban freight tours. The models to be discussed are based on
spatial price equilibrium and maximum entropy. The paper discusses
them and outlines future research needs.
2 - Developing a Multi-Scale Multi-Region Input-Output
Model
Matthew Roorda, Chris Bachmann, Chris Kennedy
Global multi-region input-output (GMRIO) models do not capture the
heterogeneity of regions within a single country. Multi-scale models capture the global economy while preserving regional differences.
This research develops methods for integrating multi-region inputoutput (MRIO) datasets from multiple spatial scales to develop multiscale multi-region input-output (MSMRIO) models. A Canadiancentric GMRIO model was developed that includes 47 countries and
Canada’s 13 subnational regions. Results show that it is possible to
link scales with a reasonable degree of accuracy.
3 - Elasticity Estimations for Continental Intermodal
Freight Transport
Bart Jourquin, Lorant Tavasszy
Elasticities for continental intermodal container transport are expected
to be different from values found in the literature for traditional freight
transport, as trucking can be used as a substitute or a complement to
rail or inland waterway transport. Elasticities estimated by a simple
theoretical synthetic model and values estimated with a complete European multimodal network model are presented. It appears that the
demand for intermodal rail-road transport is inelastic and that elasticities decrease with the pre- and post-haulage distance but increase with
the total length of the trips.
4 - Transport Mode Selection During Cargo Movement
Operations in the South East Europe Area
Panagiotis Otapasidis, Christina Arampantzi, Vasileios
Zeimpekis, Ioannis Minis
We assess different freight transportation options for cargo movement
within the SEE area. An extension of Dijkstra’s algorithm is used to
identify the most suitable transportation mode based on cost, trip duration, and CO2 emissions. We apply the proposed algorithm between
the Port of Piraeus and four capital cities of the SEE (Sofia, Bucharest,
Budapest, and Ljubljana). The results show that the use of road transport is the most convenient solution if trip duration is the main criterion, whereas combined transport is selected when minimization of
cost and CO2 emissions is the objective.
MB-08
MB-07
Monday, 10:30-12:00 - Room 003
Complementarity Models in Natural Gas
and Renewable Markets
Stream: Equilibrium Problems in Energy
Invited session
Chair: Sauleh Siddiqui
1 - Risk Aversion in Imperfect Natural Gas Markets
Ruud Egging, Alois Pichler, Øyvind Iversen Kalvø, Thomas
Walle-Hansen
We consider risk aversion by natural gas supply companies considering investments in conventional and shale gas resources in a mixed
complementarity problem. Uncertainties considered include political
risk and resource sizes. We discuss investment decision results and
expected welfare loss due to risk aversion.
2 - LNG Market Modeling
Steven Gabriel, Seksun Moradee
In this talk, we report on the recent World Gas Model (WGM 2014)
which includes more details on the liquefied natural gas (LNG) market.
We consider a variety of scenarios involving LNG and canal expansion
and the overall effects of U.S. natural gas LNG exports combined with
other pipeline and LNG expansion activities globally. WGM2014 is a
large-scale Nash-Cournot MCP model that has been used in a variety
of settings by U.S. and European governments.
3 - A Complementarity Approach to Analyse the Influence of Renewables on Market Power
Susanne Koschker, Dominik Möst
The paper will investigate with an Electricity Market Model the possibility for the abuse of market power by taking the Lerner-Index as indicator. Especially, the role of renewables and the overcapacity situation
will be investigated. Marginal costs of the market model in a competitive environment are taken as reference for electricity prices. This
situation will be compared within a Stackelberg game where the influence on capacity withdrawing and market prices will be analysed. The
mathematical model of both cases (competition, Stackelberg game) as
well as results will be presented.
4 - An Equilibrium Model for the US RIN Market
Sauleh Siddiqui, Adam Christensen
Renewable Identification Numbers (RINs) are used to track the use
of biofuels in the US transportation infrastructure and are the primary
currency to demonstrate compliance with the mandated biofuel volume
requirements. The RIN market and its respective players will be modeled using an equilibrium problem, which will be used to quantify the
effects of parallel incentives in the form of tax credits and other policy
initiatives.
MB-08
Monday, 10:30-12:00 - Room 120
Electricity Markets and Smart Grids
Stream: Energy Economics, Environmental Management and Multicriteria Decision Making
Invited session
Chair: Jinwoo Park
1 - Electricity Futures
Silvana Stefani, Paolo Falbo, Daniele Felletti
In the literature, the elusive behavior of the risk premia in electricity forwards is documented. In fact, electricity futures and forwards
may help generators, consumers and marketers to manage volatility,
but also introduce risks of their own. We evaluate the ex post performance of monthly base load futures contracts on the Italian market in
2008-2013. The results show that alternative models, different than the
"traditional’ ones, are needed for pricing futures in electricity markets.
23
MB-09
IFORS 2014 - Barcelona
2 - European Day Ahead Electricity Market Structures
Kürşad Derinkuyu
Power exchanges in Europe organize two sided combinatorial auctions
every day to determine the electricity prices within an hour for the
delivery of electricity next day. Day-ahead market prices are usually
accepted as reference prices and affect other electricity markets such
as intra-day and futures. This study first gives a brief summary of the
electricity market structures. Then, we provide the alternative formulation and solution approaches to the day ahead market optimization
problem, and the difficulties appear in practice. Lastly, we discuss the
future trends and open research problems
3 - Market Design for Rapid Demand Response - The
Case of Kenya
Kurt Nielsen
We suggest a market design for rapid demand response on electricity markets. The collective solution consists of remotely controlled
switches, meters, forecasting as well as an auction design to set prices
and select end-users job by job. The auction motivates truth-telling and
makes it simple to involve the end-users in advance and to activate demand response immediately. The solution is analyzed and simulations
are conducted for the case of Kenya. In Kenya we focus on turning the
many private backup generators into a part of the on-grid solution by
the rapid demand response solution.
4 - Optimal Operation Management for Electric Vehicle
Battery Switch Stations in Smart Grid Environment
Jinwoo Park
This study considers the application environment of a battery switch
station (BSS) for electric vehicles (EVs) as a micro-grid consisting
of distributed generation facilities (DGFs) including EV batteries and
renewable energy resources. An optimal model for environmentally
sound and efficient power generation/use should take into account of
the daily and seasonal variations caused by nature as well as by humans. In addition to the operational models, station-to-grid (S2G) concept is proposed to maximize the efficiency of the stations.
MB-09
Monday, 10:30-12:00 - Room 121
Dynamical Systems and Mathematical
Modelling 2
Stream: Dynamical Systems and Mathematical Modelling in OR
Invited session
Chair: Yutaka Kimura
1 - Looking for Optimal Strategies in Agribusiness via
Nonlinear Optimal Control
Jitka Janova, Gabriela Ruzickova, David Hampel
The optimal control theory is a promising tool to identify the long run
strategies in natural resources economics, but where the optimal control policies have been determined, these often fail. We suppose this
is mainly due to the shortcomings of the models stemming from neglecting non-linearities of real systems and miss identification of constraints. In this contribution we formulate key long run decision problems of agribusiness in the Czech Republic in the form of nonlinear
optimal control problems, present the solution and thoroughly discuss
the validity of the results.
2 - A Study of the Enumeration of the Electoral Districts
Keisuke Hotta
In Japan, there is much criticism for the point that the gap in the value
of individual votes is too big. The electoral system is overdue for
change. We have been tackling this research, and have been providing the optimal district plan and the k-th optimal solutions to support
the decision-making. However, enumerating them faster is expected.
So, in this study, I propose the method to enumerate them faster.
24
3 - The Second Dual of a Primal
Takayuki Ueno, Yutaka Kimura, Seiichi Iwamoto
Recently, we’ve found out that there are many interesting relations between a certain primal problem and dual problem. It is the trinity between the optimal solutions (optimal point and optimal value) of both
problems. That is, it is Fibonacci complementary duality and is Golden
complementary duality. This duality is called dynamic dual. In this
talk, we introduce a second dual problem by considering another dual
problem for a primal problem and derive a relation between the optimal
solutions of a primal and a second dual. This second dual is Fenchel
dual.
MB-10
Monday, 10:30-12:00 - Room 122
Integration of Distributed Energy
Resources in Electricity Systems
Stream: Optimization Models and Algorithms in Energy
Industry
Invited session
Chair: Tomas Gomez San Roman
1 - Transmission and Wind Investment in a Deregulated
Electricity Industry
Afzal Siddiqui, Lajos Maurovich-Horvat, Trine Krogh
Boomsma
Adoption of dispersed renewables like wind typically requires expansion of the transmission network. While the two decisions could be
reconciled within the auspices of a central planner, restructuring of
electricity industries has introduced a merchant investor (MI), who
earns congestion rents from construction of new lines, in addition to
the transmission system operator (TSO). We compare the two market
designs via a bi-level model that has the MI or TSO making transmission investment decisions (upper level) and producers making generation investment and operational decisions (lower level).
2 - Aggregated Scheduling of Plug-in Electric Vehicles
Under Direct and Indirect Load Control Approaches
Ilan Momber, Tomas Gomez San Roman
Unbundling in power systems regulation stipulates aggregators to coordinate the scheduling of plug-in electric vehicles. This may involve
centralized, i.e., direct load control and decentralized, i.e., indirect load
control decision making. We compare the two via a bi-level programming approach that has the aggregator procuring electricity from dayahead and balancing markets (upper level) and PEVs reacting to different combinations of retail and network use-of-system charges (lower
level).
3 - Multi-temporal OPF for Maximizing the Integration
of Energy from Renewable Sources in Distribution
Grids
Andre Madureira, Jose Meirinhos, Joao Pecas Lopes
A multi-temporal OPF was developed for managing distribution network operation, including control of voltage magnitudes and active/reactive power injections. Taking as inputs load and generation
forecasts, the multi-temporal OPF will exploit a metaheuristic to produce a set of control actions to coordinate available distributed energy
resources for the day-ahead. The main objective is to maximize the integration of energy from variable renewable sources subject to a set of
technical/operational constraints. Results from the application of the
approach in a distribution grid will be presented.
4 - Tools, Procedures and Principles of Coordination between DSOs & TSOs
Miguel Cruz-Zambrano, Cristina Corchero
European Energy Policy aims to promote the integration of large
amounts of RES on the electricity sector. Controllable DER will be
able to offer network operators a set of instruments for ensuring a secure and reliable grid operation as well as for reducing or deferring
network investment. The aim of this work is to propose a set of preliminary procedures of coordination between DSOs and TSOs, considering both current grid codes and national technical regulations. The
development of distribution network management tools for increasing
the RES hosting capacity will be addressed.
IFORS 2014 - Barcelona
MB-11
Monday, 10:30-12:00 - Room 113
Advances in Specialized Zero-One
Optimization
Stream: Combinatorial Optimization
Invited session
Chair: Fred Glover
Chair: Manuel Laguna
Chair: Gary Kochenberger
1 - GRASP-based Tabu Search for the Vertex p-Center
Problem
Zhipeng Lu, Qingjie Zhao, Taoqing Zhou
The p-center problem consists of choosing p facilities from n vertices
of an undirected graph in order to minimize the maximum distance between a client and its closet facility. We present a GRASP-based Tabu
Search (denoted as GRASP/TS) algorithm for the p-center problem,
which employs a Tabu Search based local search and an adaptive perturbation operator to reconstruct the solution when the search falls into
local optimum. Experiments show that GRASP/TS is competitive with
the best performing algorithms in the literature and is able to improve
some previous best upper bounds.
2 - Convergent Scatter Search and Star Paths with Directional Rounding for 0-1 Mixed Integer Programs
Saïd Hanafi, Raca Todosijevic, Fred Glover
Scatter Search is an evolutionary metaheuristic introduced by Glover
(1977) for 0-1 Mixed-Integer Programs (MIP). Based on the Star Paths
and directional rounding strategies proposed in Glover (1995), we establish several useful properties of directional rounding and show that
it provides an extension of rounding and complementing operators. We
provide a convergent scatter search algorithm for 0-1 MIP with a proof
of finite convergence, accompanied by two implementation variants
and illustrative examples. Finally, we present different heuristics based
on our extensions of Scatter Search.
3 - The Boolean Quadratic Programming Problem with
GUB Constraints
Yang Wang, Abraham Punnen
We consider the boolean quadratic programming problem with generalized upper bound constraints (BQP-GUB) which subsumes the wellknown quadratic semi-assignment problem. BQP-GUB has various
applications in engineering and biology. We present various complexity results on the problem along with several metaheuristic algorithms.
Results of extensive experimental analysis are presented demonstrating
the efficacy of these heuristic algorithms.
4 - Effective Long-Term Memory Strategies for Local
Search-Based Optimization
Oleg Shylo, Vladimir Shylo
In this presentation, we explore effective and scalable strategies for
accumulation and utilization of the feasible solution properties that
can improve performance of optimization algorithms based on local
search. In particular, we investigate an extension of the tabu search
methodology by embedding a long term memory into the tabu list dynamics. The strategies that we present achieve a state-of-the-art performance for well-established benchmark instances of job shop scheduling and max-cut problems.
MB-12
Monday, 10:30-12:00 - Room 004
Graphs and Networks II
Stream: Graphs and Networks
Invited session
Chair: Reinhardt Euler
MB-13
1 - Coloring Circulant Graphs C_n(a,b,c)
Sara Nicoloso, Ugo Pietropaoli
A circulant graph C_n(a_1,...,a_k) is the graph with vertex set v(0), ...,
v(n-1), where each vertex v(i) is adjacent to vertices v(j), j=(i+ x) mod
n, x in a_1,...,a_k. We characterize a class of 3-chromatic circulant
graphs C_n(a_1,...,a_k) with k greater than 2. The approach is based
on an array representation of the given graph, and allows the design of
a linear coloring algorithm.
2 - On Two Matching Problems in Induced Subgrids
Marc Demange, Tinaz Ekim
Given a graph, finding the maximal matching of minimum size
(MMM) and the induced matching of maximum size (MIM) have been
very popular research topics during the last decades. In this paper, we
give new complexity results for these problems in induced subgrids. In
particular, we show that MMM is NP-hard in subgrids of degree 2 and
3 and of arbitrarily large girth. We also show that MIM is NP-hard in
4 regular planar graphs and in subgrids of degree 2 and 4 and of arbitrarily large girth. Finally, we sketch a unified approach to show the
NP-hardness of some problems in subgrids.
3 - On the System of Two Submodular Functions
Dimitrios Magos, Yiannis Mourtos
In the current work we present results on the system of two submodular functions each defined on a different ground set. In particular, we
provide applications where such systems arise and show that they are
totally dual integral. We further generalize this result for systems that
are defined in terms of two submodular and two supermodular functions, i.e., intersection of two generalised polymatroids.
4 - There are only 42 Types of 10x10 Latin Squares (LS)
to Consider in the Search for a Mutually Orthogonal
Triple
Gautam Appa, Reinhardt Euler, Anastasia Kouvela, Dimitrios
Magos, Yiannis Mourtos
Existence of 3 MOLS of size 10 is an open question. Mann gave conditions under which a 10x10 LS L10 has no orthogonal mate. These
relate to the no. of cells with digits other than 1 to 5 in the 5x5 NorthWest corner I of L10. We show that in any pair of orthogonal L10 at
least one must have all 10 digits 1 to 10 in I. Call such a matrix I10. It
follows that for a triple, at least 2 of the 3 must be I10s. So the search
for triples can be confined to pairs of I10s only. But there are only
42 types of single I10s. This does dramatically reduce the number of
cases that need to be considered.
MB-13
Monday, 10:30-12:00 - Room 123
Scheduling Theory and Applications
Stream: Scheduling
Invited session
Chair: Malgorzata Sterna
1 - Late Work Minimization on Identical Parellel Machines
Malgorzata Sterna, Xin Chen, Jacek Blazewicz, Xin Han
We study the scheduling problem on two identical parallel machines
with a common due date and the total late work criterion. Minimizing
late work is equivalent to minimizing late part of jobs, which might
represent customer orders or phases of technological process. We analyzed off-line case, when all jobs are known in advance, proving its
binary NP-hardness, as well as on-line case, when jobs arrive into the
system one by one, showing competitive ratio of list algorithms.
2 - Moldable Tasks in Berth and Quay Crane Allocation
Problem
Maciej Machowiak, Jacek Blazewicz
25
MB-14
IFORS 2014 - Barcelona
The allocation problem of berths to the incoming ships while assigning
the necessary quay cranes is modelled by a moldable tasks scheduling
problem. This model considers the tasks as the ships and the processors
as quay cranes assigned to these ships. Since the duration of berthing
for a ship depends on the number of quay cranes allocated to the ship,
the use of moldable tasks is substantiated. In the model, the processing
speed of a task is considered to be a non-decreasing function of the
number of processors allocated. A suboptimal algorithm to obtain a
feasible solution is presented.
Given a number of tasks, a number of machines, a number of available
resources, the processing times for each task in each machine, and the
necessary resources for the processing of each task in each machine,
the unrelated parallel machine scheduling problem with additional resources consists of finding the assignment of tasks to machines so that
the largest task completion time is minimized and the number of used
resources does not exceed the availability at any time. We here discuss
about exact and heuristic approaches for this problem: integer linear
programming and GRASP algorithms.
3 - Single Track Railway Scheduling Problem
Grzegorz Pawlak, Gaurav Singh
Trains are traveling from the source station to the destination station
they are traveling through the transiting stations on the single track. On
the track between stations only one train can be traveling. Trains can
wait at particular stations, the number of the waiting trains depends on
the station capacity. The source and target station had unlimited capacity. Optimization criterion is to maximize the number of trains running
from the origin to the final destination and back, in the particular time
window.
4 - System Supporting Text Analysis
Grzegorz Fenrich, Malgorzata Sterna
In today’s world, where access to information and publications is very
simple, the problem of text analysis, especially text similarity detection, becomes more and more important. We present a concept of system supporting text analysis devoted mainly to managing documents
generated by students during their academic education. The system
covers all levels, from gathering information from different sources to
their processing in order to compare them to given text, and includes
a library of combinatorial optimization algorithms supporting the text
comparison phase.
MB-14
Monday, 10:30-12:00 - Room 124
Parallel Machines Problems
Stream: Realistic Production Scheduling
Invited session
Chair: Federico Perea
1 - The Parallel Machine Scheduling Problem with Job
Priorities and Sequence-Dependent Setup Times
Chun-Mei Lai, Yu Chao
This study considers the parallel machine scheduling problem with job
priorities and sequence-dependent setup times (PMSPS). Because the
PMSPS involves constraints on multiple job priorities and sequence
dependent setup times, it is more difficult to solve than the classical
machine scheduling problem. The objective is to minimize the total
machine workload. We will provide an efficient transformation which
convert PMSPS into the capacitated arc routing problem (CARP).
Based on the provided transformation, one can therefore solve the PMSPS near-optimally using existing CARP algorithms.
2 - An Iterated Greedy Algorithm for the Unrelated Parallel Machine Scheduling Problem with Setup Times
Eva Vallada, Diana Gonzalez, Ruben Ruiz
In this work an iterated greedy algorithm is proposed for the unrelated parallel machine scheduling problem with sequence dependent
setup times. The iterated greedy algorithm includes a fast Variable
Neighbourhood Search (VNS). We review, evaluate and compare the
proposed algorithm against some of the best methods known from the
literature. After an exhaustive computational and statistical analysis
we can conclude that the proposed method shows an excellent performance overcoming the rest of the evaluated methods in a comprehensive benchmark set of instances.
3 - The Unrelated Parallel Machine Scheduling problem
with additional Resources
Federico Perea, Ruben Ruiz
26
MB-15
Monday, 10:30-12:00 - Room 125
Dynamic and Competitive Pricing Models
Stream: Revenue Management I
Invited session
Chair: María Camila Ramos
1 - Microeconomic Analysis of Cartel Equilibrium Optimization Model
Michal Fendek, Eleonora Fendekova
Methodological problems of formulating oligopoly models rise from
the great diversity of ways in which firms can interact and conclude
agreements on the distribution, market shares and market prices. In
this paper we examine a general scheme of oligopoly equilibrium
model on which we present specific aspects of mutual relations between oligopoly subjects in a process of setting an equilibrium price
and supply of oligopoly. We study the economically interpretable implications of Kuhn-Tucker optimality conditions in a cartel in a context
of its behavior on the market of imperfect competition.
2 - Pricing Game with Customer Choice Based on the
Price-Performance Ratio
Yangyang Xie, Meng Lu, Houmin Yan
We propose a customer choice criterion based on the priceperformance ratio of products. This model is a variation of McFadden’s random utility model. In this paper, we first characterize the
customer choice probability among n substitutable products with a nopurchasing option. We then derive unique close-form equilibrium for
the n competing retailers’ pricing game. We compare the equilibria
of static game and dynamic game, decentralized case and centralized
case. Last, we consider how the equilibrium price changes as one competitor leaves the market or a new product enters the market.
3 - A Pricing and Inventory Decision Model with
Stochastic Demand for Perishable Products
María Camila Ramos, Alejandro Cataldo, Juan-Carlos Ferrer
We develop a methodology to solve a pricing and inventory management problem for perishable products with stochastic demand and a
service level constraint, in a finite time horizon, divided into subperiods. By solving this problem we obtain the order quantity in each
sub-period and the price for the entire horizon. The approach uses Tabu
Search to determine order quantity, a bisection method to solve the
pricing problem and simulation to assess compliance of service level
constraint. We conducted preliminary tests to compare our approach
to the deterministic case and to a real case.
MB-16
Monday, 10:30-12:00 - Room 127
Copositive and Polynomial Optimization II
Stream: Copositive and Polynomial Optimization
Invited session
Chair: Markus Schweighofer
IFORS 2014 - Barcelona
1 - Energy Minimization via Conic Programming Hierarchies
David de Laat
In this talk I will discuss a hierarchy of conic optimization problems
which can be used to compute the minimal potential energy of a system of repelling particles. For instance, in the Thomson problem one
distributes a fixed number of points on the unit sphere to minimize the
Coulomb energy (the sum of the reciprocals of the pairwise distances).
I will show how techniques from harmonic analysis and polynomial
optimization can be used to compute these bounds.
2 - Computing Rational Solutions to Linear Matrix Inequalities
Mohab Safey El Din
I will describe an algorithm which decides the existence of rational
solutions to linear matrix inequalities and computes such solutions in
case of non-emptiness. Such an algorithm can be used to compute
exact sums of squares decompositions of non-negative polynomials
(whenever such decompositions exist). Complexity estimates will also
be provided. A first implementation is powerful enough to provide a
computer-validation of Scheiderer’s example of a multivariate polynomial with rational coefficients that is a sum of squares over the reals
but not over the rationals.
3 - Sparse Polynomial Optimization for Urban Distribution Networks
Martin Mevissen, Bissan Ghaddar, Jakub Marecek
In many optimization problems over urban distribution networks, the
decision maker faces the combined challenge of nonlinear constraints,
system parameters affected by uncertainty, and the scale of the underlying network. However, such problems also exhibit structure, notably
sparsity, which can be exploited in order to improve the scalability of
polynomial optimization solvers. On challenging problems including
AC optimal power flow and pressure management in water networks,
we demonstrate an approach, which exploits sparsity and strengthened
low-order instances of SDP hierarchies.
4 - Polynomial Optimization with Symmetric Polynomials
Cordian Riener
This talk will present some new results related to exploiting symmetries in the context of polynomial optimization with symmetric polynomials. We will show an efficient way of building a block diagonal
moment matrix approach using harmonic polynomials. Further a generalization of the degree principle for symmetric polynomials will be
presented.
MB-17
Monday, 10:30-12:00 - Room 005
Global Optimization and Applications in
Development I
Stream: Global Optimization
Invited session
Chair: Herman Mawengkang
1 - An Interavtive Approach for Solving Multi-Objective
Model of Logistic System and Waste Management in
Crude Palm Oil Industry
Meslin Silalahi, Herman Mawengkang
The crude palm oil industry is an agro-industrial commodity which
has a strategic value to be developed for Indonesian economy. However, there are a number of environmental problems at the factories,
such as high water consumption, the generation of a large amount of
wastewater with a high organic content, and the generation of a large
quantity of solid wastes and air pollution. As we adopt environmental
economics concept, then there are three objectives which are necessarily to be met. Therefore the formulation would take the form of a
multi-objective programming model.
MB-18
2 - An Active Constrained Based Approach for Solving
Problems for Positioning New Products under Risk
Nerli Khairani, Herman Mawengkang
Currently, manufacturers are faced with the rapid change in technology
and customer’s preferences. The problem for positioning new products is a marketing problem faced by a firm which wishes to position
a new brand product considering customer’s preferences. The aim of
the problem considered is to optimally design a new product in order to attract the largest number of consumers. This paper addresses a
mixed integer nonlinear programming model to formulate the positioning problem. A direct search approach is proposed to solve the model.
A computational experience is presented.
3 - The Dynamic Selection of Coordination Mechanisms
in Indonesian Ministry of Religion Affairs Based on
Agent Approach
Azizah Hanim Nasution, Herman Mawengkang
This paper presents and evaluates a decision making framework that
enables autonomous agents to dynamically select the mechanism they
employ in order to coordinate their inter-related activities in Indonesian
Ministry of Religion Affairs. The framework implicates a coordination
mechanisms that assign precepts arising during design time, to something that the agents select to fit their prevailing circumstances and
their current coordination needs. Then agents make informed choices
about when and how to coordinate and when to respond to requests for
coordination.
4 - A Strategic Conflict is a Decision Problem Involving
several Interest Groups or Decision Makers (DMs),
Each of Which has Different Preferences
Zahedi Zahedi, Herman Mawengkang
The allocation, utilization, and management of the forest’s resources
often give rise to serious strategic conflict, typically involving multiple
interest groups, each of whom may have multiple objectives and multiple possible courses of action. We develop the graph model for conflict
resolution in order to study and analyses systematically these forestry
disputes. Then we model the problem as a multi-objective program.
We solve the model using an interactive approach.
MB-18
Monday, 10:30-12:00 - Room 112
Applications of Goal Programming
Stream: Multiobjective Optimization - Theory, Methods
and Applications
Invited session
Chair: Markus Hartikainen
1 - A Real Life Door Assignment Problem with a Multiobjective Structure
Zehra Kamisli Ozturk, Bengül Lepki, Kıymet Özge Güngör
In this study, we consider a real life door-assignment problem in a logistics firm. The objective is to find an optimal assignment of vehicles
to doors and door ranks that minimizes the total service time, the total
distance traveled by the forklifts in the freight yard, deviations from
delivery times and deviations from one-day planning period. These
objectives do not have the same priorities. So, first of all we weigh the
objectives with an ANP model. Then, because of this multi-objective
structure we use goal programming and conic scalarization methods to
obtain efficient solutions.
2 - A Goal Programming Approach To Design The Supply Chain Network
Mehmet Alegoz, Zehra Kamisli Ozturk
Supply chain network design is a problem which includes lots of goals
like minimizing the cost and maximizing the service level. Generally,
the goals contradict each other and it makes the problem complex. In
the proposed model, we prefer to use a goal programming approach
which gives us the opportunity of putting all the five goals into account.
The proposed methodology consist of two important steps. During
the first step, we use a fuzzy MCDM approach to determine the goal
weights. After determining the goal weight, we create the model and
solve it by using goal programming.
27
MB-19
IFORS 2014 - Barcelona
3 - A Non-Interactive Calibration Method of LinearQuadratic Composite Metrics in Compromise Programming
Argyris Kanellopoulos, Aleksander Banasik, G.D.H. (Frits)
Claassen
Utility functions have been used widely to support multi-objective decision making. Expansion of an additive utility function around the
ideal results in a composite linear-quadratic metric of a Compromise
Programming problem. Recovering unknown parameters of the metric
requires interaction with the decision maker who is not always available and consistent. We propose a non-interactive method that uses information on observed attribute levels to recover unknown parameters
and enable forecasting and scenario analysis.The method is applied on
a planning model for sustainable mushroom production.
4 - Prepartaion of Blended Flour by Goal Programming
Abdullah Oktay Dundar, Mehmet Akif Sahman, Mahmut
Tekin, Adem Alparslan Altun
Flour plants attempt to blend different kind of wheat in various ratios
to sustain certain quality levels; besides, they aim to reduce costs. This
situation leads to difficulty in sustaining certain quality standards, and
it requires that conflicting targets should be managed in a proper way.
Goal programming enables managers to consider problems as a whole
by providing solutions to manage conflicting aims. In this paper, a goal
programming model regarding to the problem of flour blend preparation of a flour plant is developed, and results are discussed.
MB-19
Monday, 10:30-12:00 - Room 128
Business Analytics Methods for Demand
and Supply Planning and Control
Stream: Demand and Supply Planning in Consumer
Goods and Retailing
Invited session
Chair: Michael Katehakis
1 - Strategic Inventories and Supply Chain Structure
Sudheer Gupta
We consider a competing supply chains framework where manufacturers sell differentiated products through independent retailers and decide on prices and inventory levels. Retailers can carry inventories forward to next period. We show that in equilibrium retailers will always
carry inventories as a credible source of competition for the manufacturers even in the absence of traditional reasons for inventories. We
show how intensity of product-market competition and ease of carrying inventories forward (holding costs per unit) affect prices, profits
and equilibrium supply chain structure.
2 - Partially Observable Total-Cost Markov Decision Processes with Borel State Spaces and their Applications
Eugene Feinberg, Pavlo Kasyanov, Michael Zgurovsky
This paper describes sufficient conditions for the existence of optimal policies for Partially Observable Markov Decision Processes
(POMDPs) with Borel state, observation, and action sets and with the
expected total costs. Action sets may not be compact and one-step cost
functions may be unbounded. The introduced conditions are also sufficient for the validity of optimality equations, semi-continuity of value
functions, and convergence of value iterations to optimal values. We
discuss applications of the results of this paper to inventory control.
3 - On Optimal Tax Planning and Inventory Systems with
Perishable Items
Nilofar Varzgani, Suresh Govindaraj, Michael Katehakis
We explore the connections between a problem that arises in optimal
tax planning in the finance literature and the problem of usage of inventory with perishable commodities. We show that a problem relating to
the valuation of tax losses that can be used as tax shields against future
income can be solved as an equivalent problem of valuing perishable
commodities. Tax losses, like perishable goods, have a finite useful
life. However, unlike in standard inventory problems, tax losses occur randomly and cannot be "purchased’ or "ordered’ like perishable
commo
28
4 - Inventory Models with Omega-Distributed Demand
Lee Papayanopoulos
In our procurement model, a finite, stable set of retailers place orders for a commodity at random times. We show that total demand
in a period is omega distributed when i) the size of the order from
any given customer remains constant over time and ii) order placement
from a customer in any period is Bernoulli with known expected value
that may vary between customers. We also examine conditions under
which the total demand distribution can be approximated adequately
by a normal or other common, closed-form function. We demonstrate
the usefulness of the omega distribution through simulation.
MB-20
Monday, 10:30-12:00 - Room 129
IFORS Prize for OR in Development 2014 2
Stream: IFORS Prize for OR in Development 2014
Award Competition session
Chair: Andrés Weintraub
1 - Optimizing Ambulance Moveable Station Location
and Vehicle Repositioning to Reduce Response
Times for the City of São Paulo
Luiz Augusto Gallego de Andrade, Claudio B. Cunha
In this paper, we address the problem of determining the optimal number and the location of ambulance stations, as well as the vehicle allocation and repositioning for the Mobile Emergency Care Service of
Sao Paulo (SAMU-SP), in Brazil. This problem arises in the context of
seeking to reduce expected ambulance response times, that was within
27 minutes in Sao Paulo for 98% of the requests. In order to bring total response times down closer to internationally acceptable standards,
SAMU-SP devised the concept of moveable ambulance stations that
can be installed in available public spaces such as squares and parks
and also can be periodically relocated to ensure a good coverage at all
times. This new concept, however, was not an easy sell. It was necessary to clearly demonstrate the benefits that such stations, properly
located, could provide in the context of limited budgetary resources
when compared to the traditional facilities in regular buildings. In this
context, we propose an optimization-based decision support system to
guide SAMU-SP in its strategic decisions involving their service network, as well in the allocation and repositioning of ambulances to each
stand-by points in order to cope with varying demand on different time
periods. The model was applied to analyze different scenarios, including one that was implemented in the short term and yielded an
improvement in the expected coverage of over 40%.
2 - Modelling and Solutions of Slab Allocation and Reallocation Problems in Chinese Steel Industry
Lixin Tang, Gongshu Wang, Ying Meng, Jiyin Liu, Yuan Yuan
Over the last thirty years, China’s steel industry, along with China’s
economy, has developed rapidly. However, in terms of operations management, most steel companies in China are still well behind those in
developed countries and need significant improvements. We worked
with China’s leading steel company, Baosteel, and developed advanced
OR modelling and solving techniques to solve two important operations decision problems on allocating and reallocating slabs to customer orders to improve resource utilization and customer satisfaction. The problems were formulated as an integer linear programming
model and a mixed-integer second-order cone programming model, respectively. Column generation and Lagrangian relaxation techniques
were used to solve the models. For large-scale instances of the slab
allocation and reallocation problems, hybrid metaheuristic algorithms
were proposed to obtain near-optimal solutions within a short computation time. The models and solution methods were successfully
embedded into a computerized decision support system (DSS). The
implementation of the DSS has brought a total direct economic benefit
of $43.16 million USD to Baosteel and reduces carbon dioxide (CO2)
emissions by 238,883 tons annually.
IFORS 2014 - Barcelona
3 - Water Allocation Modelling and Policy Simulation for
the Min River Basin of China under Changing Climatic Conditions
Jiuping Xu
The significant stress on development caused by unsustainable water
resource allocation has been a perplexing problem for the Dujiangyan
Administration Bureau of the Min River Basin, a tributary of the upper
Yangtze River in China. To tackle these regional water resources allocation issues at Sancha Lake, an important area in the lower-right basin
of the Dujiangyan Irrigation System, the local authority was seeking
an optimum allocation strategy to ensure equitable and efficient water use for its subareas, from which the subareas would be able to
provide reasonable reaction strategies. The authority dominates the
water transactions between the subareas involved in water rights distribution, which shows a Stackelberg-Nash equilibrium, with the subareas playing a Cournot-Nash game to develop optimum strategies.
Using a multi-objective multi-stage decision making process with an
uncertain stream now, a multi-objective multi-stage Stackelberg-NashCournot (m2SNC) game is modeled as a bi-level equilibrium optimization incorporating fuzzy random coefficients. An interactive-dynamicprogramming-based genetic algorithm (IDP-GA) is designed to simulate the policies needed for the optimum allocation of water resources
under various climatic scenarios. Specifically, a complete operationalized mechanism for the Sancha Lake area is presented to demonstrate
the practicality and efficiency of the bi-level equilibrium model and the
policy simulation procedure: (1) The bi-level equilibrium model, integrating the Stackelberg-Nash equilibrium and the Cournot-Nash equilibrium, is an efficient tool to determine optimum water resource allocation strategies. (2) Similar to the principles of an input-output system
and the computable general equilibrium (CGE), the policy simulation
system with an IDP-GA, an extension of principle of CGE, inputs scenario data and outputs an early-warning mechanism to inform the policy suggestions. (3) An emergency response cooperative mechanism
based on allocation modes dominated by an authority is a relatively
equitable and efficient method for developing countries which need to
cope with uncertain situations under changing climatic conditions.
MB-21
Monday, 10:30-12:00 - Room 006
Optimization Modeling Software &
Systems 2
Stream: Optimization Modeling in OR/MS
Invited session
Chair: Robert Fourer
1 - Recent Developments in IBM ILOG CPLEX Optimizer
Xavier Nodet
Recently added features and performance enhancements will be presented. Particular emphasis will be given to distributed computing
options available with the CPLEX Remote Object and the distributed
parallel MIP algorithm as well as the solver for global solutions to
nonconvex MIQP.
2 - Robust Problem Formulation Alternatives
Susanne Heipcke
Many optimization models include strategies for improving the
model’s robustness based on an intuitive definition of what is ’robust’.
The first part of the talk reviews examples of such model formulation techniques. The second part presents cases that are not easily addressed this way with implementation examples using the new robust
optimization framework of the FICO Xpress suite.
3 - Developments in the AMPL Ecosystem
Gautam Mitra, Christian Valente
For the AMPL modelling language ecosystem we report new developments which include: (i) AMPLDev, an advanced Integrated Development Environment for AMPL; (ii) SAMPL, a collection of extensions
to AMPL for stochastic programming and robust optimisation models; and (iii) FortSP, a solver that processes stochastic programming
problems and SOCP instances of robust optimization problems, using CPLEX or Gurobi as embedded solver and Benders decomposition
with regularisation by the level method. We also describe AMPLDev
cloud, which makes this software available via a cloud-based service.
MB-23
4 - Optimizing a Manufacturing Process using JMP
Volker Kraft
This case study will demo JMP in capability analysis and process optimization, dramatically improving a manufacturing process. Dynamic
visualization tools in JMP help to explore relationships between process factors and responses. As a next step various modeling techniques
determine the most important factors and how they collectively impact
process quality. Factor optimization will determine the best-case process capability, before finally simulating the process under real-world
conditions. The live demo incorporates a wide range of tools for data
exploration, modeling and simulation.
MB-22
Monday, 10:30-12:00 - Room 007
OR and Health Care Management
Stream: Health Care Data Analytics
Invited session
Chair: Janny Leung
1 - The Impact of Directed Choice on the Design of Preventive Healthcare Facility Network Under Congestion
Navneet Vidyarthi, Onur Kuzgunkaya
Preventive healthcare (PH) programs and services aim at reducing the
likelihood and severity of potentially life-threatening illness by early
detection and prevention. The effectiveness of these programs depends
on the participation level and the accessibility of the users to the facilities providing the services. In this talk, we study the impact of
system-optimal directed choice on the design of the preventive healthcare facility under congestion. We present a model, solution approach,
and insights using a case study that deals with locating mammography
clinics in Montreal, Canada.
2 - Medical Decision Making in Resource Constrained
Environments
Mariel Lavieri
I discuss ongoing work on allocating constrained resources across a
panel of patients. This work is first applied to guide the sequential
allocation of fixed screening capacity. The allocation of constrained
treatment resources is then discussed. The models are calibrated using
longitudinal clinical data from chronic disease patients.
3 - Using Simulation to Analyze Patient Flows in a Hospital Emergency Department in Hong Kong
Janny Leung, Yong Hong Kuo, Colin Graham, Omar Rado,
Benedetta Lupia
This paper presents a case study of applying simulation to analyze patient flows in a hospital emergency department in Hong Kong. The purpose of our work is to analyze impact of the enhancements made to the
system after the relocation of the department. We developed a simulation model to capture all the key relevant processes of the emergency
department. Using the simulation model, we evaluated the impact of
possible changes (such as, adjusting staffing levels or shift times) to
the system by running different scenarios.
MB-23
Monday, 10:30-12:00 - Room 008
Behavioural Issues in Decision Making
and Negotiation
Stream: Behavioural Operational Research
Invited session
Chair: Etienne Rouwette
29
MB-24
IFORS 2014 - Barcelona
1 - Decision Analysis in the Context of the Behavioural
Reality in Organizations — An Empirically Supported
Framework for Analysing Implementation Problems
Ana Barcus, Kai Helge Becker, Gilberto Montibeller
Decision analysts’ experience shows that the practical implementation
of their methods often turns out to be difficult. Our paper contends that
these difficulties are the consequence of a gap between the prescriptive approach of decision analysis and the way in which unsupported
decision making is typically carried out. We suggest an empirically
supported framework that describes the nature of this gap and discuss
its implications for the decision analysis practice, thereby offering a
systematic way to reflect on the challenges that decision analysts encounter.
2 - Cognitive and Motivational Biases in Risk and Decision Analysis
Gilberto Montibeller, Detlof von Winterfeldt
Behavioral decision research has demonstrated that judgments and decisions of ordinary people and experts are subject to numerous biases.
Decision analysts often face such biases when eliciting models and parameters from decision makers or experts. Some of them are due to
faulty cognitive processes, some are due to motivations for preferred
analysis outcomes. The purposes of this talk are to identify the cognitive and motivational biases that matter, as well as those that do not
matter, show how they distort judgments involved in modeling, and to
suggest effective debiasing techniques.
3 - The Impact of Need for Closure on Model-supported
Group Conflict Management
Etienne Rouwette, L. Alberto Franco, Hubert Korzilius
Need for closure, the desire for definite knowledge on an issue, has
important impacts on decision making. Decision makers that are high
in need for closure seize on information and then freeze on early cues.
We focus on the impact of need for closure on conflicts in decision
making groups. The groups in our study use Value Focused Thinking
to jointly develop a model. We compare MBA and MSc groups high
and low in need for closure with regard to a) conflicts and how these
are resolved and b) group outcomes such as consensus and satisfaction,
using interaction/ phasic and multilevel analysis.
4 - Using Analytic Hierarchy Process to Enhance Consensus in Multi-agent Multi-issue Negotiation
Djamila Boukredera, Kamal Hariche, Maamri Ramdane,
Rabah Kassa
This paper proposes to use the Analytic Hierarchy Process (AHP) to
enhance consensus in bilateral multi-issue negotiation with incomplete
information. We focus on mediated negotiation, where two agents try
to reach an agreement over a range of qualitative and quantitative issues. We assume that the mediator agent adopts the AHP method to
construct the ranking of the alternatives based on both agents’ preferences defined beforehand. Based on a case study, we show how AHP
can provide a simple and effective decision making leading to an efficient and timely conflict resolution.
MB-24
Monday, 10:30-12:00 - Room 212
Preference Learning II
Stream: Preference Learning
Invited session
Chair: Roman Slowinski
1 - Descriptive Models of Deliberated Preferences
Olivier Cailloux
Prescriptive approaches to decision making aim at letting the decision
maker (DM) think about, and possibly change, her preferences. This
talk relates to validation of preference models obtained following such
an approach. We propose to view the preference modeling task as aiming to describe the many possible views and arguments a DM can adhere to when facing a decision problem. By integrating elements from
formal argumentation theory, we show how this view can render a preference model falsifiable, without having to adopt the belief that precise
preferences pre-exist in the head of the DM.
30
2 - New Veto Rule for a Sorting Model
Olivier Sobrie, Marc Pirlot, Vincent Mousseau
In MCDA outranking methods, an alternative is considered at least as
good as another one if a majority of criteria support this assertion and
if there is no strong opposition, i.e., veto, among the minoritarian criteria. We give an overview of existing veto models in the literature. In
the context of the sorting problematic, we introduce a new veto rule
for a model based on ELECTRE-Tri in order to increase its descriptive ability. We present a Mixed-Integer Program and an heuristic that
allow to learn the parameters of such a model on basis of assignment
examples.
3 - Integrated Preference Disaggregation Framework for
Value-Driven Multi-Criteria Sorting
Milosz Kadzinski, Krzysztof Ciomek, Roman Slowinski
We introduce a new preference disaggregation method for multicriteria sorting. The preference information supplied by the Decision
Maker is composed of (1) possibly imprecise assignment examples,
(2) desired class cardinalities, and (3) assignment-based pairwise comparisons. The exploitation of all compatible value functions results in
(1) necessary and possible assignments, (2) extreme class cardinalities,
and (3) necessary and possible assignment-based preference relations.
By exhibiting these outcomes, we provoke the DM in various ways to
enrich her preference information interactively.
4 - Robust Ordinal Regression for Dominance-based
Rough Set Approach to Decision under Risk
Roman Slowinski, Milosz Kadzinski, Salvatore Greco
We consider decision under risk where preference information provided by a decision maker is a classification of some reference acts
described by outcomes to be gained with given probabilities. We
structure the classification data using a variant of the dominance-based
rough set concept. Then we induce all possible sets of minimal cover
rules which correspond to all instances of the preference model compatible with the input preference information. We apply these instances
on a set of unseen acts and draw robust conclusions about their quality
using the robust ordinal regression paradigm.
MB-25
Monday, 10:30-12:00 - Room 009
Mathematical Economics and Optimal
Control
Stream: Mathematical Economics
Invited session
Chair: Alexander Zaslavski
1 - Optimal Irrigation Scheduling for Wheat Production
in Manitoba: A Simulation Study
Raphael Linker, Ilya Ioslovich
The current practice in Manitoba (Canada) is to grow wheat as a rainfed crop. We investigated whether applying supplemental irrigation
could increase yield significantly. The optimization problem can be expressed as: Given weather and soil data, obtain maximum yield subject
to irrigation water quota. Solving this problem for different values of
the water quota allows creating an irrigation water use efficiency function which presents the yield as a function of the irrigation applied.
This optimization problem was solved with the TOMLAB optimization library and the AquaCrop model
2 - Harvesting in an Age-Structured Population
Vladimir Veliov, Anton Belyakov
We investigate an age-structured infinite-horizon optimal control
model of harvesting a biological resource, interpreted as fish. Time and
age are considered as continuum variables. The main result shows that
in case of selective fishing, where only fish of prescribed sizes is harvested, it may be advantageous in the log run to implement a periodic
fishing effort, rather than constant (the latter suggested by single-fish
models that disregard the age-heterogeneity). Thus taking into account
the age-structure of the fish may qualitatively change the theoretically
optimal fishing mode.
IFORS 2014 - Barcelona
3 - Hierarchical Organizations
Zvi Winer, Benjamin Bental
This paper endogenizes the number of hierarchical layers, workers per
layer, control spans of supervisors and the wage scale in hierarchical
organizations. To monitor production workers’ hidden effort the organization hires supervisors whose effectiveness also depends on hidden
effort, and so on. The number of production workers and their induced
effort is traded off against the overhead costs generated by the hierarchical structure needed to control the system. The latter limits the
optimal size of the organization even if production is characterized by
increasing returns to scale.
MB-28
4 - Fuzzy Scenario-based Multi-Criteria Optimisation of
a Manufacturing Supply Chain
Jiabin Luo, Dobrila Petrovic
A real-world supply chain which consists of suppliers, a manufacturer
and customers is considered. Raw materials are purchased in advance
according to forecasted customer demand; customers can change their
order at any time. In order to meet changed customer demand, raw
material can be ordered from a standard supplier or a local supplier at
different prices and lead times. A two-stage fuzzy scenario-based optimisation model is developed to determine the orders for a planning
period, in such a way as to maximise the effectiveness, robustness and
resilience of the supply chain.
4 - Steady State Properties in a Class of Dynamic Models
Amos Zemel, Yacov Tsur
We characterize the location, stability and approach-time of optimal
steady states in single-state, infinite-horizon, autonomous models by
means of a simple function of the state variable, defined in terms of the
model’s primitives. The method does not require the solution of the underlying dynamic optimization problem. Its application is illustrated in
the context of a generic class of resource management problems.
MB-27
Monday, 10:30-12:00 - Room 213
OR in Quality Management II
Stream: OR in Quality Management
Invited session
Chair: Aysun Kapucugil-Ikiz
MB-26
Monday, 10:30-12:00 - Room 010
Fuzzy Multiobjective Programming
Stream: Fuzzy Decision Support Systems, Soft Computing, Neural Network
Invited session
Chair: Monga K Luhandjula
1 - Approximation and Equivalence Approaches for
Fuzzy Multiobjective Programming Problems
Monga K Luhandjula
In this paper, we present approximation and equivalence approaches
for dealing with an optimization problem with several fuzzy objective
functions. The first one is based on the Nearest Interval Approximation
Operator for fuzzy numbers and the second is based on an Embedding
Theorem for fuzzy numbers. Our approaches strike a balance between
computational efficiency and effectiveness in representing the reality.
Numerical examples are also provided for the sake of illustration.
2 - Mathematical Programming Problems with Several
Fuzzy Objective Functions
Moeti Rangoaga
In this paper, we propose an approach for multiobjective programming
problems with fuzzy number coefficients. The main idea behind our
approach is to approximate involved fuzzy numbers by their respective
nearest interval approximation counterparts. An algorithm that returns
a nearest interval approximation to a given fuzzy number, plays a pivotal role in the proposed method. Our approach contrasts markedly
with those based on deffuzification operators which replace a fuzzy set
by a single real number leading to a loss of a lot of important information. A numerical example is also provided.
1 - The Factors to Affect Gap Between Exhibitors’ Expectations and Visitors’ Perceptive Satisfactions in
Trade Shows
Kuochung Chang
Trade shows are always the excellent sources and opportunities for
marketing programs. The study is purposed to verify the visitors’ quality perspective of trade shows in 3C and design industries. Besides, the
interaction quality is thought to be influenced by attitudes, behavior,
and expertise of service personnel. Therefore, the study uses the analytic hierarchy process (AHP) to resolve the priorities of the influential
dimensions in the trade show quality, and finds out the existed gap between exhibitors’ expectations and visitors’ perceptive satisfactions.
2 - Hybrid Quality Function Deployment for Tool Making
Cem Kayguluoglu, Gül Gökay Emel
Our study presents a Hybrid QFD for tool making; by integrating fuzzy
app., Analytic Hierarchy Process and Axiomatic Design principles.
AD independence axiom is used to check the dependency level of Customer Needs to have CNs which could be satisfied without affecting
each other. Fuzzy AHP is used to define the degree of importance. After defining the absolute weight of CNs with QFD methodology; AD
information axiom is used to define the final importance ranking of
ECs by exploring the roof correlation. Aim of the study is to max. the
efficiency of QFD by min. the effect of correlations.
3 - A Fuzzy-QFD Decision Model for Service Design
Aysun Kapucugil-Ikiz, Aşkın Özdağoğlu, Güzin Özdağoğlu
Quality Function Deployment (QFD), a well-known methodology,
dedicated to translating customer needs (qualitative data) into technical characteristics (quantitative data) to develop products and services.
Literature well defines some technical issues occurring in this transformation and also in determination of design targets in QFD methodology. As a solution to the technical issues, this study proposes a fuzzy
optimization model which considers budget factors and uncertainties
in order to balance between customer and organization satisfaction in
service design.
3 - Fuzzy Linear Programming Problems with Appropriate and Flexible Membership Functions
Takashi Hasuike, Hideki Katagiri, Hiroe Tsubaki
This paper considers a general fuzzy linear programming problem with
flexibility of membership functions based on interval values involving
ambiguity and decision maker’s subjectivity. Since this proposed problem is not well-defined due to fuzziness, some fuzzy mean values and
mathematical relations between two intervals are introduced. The main
linear programming problem is transformed into a standard mathematical programming problem according to each fuzzy mean value and
relation, and hence, each strict algorithm is developed.
MB-28
Monday, 10:30-12:00 - Room 130
Challenge ROADEF/EURO 2
Stream: Challenge ROADEF/EURO
Award Competition session
Chair: Safia Kedad-Sidhoum
31
MB-29
IFORS 2014 - Barcelona
1 - A Multi-stage Selection Hyper-heuristic for Rolling
Stock Unit Management on Railway Sites
Ahmed Kheiri, Elsayed Elsayed
3 - Sensitivity Analysis of Nonlinear Behavior with Distorted Probability in an Incomplete Market
Xiangwei Wan, Xi-Ren Cao
We propose an easy-to-implement, easy-to-maintain, yet an effective multi-stage selection hyperheuristic approach to solve the challenge problem. Selection hyper-heuristics, also known as ’heuristics to
choose heuristics’, are high level search methodologies which control
and mix a fixed set of low level heuristics (neighbourhood operators)
under an iterative framework. The proposed approach aims to exploit
a large set of constructive and perturbative low level heuristics, each
of which attempts to enhance an aspect of the quality of a solution in
hand during the search process.
The dynamic programming fails to work when a distortion in performance probability appears. In this talk, we use the sensitivity-based
analysis to study this nonlinear behavior with probability distortion.
We find a local linearity property of the distorted performance, which
we call mono-linearity, and apply it to the portfolio management problem under distorted performance in an incomplete continuous market.
The first-order condition for the optimal solution is presented, from
which we obtain several characterizations of optimal solutions in the
general market setting of incomplete markets.
2 - Constructive and Heuristic Algorithms for a Rolling
Stock Management Problem
Florence Thiard, Hugo Joudrier
We develop an algorithm to solve an industrial problem submitted by
SNCF to the EURO/ROADEF Challenge 2014. The goal is to manage the traffic inside a railway station, under numerous constraints. In
order to rapidly obtain initial feasible solutions, we develop a greedy
constructive algorithm. These solutions are built by scheduling trains
to storage units, then assigning departures when possible. To obtain
relevant upper bounds and improve our initial solutions, we then move
towards a metaheuristic approach.
3 - Local Search Algorithm for Trains Scheduling on
Railways Sites
Szymon Wasik, Piotr Zurkowski, Wojciech Jaśkowski
The presented algorithm for solving the ROADEF Challenge 2014
problem consists of several phases. First, we use a heuristic based on
network flow algorithms that determines the initial assignment of arriving trains to departure requests. Then, we use a simple construction
heuristic on a resource-time graph to verify and improve the initial assignment. Finally, the solution is optimized using various local search
techniques. A simplified version of this approach with much worse
results was ranked on 6th place during the qualification phase.
MB-29
Monday, 10:30-12:00 - Room 011
Stochastic Models and Finance
Stream: Financial Optimization
Invited session
Chair: Xiangwei Wan
1 - Portfolio Decision under Loss Aversion Preference
with Mean-reverting Returns
Jianjun Gao, Xiangyu Cui, Duan Li
The loss aversion, which describes the inconsistency of an investor’s
risk attitude for loss and gain, plays a central role in famous Prospect
Theory in behavioral finance. On the other hand, there are abundant empirical studies which document the phenomena of the meanreverting of the stock return. In this research, we propose a portfolio optimization model combining these two features. We develop the
semi-analytical solution of such a problem by using the method of Inverse Fourier Transformation. The revealed portfolio policy exhibits
different features compared to the classical policy.
2 - The Survival Distribution of SABR Model
Nian Yang
In this paper, we work out the asymptotic formulae for the rst passage time, the marginal and joint survival probability densities of the
SABR model. To the best of the author’s knowledge, this is the first
time to obtain asymptotic solutions of problems with a lower absorbing boundary. These formulae have a wide range of applications such
as the survival probability, pricing down-and-out barrier option under
SABR model, etc. The numerical results show that our analytic formulae are accurate and efficient.
32
MB-30
Monday, 10:30-12:00 - Room 012
Financial Mathematics and OR
Stream: Financial Mathematics and OR
Invited session
Chair: Gordon Dash
Chair: Nina Kajiji
1 - Hierarchical Neuro-Cybernetic Systemic Risk Factors for Multiobjective ESG Portfolio Optimization
Gordon Dash, Nina Kajiji
Investment approaches that embrace environmental, sustainability
and governance (ESG) factors provide investors with long-term riskmitigated performance gains. While ESG factors offer a wider view
of the risk-return profile such factors are known to dampen short-run
portfolio returns. This paper uses an artificial neural network (ANN)
to capture ESG stylized effects from traded ETFs. The ANN linear
weights are combined with a combinatorial nonlinear multiple objective portfolio optimization model to overcome the performance dampening effects observed in the traditional mean-variance approach.
2 - Entrepreneurial Decisions on Effort and Project with
a Non-Concave Objective Function
Abel Cadenillas, Alain Bensoussan, Hyeng-Keun Koo
We solve an entrepreneurial/managerial decision making problem. We
use a general expected utility function. We show that the optimization
problem with the non-concave objective function has the same solution
as the optimization problem when the objective function is replaced by
its concave hull. We also show that the final wealth cannot take value
in the region where the objective function is not concave. This implies
that the risk taking explodes as time nears maturity if wealth is equal
to the right end point of the non-concave region.
3 - Sustainability of the Japanese Pension System with
the Automatic Balancing Mechanism
Masanori Ozawa, Tadashi Uratani
The Japanese pension system is a two-tier system which is composed
of the employees’ pension insurance and the national pension. There is
a slowdown in economic growth in the recent decade. The population
forecast shows a rapid growth of aged population and a low level in
fertility. Therefore, the government introduced an automatic balancing mechanism for pension finance. We study the sustainability of the
pension system with stochastic simulations under some scenarios.
4 - Optimal Investment Problem for Eco-Product
Masashi Toyoda, Katakai Takafumi, Katsunori Ano
We study the optimal stopping problem for the optimal investment
problem of the eco-product company, such as energy supply with solar
panel, in the real option framework, that is solved by the free-boundary
problem approach to the corresponding optimal stopping problem. We
naturally assume that the return of the investment depends on the remaining time to a certain finite time.
IFORS 2014 - Barcelona
MB-31
Monday, 10:30-12:00 - Room 013
Decision Processes under a Life-cycle
Perspective
Stream: Decision Processes
Invited session
Chair: Luis C. Dias
MB-33
1 - Discrete Event Simulation for Performance Modelling
in an Outpatient Clinic
Aline Mendes, Paulo Rotela Junior, Luisa Moschioni
In an outpatient clinic the proper functioning of scheduled appointments is of paramount importance. The malfunction of this care leads
to delayed diagnosis and treatment, causing high costs for the government as a consequence which justify the reason why optimization of
this process is required. Applying Discrete Event Simulation, by using
the IDEF-SIM technique and the ProModel software, this paper aims
to analyze and optimize an outpatient clinic of a hospital located in
Bragantina region of Sao Paulo state, demonstrating the applicability
of Discrete Event Simulation in healthcare field.
1 - Applying MCDA without Precise Weights to LifeCycle Environmental Assessment of Vehicle Alternatives
Luis C. Dias, Ana Rita Domingues, Fausto Freire, Rita
Garcia, Pedro Marques
2 - Developing and Validating Joint Dynamic Ambulance
Relocation and Flexible Dispatching Strategies: A
Simulation-Optimization Approach
Cem Saydam, Xun Li
Six technologies of compact passenger vehicles available in Portugal (internal combustion and electric) are evaluated by combining
Life-Cycle Assessment (LCA) and Multi-Criteria Decision Analysis
(MCDA). The evaluation is based on environmental indicators from
Life-Cycle Impact Assessment and operation indicators. The ELECTRE TRI method (IRIS software) is used to sort the alternatives in
performance classes, without requiring precise criteria weights. Combining ELECTRE TRI and LCA allows synthetizing the environmental
assessment of the vehicles without requiring value trade-offs.
We present a simulation embedded optimization approach for relocating ambulances and determining flexible dispatch policies for maximum performance. A realistic simulation model allows us to remove
most of the simplifying assumptions which are required in analytical
approaches. Using experimental and real data we show that this approach can provide a detailed output that can be used by EMS managers to estimate lives saved for multiple life threatening situations
while providing a plethora statistics on important performance measures such as actual vehicle busy probabilities and response times.
2 - Multi-Criteria Analysis of Low Voltage Grid Expansions
Tobias Lühn, Jutta Geldermann
Due to the increasing generation capacity of photovoltaics connected
to the German low voltage grid, distribution system operators (DSOs)
are challenged to prevent the overload of grid components and the violation of voltage range. Therefore, DSOs have to evaluate novel smart
grid concepts leading to new types of structure, design and operation
of distribution grids. These grid expansion concepts are analysed regarding environmental, economic, technological and social dimensions
using the approach of multi-criteria decision making.
3 - Multicriteria Assessment of the Use of Renewable
Resources under a Life-cycle Perspective
Jutta Geldermann, Meike Schmehl
Energy and material products based on renewable resources have different and partly opposing effects on sustainable development throughout their life-cycles. Based on one hectare agricultural land as common
functional unit, four alternatives of use of renewable resources are assessed by a PROMETHEE-model. As the modeling of these different
product systems requires heterogeneous kind of data sources, a pedigree matrix of data quality is implemented into the approach. Consequences for decision processes under a life-cycle perspective will be
discussed.
4 - Incorporating Different Cognitive Styles into a DSS
based on ILS Model
Ana Paula Costa, Levi Adelino Lima
This paper proposes to incorporate the cognitive style of different decision makers in a Decision Support System. In this research, an empirical study is performed to evaluate user satisfaction using a DSS which
incorporate the learning style of the user based on Index Learning Style
(ILS). The prototype developed offers different versions of DSS appropriate to each decision maker learning style, identified by the system
through a questionnaire. The results of an experiment conducted with
undergraduate and graduate students point differences in the levels of
satisfaction in using the DSS.
3 - Analysis of the Dengue’s Fever Care in a Basic Health
Unit Using Discrete Event Simulation
Luisa Moschioni, Paulo Rotela Junior, Aline Mendes
Diseases outbreaks have different impacts in populations. In the
Brazilian state of Goias, there have been many dengue’s fever outbreaks, which have effects on society. Especially the financial effects
concern particularly the municipal’s governments. This current study
uses the Promodel software, an discrete event simulation software, to
analyze and optimize the costs for the official flowchart of dengue’s
fever care in the basic health unit of Ipora, in order to reduce them,
however without losing process quality, helping the economy of the
outbreak’s area.
4 - Multi-Optimization in the Partitioning Healthcare System of Parana State, Brazil
Maria Teresinha Arns Steiner, Dilip Datta, Pedro Steiner
Neto, Cassius Tadeu Scarpin, José Rui Figueira
Partitioning health services is a proposal to aggregate municipalities
into microregions in a way to facilitate patients flow when in need for
procedures not offered in their municipalities. This paper aims to "optimize" the division of Parana State, Brazil, into microregions through
the use of a multi-objective genetic algorithm. Three objective functions (homogeneity its population; variety of medical procedures; distances), for defining the microregions, have been considered. The results may have a strong impact on the healthcare system management
in Parana State.
MB-33
Monday, 10:30-12:00 - Room 015
Environmental Sustainability in Global
Operations
Stream: Environmental Sustainability in Supply Chain
Invited session
MB-32
Monday, 10:30-12:00 - Room 014
Health Care Analytics
Stream: Humanitarian Operations Research
Invited session
Chair: Silja Meyer-Nieberg
Chair: Erik Kropat
Chair: Maria Teresinha Arns Steiner
Chair: Emel Arikan
1 - Investigating the Role of Electrified Vehicles for Automotive Industry Supply Chain and Fleet Sustainability
Matthias Kannegiesser, Hans-Otto Guenther, Niels Autenrieb
Electrified vehicle powertrains are perceived as key measures towards
a zero emission and more sustainable automotive industry. We investigate how vehicle electrification may change end-to-end industry supply chain structures together with fleet powertrain mixes long-term towards 2030 and if these changes are sustainable with respect to costs,
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IFORS 2014 - Barcelona
CO2 emissions and jobs created. We use a sustainability optimization
framework applied to comprehensive industry data with a specific focus on supply chain steps and vehicle fleets in Germany and Europe
vs. China.
2 - A Multi-Objective Modeling Approach for Intermodal
Transport Planning with Environmental Aspects
Martin Hrusovsky, Emrah Demir, Wolfgang Burgholzer,
Werner Jammernegg, Tom Van Woensel
Growing transport volumes induce new challenges for transport planners as increasing traffic congestion leads to more and more uncertainty and volatility of travel times as well as increased GHG emissions. Therefore, the need for new transport alternatives combining
different transport modes is evolving. We propose a linear mathematical model in the form of a multi-commodity, capacitated network design formulation which considers time-dependent travel times and enables transport planning optimization according to costs, travel time
and emissions.
3 - On the Effectiveness of Emission Prices in Decentralized Supply Chains
Saif Benjaafar, Xi Chen
We show that pricing emissions in a decentralized supply chain can
paradoxically lead to higher overall supply chain emissions and for
this emission to increase in the emission price. We discuss several
remedies and the social welfare implications of each. We illustrate our
analysis with several applications.
MB-34
Monday, 10:30-12:00 - Room 016
Large-Scale Risk Systems
Stream: Data Mining in Finance and Commodities
Invited session
Chair: Gegoire Caro
Chair: Dejan Stokic
1 - Robust Multivariate Regression for Large Scale Risk
Systems
Gegoire Caro
This study is focusing on the mapping of instrument returns on a set of
market returns, as done for the CAPM model. The standard approaches
implemented in the industry combine a set of heuristic rules based on
the instrument meta-data with a univariate regression. The contribution of this work is a listing of the requirements of this mapping in
the context of large scale risk systems, and a solution inspired from
the LASSO regression to combine heuristic and statistics in a single
optimization framework.
2 - Stress Testing Framework in a Large Scale Risk System
Paraskevi Papoula
This study focuses on hypothetical scenarios of market risk drivers. A
way to translate the scenarios assumptions of a few risk drivers into
the other risk factors via the covariance matrix is explained. One can
also stress the covariance matrix or equivalently the correlation matrix
through exposures to latent drivers of various risk driver groups. A
solution using the latent factor theory is recommended to combine the
historical correlations with a target/limit correlation matrix.
3 - Temporally Weighted Portfolio and Purchasing Sequences for Next-Purchase Prediction
Katerina Shapoval, Thomas Setzer
Although a customer’s purchasing history might provide valuable information to better identify target customers, it is often considered in a
very aggregated fashion, as such data would drive complexity due to an
explosion of potential product sequences. We propose an approach to
incorporate purchasing information by applying supervised clustering
techniques on past purchases weighted nonlinearly, with more weight
given to more recent purchases. Exploiting a unique set of empirical
data of a large telecommunications provider, the experimental results
on predictive accuracy are presented.
34
4 - Impact of Market Data Quality on Capital Requirements
Dejan Stokic
Data cleansing of financial time series is being established as a crucial part of risk management. We show how the different approaches
in assessing the data quality of equity, interest rates and currency risk
factors directly influence the estimated market risk, evaluated with different risk measures. The sensitivity of the historically simulated risk
measures on the risk factor data quality impacts the capital adequacy
of the financial institutions furthermore.
MB-35
Monday, 10:30-12:00 - Room 131
Stochastic Sports Analysis
Stream: Stochastic Modeling and Simulation in Engineering, Management and Science
Invited session
Chair: Norio Torigoe
1 - Mathematical Modeling of Team Competition in Artistic Gymnastics
Nobuyoshi Hirotsu, Mutsumi Harada, Minoru Kano
We model men’s team competition in artistic gymnastics of a 6-5-4
format, and propose a mathematical formulation for calculating a team
score, considering each gymnast’s score as a normal distribution. By
setting the different mean and SD of the normal distributions, we calculate the distributions of the team score, and obtain the relationship
between the mean and SD of the each gymnast and the expected number of the team score. Using this model, we demonstrate the method
for selecting five gymnasts and analyze the sensitivity of an improvement of each gymnast’s performance to the team score.
2 - Are Soccer Schedules Robust?
Dries Goossens, Fabrice Talla Nobibon
This talk focuses on the robustness of soccer schedules. We analyze the
schedules of ten main European soccer leagues and we find that soccer
seasons are hardly ever played as initially scheduled. This is due to disruptions, which require some games to be rescheduled. The data of the
last ten seasons reveal that these disruptions have a profound impact
on the quality of the final schedule, indicating that soccer schedules in
Europe are computed without taking uncertainty into account.
3 - Figure Skating Scoring Optimization and Analysis
Kellie Keeling, Sydney Raith
In 2002, the International Skating Union scoring system was updated
to make the system more objective, transparent, and fair to the competitors. In this study, we examine how the judging system has impacted
the skater’s strategy and their rankings. We use simulation to develop
strategies to place elements of a program in or out of Bonus time.
MB-36
Monday, 10:30-12:00 - Room 132
Integrated Forest Planning
Stream: OR in Agriculture, Forestry and Fisheries
Invited session
Chair: Christian Rosset
1 - Rethinking the Strategic Model
Eldon Gunn
If, in addition to its role in evaluating and planning landscape level
ecosystem strategies, the strategic forest management modelling involves wood supply to the forest industry, then it seems obvious that
it needs to include a reasonable representation of the industry capacity and how it might change over time. This paper discusses what this
means for the mathematical structure for the model. We also raise
questions about the appropriate time horizon for analysis. There are
good reasons that this time horizon should be much shorter than it has
been conventionally.
IFORS 2014 - Barcelona
2 - Models and Mathematical Decomposition for LargeScale Location Problems in the Forestry Sector
Bernard Gendron, Jean-François Cordeau, Sanjay Dominik
Jena
We present mathematical models and algorithms for a complex location problem which is found in the forestry sector. Based on logging
demands for the next five years, this problem investigates the optimal
number, locations and sizes for new camps in order to host workers involved within logging activities and balance transportation, camp construction and camp relocation costs. The problem includes a very detailed cost structure. We compare different models and present heuristics based on two different Lagrangian decomposition approaches, capable to solve even very large instances.
3 - Integrated Planning and Control of Forest-based
Supply Chains with Focus on Forest Management:
Limitation and Potentialities
Christian Rosset, Germano Veiga, Alexandra Marques, Jussi
Rasinmäki
Systematic planning and control of forest-based supply chain involving different actors is a key ingredient for overall sustainability and
efficiency. The FOCUS project (focusnet.eu) aims to develop innovative solutions based on pilot study cases in several countries across
Europe. The blend of operational planning with the concept of modelbase control inspired in its use in industrial processes is a new and
promising approach. This paper discusses the potentialities and limitations of such a concept and draws the outlines of a planning and control
software focused on forest management.
4 - A Model for Optimal Crop Selection Based on Conditional Value-at-Risk
Carlo Filippi, Renata Mansini, Elisa Stevanato
Consider a farmer in a temperate zone who has to select crops to be
cultivated on a piece of land in order to maximize the total expected
profit on a given time horizon while considering: resource requests
for each crop; machinery and manpower availability; timing of the operations required by each crop; market price and yield variability of
harvested products. We propose a stochastic MILP model that allows
to maximize the average expected return under a predefined quintile
of worst realizations. We use the model to prove the advantages of
resource aggregation among different farmers.
MB-37
Monday, 10:30-12:00 - Room 017
AHP Application
Stream: AHP (Analytic Hierarchy Process) /ANP (Analytical Network Process)
Invited session
Chair: Yoichi Iida
1 - The AHP Based on Weighted Sum
Yoichi Iida
I propose the AHP based on weighted sum. This method can restore
the evaluation ratios of alternatives with respect to criteria in a meaning of weighted sum. The conventional AHP can often not restore such
evaluation ratios of alternatives with real evaluation values. I think that
this is a reason which users feel like it does not work well for such alternatives, although it is proper for intangible alternatives. The method
has two versions. I also show the validity of this method mathematically. This is different from the ANP since it does not deal with dependence within or between clusters.
2 - Mapping Verbal AHP Scale to Numerical Scale for
Cloud Computing Strategy Selection
Alessio Ishizaka
In Analytic Hierarchy Process (AHP), evaluations are given on a verbal scale and then converted into quantitative values for calculating the
priorities. Several conversion scales have been proposed. In order to
select the best matching scale according to the mental representation
of each individual decision-maker, verbal scales are first used to compare alternatives with known measures, e.g., surface of figures. The
best matching scale representing the real values is then selected. This
AHP with individualised scales has been applied in a real case study to
select cloud computing strategies.
MB-38
3 - Strategic Customer type Segmentation by AHP Analysis
Masayo Morisada, Ning Li, Kutu Kei, Hong Seung Ko
Customer acquisition and retention are the very important issues for
a company to survive in the global business environment with severe
competitive change. Since current customer type category is complicated by the various classification bases, it is hard to draw up the efficient customer strategy. Therefore, we consider the segmentation with
assigning various customer types to behavior pattern model proposed
by Ko et al. through AHP analysis, in order to be able to draw the
marketing strategy which results in the sales improvement and profits
increase.
4 - Multi-Criteria Decision-Making Solution, Based on
the ANP Approach, Applied to Maintenance’s Supplier Selection Problem
Touhami Lalla Samira
Supplier selection is one of the most important decision problems in
management. Achieving an accurate solution to this issue, the paper
developes a model selection to enable managers of maintenance to different potential supplier selection in a multi-criteria decision making
context. The contribution applies the ANP approach to the different
supplier of the maintenance selection problem in order to help selecting the best compromise alternatives. Determining the selection criteria is the most important task of supplier selection.
MB-38
Monday, 10:30-12:00 - Room 214
Biomass-Based Supply Chains II
Stream: Biomass-Based Supply Chains
Invited session
Chair: Frederic Lantz
1 - Supply Chain Management for the Design of Future
Biorefineries
Sara Giarola, Nilay Shah
This work proposes a multi-period spatially-explicit resourcetechnology network model to drive policies and investments on biorefineries. A MILP model is used to optimise an Organosolv-based
biorefinery supply chain valorising all biomass fractions for the production of biofuels and biomaterials. It minimises the system cost accounting for seasonal biomass supply, geographical availability and
competitive uses, transport logistics, densification technologies, biorefinery/storage capacity and location, product portfolio, biofuels mandates fulfilment. A real-world case study is proposed.
2 - Sensor and Controller on Bio-diesel Fuel Market for
Eco-efficient Policy Making
Noriaki Koide
In this research, authentication systems for waste cooking oil (WCO)
collection and bio-diesel fuel production and mathematical model are
proposed to support the policymaking on environmental issues. Implemented systems visualize the BDF and WCO flow as sensor. We
propose a system model describing the BDF production, human perceived price for WCO collection and BDF use in a city. We discuss a
balance between environmental impact and consumer behavior. Using
this model, we support the policymaking for the collection of WCO
and selling price of BDF while minimizing the impacts as a controller.
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3 - Modelling the European Biofuel Supply Through a
Mixed Integer Programme Linked with an Agricultural Model and a Refining Model
Frederic Lantz
The European Union has an 10% biofuel objective in the automotive
fuel. In this context, we have developped an optimization model to
assess the potential developement of biofuel supply according to the
biomass supply and to the refining activity. Consequently the model is
linked with the European biomass supply model AROPAJ (INRA) and
with the European OURSE refining model (IFPEN). Because the local
potential supply and the transportation costs are an important issue of
this research, we use a disagregated approach. Through this modelling
framework, several scenarios for 2030 are evaluated.
MB-39
Monday, 10:30-12:00 - Room 018
ORAHS V - Outpatient Scheduling
Stream: Health Care Applications
Invited session
Chair: Sally Brailsford
Chair: Weifen Zhuang
1 - Appointment Scheduling in Presence of Seasonal
Demand
Evrim Didem Gunes, Tugba Cayirli, Pinar Dursun
This study investigates appointment systems, as combinations of access rules and appointment rules, that are explicitly designed for dealing with walk-in seasonality. We assume that a portion of capacity is
reserved for walk-in demand while the rest is set as the booking limit
for appointments. Simulation experiments are used to investigate the
effects of environmental factors, such as demand load, probability of
walk-ins and seasonality level. We use the efficient frontier method to
explore the best appointment systems both in terms of micro-level and
macro-level performance measures.
2 - Appointment Scheduling for Medical Diagnostic Facilities
Weifen Zhuang
This paper studies appointment scheduling for medical diagnostic facilities through a Markov Decision Processes (MDP) model. We derive
structural properties of the value function and develop simple bounds
to study the asymptotics. Using the empirical data from the hospital,
we conduct numerical studies to exam the asymptotics and evaluate the
performance of heuristics.
3 - An Adaptive Heuristic with Memory for Scheduling
the Block Appointment System of an Eye Outpatient
Clinic
Ka Yuk Carrie Lin
An eye clinic in a public hospital treats multiple patient classes with
different flow sequences through the multi-phase-multi-server system.
An adaptive scheduling heuristic with memory is proposed for the
block appointment system. A mixed-integer programming model is
formulated. The adaptive heuristic improves an initial schedule iteratively by identifying procedures with large average waiting times and
reassigning their related patient classes to less congested time blocks
probabilistically. The multiple objectives include patient system times,
staff overtime and waiting room congestion.
4 - Case-based learnings for configuring custom packs
Brecht Cardoen, Jeroen Belien, Mario Vanhoucke
A custom pack combines medical disposable items into a single sterile
package that is used for surgical procedures. In this paper we propose
a mathematical programming approach to guide hospitals in developing or reconfiguring their custom packs. A computational experiment,
based on real data of a medium-sized Belgian hospital, compares the
optimized results with the performance of the hospital’s current configuration settings and indicates how to improve future usage.
MB-40
Monday, 10:30-12:00 - Room 019
Production and Supply Chain Design
Stream: Production and the Link with Supply Chain
Invited session
Chair: Jairo R. Montoya-Torres
Chair: Carlos L. Quintero-Araújo
1 - On Supply Chain Network Re-Design after a Corporate Merger
Scott Mason, Mariah Magagnotti, Kelly Sullivan
When a corporate merger or acquisition occurs, it is often desirable to
combine the companies’ supply chains for increased efficiency. During
this challenging task, decisions must be made as to what supply chain
elements should be included in the combined network. We present a
multi-objective model for supply chain network design problems that
considers both cost and network connectivity. We argue that increased
connectivity allows for increased supply chain reliability under uncertain future conditions and examine the cost and benefit of increased
network connectivity in a supply chain.
2 - A Multi-objectives Facility Layout Design Problem for
Thin-film Solar Power Plants
Mei-Shiang Chang, Shih-Ya Liu
A skeleton of designing thin-film solar power plants is a spine layout.
A multi-objectives model is proposed to locate cells on an aisle. The
first objective is to minimize material handling cost. The second one
is to minimize unfitness of locating cells that is measured by weighted
activity relationships. Weighting factors are distances between cells.
Activity relationships are defined by the closeness rating system. A
solar power plant is used to illustrate this model. It is solved by an
immunized ant colony system. Compared with manual planning, our
approach can obtain a dominated result.
3 - A Novel Mathematical Formulation for Minimizing the
Makespan on a Single Batch Processing Machine
Mario Velez-Gallego
A batch processing machine (BPM) can process a set of jobs simultaneously as a batch as long as its capacity is not violated. This research
was motivated by a practical application where a BPM is a bottleneck
and consequently minimizing the makespan is the primary objective.
We propose a novel mathematical formulation and compare its performance against one formulation that is commonly found in the literature. Extensive computational experiments showed that the proposed
formulation performs considerably better that its counterpart with respect to solution quality and computational cost.
4 - Complete Solution of the Extended EOQ Repair and
Waste Disposal Model with Switching Costs
Nadezhda Kozlovskaia, Nadezda Pakhomova, Knut Richter
The EOQ repair and waste disposal problem studied first by Richter,
1997, was extended by Saadany and Jaber, 2008, to the problem of
minimizing the total cost of production, remanufacturing and inventory and, additional switching cost. However, in their paper the authors
did not provide a complete solution to this complex problem. In our
talk such a master solution will be provided. Furthermore, it will be
illustrated how various other remanufacturing problems can be solved
by specifying this master solution.
MB-41
Monday, 10:30-12:00 - Room 216
Lot-Sizing and Related Topics 2
Stream: Lot-Sizing and Related Topics
Invited session
Chair: Mathieu Van Vyve
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IFORS 2014 - Barcelona
MB-43
1 - Computational Analysis of Lower Bounds for Economic Lot Sizing Problems with Remanufacturing
Sharifah Aishah Syed Ali, Kerem Akartunali, Robert Van der
Meer
2 - Strategic Mixed Fleet Management with Electric Vehicles
Jakob Puchinger, Gerhard Hiermann, Pamela Nolz, Richard
Hartl
This talk evaluates different approaches to obtain better lower bounds
for economic lot sizing problems with remanufacturing and separate
setup (ELSRs) and joint setup (ELSRj), which are NP-hard in general. We propose several methods such as valid inequalities, a facility
location reformulation and a shortest path reformulation for this, and
study their theoretical strengths to understand the substructures of both
problems. We also present computational results on a large number of
test data sets available from the literature, and conclude with future
research directions.
Finding an optimal fleet mix of heterogeneous vehicles to fulfill a
single-day demand is a hard problem for itself, which is further complicated by range-restrictions of electric vehicles. In real-world settings,
changing the whole fleet layout each day is not an option, thus changes
in the mix have to be planned over a longer period of time. In our
work we present a mathematical model for the strategic problem. Furthermore we discuss methods to acquire useful approximations of tour
costs for electric, plug-in hybrid and conventional vehicles which can
be used in the strategic planning.
2 - Bounds for a Production-Inventory-Routing Problem
Cristina Requejo, Agostinho Agra
3 - A Heuristic for Locating Electric Vehicle Charging
Stations for Trip Chains
Min Wen, Stefan Ropke
We consider a single item production-inventory-routing problem with
a single producer/supplier and multiple retailers. Inventories are considered both at the producer and at the retailers following a vendor
managed inventory approach, where the supplier monitors the inventory at retailers and decides on the replenishment policy for each retailer. We assume a constant production capacity and consider a single
vehicle. Based on the mathematical formulation we discuss different
relaxations and hybrid heuristics. A computational study is reported.
We present the problem of locating a limited number of electric vehicle
charging stations for a given set of trip chains, each of which consists
of a series of linked short trips and is represented by a sequence of
intervening stops along the trip chain. The objective of this problem
is to maximize the number of trip chains that can be completed by the
electric vehicle without running out of battery. A mixed-integer programming formulation as well as a heuristic for solving this problem
will be presented.
3 - Lagrangian Heuristic Applied to Lot Sizing Problems
on Parallel Machines
Diego Fiorotto, Silvio de Araujo, Raf Jans
4 - Optimization Model and Algorithm for Wireless
Charging Electric Vehicles
Young Jang, Ill Hoe Hwang
The lot-sizing problem is an optimization problem, where the objective is to plan the quantity of items to be produced in order to satisfy
the known demand over the time horizon and minimize the total costs.
This work addresses the problem that involves the production planning
of multiple items in a single stage composed of distinct parallel machines and each item can be produced on any machine. We apply a
Lagrangian heuristic within two hybrid methods to obtain upper and
lower bounds of good quality for this problem.
We introduce a new type of electric transportation system called the
On-line Electric Vehicle. The battery in the OLEV is charged remotely
from power transmitters installed under the road using the innovative
wireless charging technology. The key design parameters of the OLEV
are the battery size and the allocation of the power transmitters. We
construct an optimization model for economically determining the key
design parameters. The wireless-charging has been a big issue in a
greener transportation. This paper introduces a new application of OR
in this emerging technology.
4 - Efficient Approximation Algorithms for the Economic
Lot-Sizing in Continuous Time
Mathieu Van Vyve, Claudio Telha
We consider the continuous-time variant of the classical Economic
Lot-Sizing (ELS) problem. The setup cost, the demand and the holding
cost are all continuous and integrable functions of time. The replenishment decisions are not restricted to be multiples of a base period. Starting from the assumption that certain operations involving the setup and
holding cost functions can be carried out efficiently, we develop approximation scheme that are efficient under an oracle computational
model.
MB-43
Monday, 10:30-12:00 - Room 217
Algorithms and Applications - 2
Stream: Algorithms and Computational Optimization
Invited session
Chair: Gulser Koksal
MB-42
Monday, 10:30-12:00 - Room 215
Electric Vehicles
Stream: Green and Humanitarian Logistics
Invited session
Chair: Jakob Puchinger
1 - A Large Neighborhood Search for the Two-Echelon
VRP: Extensions for Electric Vehicles
Richard Hartl, Ulrich Breunig
A two-tiered setup for the distribution of goods in cities can combine
the advantages of small electric vehicles and conventional large trucks.
In the classical 2EVRP first-level trucks are shipping goods to several
satellites, located in the outskirts. From there smaller city freighters are
used for inner-city deliveries. Keeping trucks out of the centre helps to
reduce congestion and pollution - especially when replaced by electric
vehicles. We show a simple LNS to find good solutions for the problem as well as specific extensions for implementing electric vehicles
on the second level.
1 - A Coal Blending Problem Solved by Column Generation
Daniel De Wolf, Stephane Auray, Yves Smeers
We formulate and solve a real life coal blending problem using a column generation approach. The objective of the model is to prescribe
optimal mixes of coal used to produce coke. The problem is formulated as a mixed integer program. It involves various types of constraints arising out of technical considerations of the blending process.
The model also incorporates integer variables. Three heuristics based
on column generation ideas are proposed to solve this problem. The
heuristics are enabled by the use of dual variables related to the ratio
amounts of each coal.
2 - Waste Sortation in Single Stream Recycling
Joshua Ignatius, Seyed Ahmad Hosseini, Mehdi Sepehri,
Mark Goh
One way to generate a higher recycling rate is to handle materials recovery efficiently. Conventional recycling schemes require the recylates to be "clean", i.e., separated prior to coming into the Material
Recovery Facility (MRF). However, it is inconvenient to pre-sort their
recyclates. To solve this problem, we propose multiple bins to be assigned to each personnel to maximize conveyor belt usage. We model
the unload-and-switch cycle through a 2-nested routing problem. A
numerical example validates the approach.
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IFORS 2014 - Barcelona
3 - In-Depth Features of the CPLEX Optimization Studio
IDE
Frederic Delhoume
4 - Does Collaboration Pay? An investigation for the Domain of Distributed Investment Decisions
Stephan Leitner, Alexander Brauneis, Alexandra Rausch
We will present many features that allow CPLEX Optimization Studio
IDE users to accelerate their model development. Tips and tricks will
be presented related to editing models, viewing results, debugging and
writing custom scripting code and profiling. This presentation will also
introduce the Eclipse environment that CPLEX Optimization Studio is
based on.
We implement a mechanism for coordinating investment decisions,
which is inspired by the idea of the competitive hurdle rate (Baldenius et al., 2007). In addition to Baldenius et al., we add collaboration
among departments, derive an optimal allocation rule for initial capital
expenditures, and model departments as being incompetent to perfectly
forecast measures associated with investment projects. We present results on the impact of the level of collaboration among departments
and different levels of departmental competence in forecasting on our
coordination mechanism’s efficiency.
4 - Product Mix Determination under Uncertainty for Effective Product Management
Gulser Koksal, Nilgun Fesel
In many real life problems, uncertainty is a major complexity for decision makers. A typical example to such a case is the product mix
problem. In this study, we develop a methodology to aid the decision
makers in product mix determination at the strategic level of product
management under uncertainty. The methodology is based on a simulation optimization approach by which scenarios are generated using
a statistical design of experiments approach. This methodology is a
novel and original approach to the best of our knowledge.
MB-44
Monday, 10:30-12:00 - Room 218
Simulation in Management Accounting
and Management Control II
Stream: Simulation in Management Accounting and
Management Control
Invited session
Chair: Stephan Leitner
1 - A Comparative Study between Different Storage Assignment Policies in Automated Storage/Retrieval
Systems
Amina Ouhoud, Amine Hakim Guezzen, Sari Zaki
Automated Storage and Retrieval Systems are warehousing systems
that are used for the storage and retrieval of products in both distribution and production environments. This paper provides an overview of
literature from the past. A comprehensive explanation of the current
state of the art in AS/RS design is provided for a range of issues such
as system configuration, storage assignment policies. Items need to be
put into storage locations before they can be picked to fill customer
orders. A storage assignment method is a set of rules which are used
to assign items to storage locations.
2 - Bridging the Gap in Transport Project Evaluation:
Accounting for the Inaccuracies in Demand Forecasts and Construction Costs Estimations
Kim Salling, Steen Leleur
For decades researchers have claimed that demand forecasts and construction costs estimations are assigned with large degrees of uncertainty, commonly referred to as Optimism Bias. A severe consequence
is that ex-ante socio-economic evaluation of infrastructure projects becomes inaccurate and can lead to unsatisfactory investment decisions.
Thus there is a need for better risk assessment and decision support,
which is addressed by the recently developed UNITE-DSS model. It
is argued that this simulation-based model can offer decision makers
new and better ways to deal with risk assessment.
3 - Transfer Pricing - Impact of the Negotiation Duration
Arno Karrer
In this paper we analyze the impact of the negotiation duration on the
consolidated profit and transfer price. A simulation is applied to show
potential results implied by a reduced negotiation process. In particular, intracompany profit centers negotiate with each other or independent parties on an external market, which is technologically as well as
demand independent. The identification of potential targets for business activities is affected by symmetric or asymmetric imperfect market information and the number of negotiation steps permitted to the
parties.
38
MB-45
Monday, 10:30-12:00 - Room 219
Stochastic Programming Models and
Algorithms
Stream: Stochastic Programming
Invited session
Chair: Francois Louveaux
1 - Stochastic Programs with Decision Dependent Probabilities
Lars Hellemo, Asgeir Tomasgard, Paul I. Barton
We present taxonomy of stochastic programming with decision dependent uncertainty and discuss modelling and applications in mathematical programming. Direct and indirect manipulations of probability
distributions via decision variables are presented. We formulate twostage models where prior probabilities are distorted through an affine
transformation, or combined using a convex combination of several
probability distributions. Additionally, we present models where the
probability distributions are either incorporated using either the exact
expression or a rational approximation.
2 - BFC-SDC Algorithm for Solving Multistage Mixed 01 Problems under Risk Averse Time Consistency
Stochastic Dominance Constraints
María Merino, Laureano Fernando Escudero, María Araceli
Garín, Gloria Perez
We extend to the multistage case a mixture of two recent risk averse
measures for two-stage stochastic mixed 0-1 problems, such that an
objective function is maximized in a feasible domain also constrained
by time consistent first- and second-order Stochastic Dominance Constraints integer-recourse. We present the BFC-SDC decomposition
algorithm, where a special treatment is given to cross scenario constraints. Computational experience is reported comparing risk neutral
and averse strategies as well as the performance of the decomposition
algorithm versus plain use of an MIP solver.
3 - BFC and other Decomposition Schemes in SMILPs
Gerardo Perez Valdes, Adela Pages Bernaus, Asgeir
Tomasgard
We apply a Branch and Fix Coordination algorithm in a parallel setting
to solve specially large Stochastic Mixed-Integer Programs in the context of energy infrastructure investment and operation. To handle large
instances, we use the decomposition already required by the BFC into
a few other schemes, like the L-shaped Method, to improve memory
use, solve LPs faster, and improve the bounding throughout the BFC
process. Preliminary results show that, with a careful selection of the
subproblems, this can perform better when compared to solving the
original SMILPs with commercial solvers.
4 - On Parallelizing Decomposition Algorithms for Solving Stochastic Multistage Mixed 0-1 Problems
Unai Aldasoro, Laureano Fernando Escudero, María Merino,
Gloria Perez
Parallel versions of two risk-neutral serial decomposition algorithms
for solving large-scale stochastic multistage mixed 0-1 problems are
presented. The first, BFC (Branch-and-Fix Coordination), is an exact one and the second, SDP (Stochastic Dynamic Programming) is
IFORS 2014 - Barcelona
a metaheuristic intended for much larger instances (millions of constraints and variables). Two message passing parallelization paradigms
are considered, namely inner and outer parallelization. Computational
results show significant reductions in computing time by using the parallelization paradigms versus the serial versions.
MC-50
Monday, 12:15-13:45
MC-50
Monday, 12:15-13:45 - Plenaries room
Plenary Session M. Brandeau
Stream: Plenary Sessions
Plenary session
Chair: Elena Fernandez
1 - Operations Research and Health Policy: Models that
Can Make a Difference
Margaret L. Brandeau
When deciding which programs to invest in, public health decision
makers face a number of challenges, including limited resources to invest among many potential programs, incomplete information about
the potential effects of programs, and objectives that include not only
health maximization but social, political, and cultural considerations.
OR-based modeling can play a key role in informing such decisions:
by providing a structured framework that uses the best available evidence, imperfect as it may be, and that captures relevant uncertainties,
complexities, and interactions, OR-based models can be used to evaluate the potential impact of alternative public health programs. This
talk describes modeling efforts in which OR has played and can play
a role in informing public health decision making. We conclude with
a discussion of useful lessons for OR modelers who wish to work on
health-related and policy-related problems.
39
MD-01
IFORS 2014 - Barcelona
Monday, 14:00-15:30
MD-01
Monday, 14:00-15:30 - Room 118
Delays and Disruptions
Stream: Railway and Metro Transportation
Invited session
Chair: Marie Schmidt
1 - Modelling Delay Propagation in Railway Networks
Fabian Kirchhoff
We want to determine delay distribution functions analytically from
given source delays. For this purpose, we consider a network that represents the relations between feeder and connection lines. Generally,
the calculation of propagated delays requires a topological sorting of
arrival and departure events and cannot be applied if the network contains cycles. We use an iterative method to approximate the long-run
delay distributions in those cycles. The objective of this talk is to investigate the impact of this approach on the limiting distributions.
2 - An Iterative Framework for Railway Disruption Management
Twan Dollevoet
Railway systems face many unexpected events that render the planned
timetable, rolling stock schedule, and crew schedule infeasible. Current scientific approaches to deal with such disruptions tend to focus
on one of the resources individually. However, the resulting resource
schedules are highly interdependent. Within the ON-TIME project, we
developed an iterative framework that reschedules the three resources
sequentially. We present results for several real-world instances from
Netherlands Railways and show that feasible solutions can be obtained
within minutes.
3 - OR Models for Disruption Management at Netherlands Railways
Dennis Huisman
Every day, there are several major disruptions on the Dutch railway
network. During a major disruption, one or more railway lines are
blocked for a few hours. In the coming years, Netherlands Railways
(NS) will introduce advanced OR models and algorithms to reschedule the timetable, rolling stock, and crew in real-time. In this talk, we
will discuss the first results, our implementation strategy and remaining challenges.
4 - Route Choice in Case of Disruptions
Paul Bouman, Marie Schmidt, Leo Kroon, Anita Schöbel
When passengers in a public transport system want to travel while there
is a disruption, they face a dilemma: should they wait and hope that
the disruption is over soon, or should they take a detour? Such a situation can be seen as a online decision problem, because as soon as the
passengers know when the disruption is exactly over, the decision is
trivial. We analyze this problem for a regular connection and a detour
connection with a periodic timetable. We then compare the worst-case
(robustness), competitiveness and expected values of arrival for different decision strategies.
1 - The Multi-Zone Multi-Trip Vehicle Routing Problem
with Separate Delivery and Collection
Andrea Bettinelli, Teodor Crainic, Daniele Vigo
The multi-zone multi-trip VRP with separate delivery and collection
(MTMZ-VRPPD) arises in the context of the planning operations of
two-tiered City Logistics systems. It is an extension of the VRPTW
involving both designing and assigning routes to vehicles within time
synchronization restrictions. Each route is made up of a sequence of
supply-point visits, each followed by a trip servicing first customerdelivery demands and then customer-pickup demands in the zones of
the respective supply-points. We propose an exact branch-and-cut-andprice method to solve MTMZ-VRPPD to optimality.
2 - A GRASP Algorithm with Path Relinking for the
Multi-depot Location Routing Problem with Stochastic Customers
Yannis Marinakis, Magdalene Marinaki
In this paper, a Stochastic Location Routing Problem is formulated
using a number of capacitated depots, each one having one vehicle
with no capacities restriction. We use a two phase algorithm based on
GRASP for solving the problem. In the first phase, the open depots
are determined and in the second phase, an a priori route is constructed
for each one of the depots. The cost is the sum of the set up cost of
the depots and the expected length of the routes. Different scenarios
are examined in which each customer has either a homogeneous or a
heterogeneous probability of requiring a visit.
3 - Waste Collection on Arcs — the Seixal Case Study
João Janela, Cândida Mourão, Leonor S.Pinto
The household waste collection problem in the Portuguese municipality of Seixal may be studied via an arc routing problem with some
side constraints, which is known to be NP-hard. This work uses a
GIS (Geographic Information System), available at the municipality,
for the input/output phases and some heuristics specifically developed
for the case study. Among the referred side constraints we try to find
vehicle trips that are: balanced; connected and compact. This project
was partially supported by National Funding from FCT (PTDC/ECEGES/121406; PEsT-OE/EGE/UI0491; PEsT-OE/MAT/UI0152.
4 - Beyond Arc Routing
Dmitry Krushinsky, Tom Van Woensel
While the Arc Routing Problem (ARP) focuses on minimising the
length (cost) of tours, several other goals take place in practice. Including them into the already complex ARP makes it unsolvable.
Yet, the way of traversing a given ARP tour is often non-unique,
which provides possibilities for optimisation. We show that such postoptimisation of ARP solutions is a non-trivial but practically tractable
problem and consider several realistic objectives, such as serving prioritised arcs earlier or minimising the expected additional costs in case
the (stochastic) demand exceeds the vehicle capacity.
MD-03
Monday, 14:00-15:30 - Room 001
Robust and Integrated Models for Airline
Scheduling
Stream: Aviation
Invited session
Chair: Luis Cadarso
1 - Comparing Delay Prediction Models for Robust Airline Resource Scheduling and Optimization
Lucian Ionescu, Natalia Kliewer
MD-02
Monday, 14:00-15:30 - Room 111
Urban Logistics Problems
Stream: Vehicle Routing
Invited session
Chair: Andrea Bettinelli
40
Since cost-optimized airline resource schedules are not delay tolerant,
sophisticated optimization techniques for robust scheduling have been
developed in recent years. However, all these approaches depend on
assumptions made concerning primary delay occurrences. In this context, we discuss different delay prediction models based on historical
delay data analysis. Eventually, we measure the impact of competing
prediction models on the scheduling process. The results show in how
far assumptions on delay occurrences potentially determine subsequent
scheduling decisions.
IFORS 2014 - Barcelona
2 - A Heuristic Algorithm for Personalized Integrated
Cockpit Scheduling
Atoosa Kasirzadeh, Mohammed Saddoune, Francois Soumis
We present a set-covering formulation and an iterative heuristic algorithm for personalized integrated cockpit pairing and assignment problems. The objective is to have as many similar pairings as possible
between pilots and co-pilots to increase the schedules robustness, even
if pilots and co-pilots schedules are different to satisfy their preferences. We use a solution approach based on column generation for this
problem. The computational results provided are based on a major US
carrier data set.
3 - A Bi-Dynamic Constraint Aggregation Based Solution Approach for Crew Pairing Problem
Mohammed Saddoune, Francois Soumis
The crew pairing problem consists of determining a minimum cost set
of feasible pairings such that each flight is covered exactly once and
side constraints are satisfied. Recently, Saddoune et al. (2013) showed
that the rolling horizon approach produced better solutions compared
to the three-phase approach. To improve the quality of the solutions,
we develop, in this paper, a bi-dynamic constraint aggregation method
that exploits a neighborhood structure when generating columns (pairings) in the column generation method. All tests are based on real data
provided by a major airline.
4 - Integrated Airline Scheduling under Competition: the
Entry of the High-speed Rail
Luis Cadarso, Vikrant Vaze, Cynthia Barnhart, Ángel Marín
Airlines and high-speed rail are increasingly competing for passengers, which affects the number of served passengers and revenues. We
develop an approach that generates airline schedules capturing the impacts of airlines’ decisions on passenger demand. We evaluate scenarios involving the entry of high-speed rail, and validate our results using
out of sample data from a market that had an entry of high-speed rail
in the past. Contingent on the offered attributes, the model predicts the
optimal decisions to retain passengers and to maximize profits.
MD-05
3 - Mathematical Model Applied to Bio-Diesel Supply
Chains in Colombia
Javier Arturo Orjuela Castro, Johan Alexander Aranda Pinilla,
Milton Herrera
This paper presents a mathematical-programming model for structuring and integration of strategic decision-making in oil-palm bio-diesel
production in Colombia. The model includes four stages of the supply
chain (planting, extraction, bio-refining and mixing) and applies to four
geographical areas. The model establishes a distribution plan for oil,
bio-diesel and diesel along the supply chain. Production and inventory
plans are included with an increase in the capacity of bio-refineries that
minimizes total cost. Results show the potential behavior of the chain,
particularly regarding soil.
4 - Post-Sales Network Design of a Household Appliances Manufacturer
F. Tevhide Altekin, Ezgi Ayli, Guvenc Sahin
In this paper, we analyze the post-sales network of a household appliances manufacturer providing repair and refurbishment services for
its products. The post-sales network design problem under consideration involves determining the warehouse locations for the spare parts
as well as their flows from manufacturing sites and to existing repair
centers. A mixed-integer programming based solution method is proposed. The efficiency and effectiveness of the proposed approach is
illustrated using a realistic case study from Turkey.
MD-05
Monday, 14:00-15:30 - Room 002
Supply Chain Management in Petroleum
Industry
Stream: Petroleum Logistics
Invited session
Chair: Anastasiya Karalkova
MD-04
Monday, 14:00-15:30 - Room 119
Supply Chain Design 1
Stream: Supply Chain Management
Invited session
Chair: F. Tevhide Altekin
1 - Design of a Collaborative Distribution Network
Xin Tang, Fabien Lehuédé, Olivier Péton
We present a case study of horizontal collaboration between several
competing firms in the same geographic area. The companies have
common customers and currently ship their products independently
from each other. They aim at reducing their distribution costs by pooling shipments. A first phase of the project is to locate several distribution centers in the territory, define distribution rules with regards to
flows, integrating their seasonality. We model this distribution network
design problem with a linear integer program and present results obtained with a solver.
2 - Supply Chain Network Design with Uncertain Demand
Matias Schuster, Jean-Sébastien Tancrez
Demand uncertainty is a concern and difficulty of primary importance
for companies. In particular, it has an important impact on the optimal design of a supply chain network. For example, demand uncertainty forces to store products in warehouses close to customers (safety
stocks), in order to react quickly to variations and meet customer expectations. In this work, we integrate the impact of demand variability
in a location-inventory model. Extending previous results, we propose
a new mathematical formulation to consider safety stocks and study
their impact on the supply chain network design.
1 - The Value of Strategic Flexibility in Gas Transport Infrastructure Investments
Katerina Shaton
Exploration interests of petroleum companies move further to the
North of the Norwegian Sea and the Barents Sea. It raises a need for a
gas transport solution in the area. In the paper, the choice between an
LNG and a pipeline solution is discussed. A Real Options framework
is used to analyse the trade-off between the destination flexibility of the
LNG solution and strategic flexibility provided by the pre-investment
in excess pipeline capacity. An approach to identify the value of strategic flexibility is proposed and the value is estimated for the case of a
potential Barents Sea pipeline.
2 - Modal Split in Offshore Upstream Supply Chain under the Objective of Emissions Minimization
Ellen Karoline Norlund, Irina Gribkovskaia
We assess modal split in the offshore upstream supply chain of cargo
from vendors to supply bases along the Norwegian coast under the
objective of emissions minimization. To gain insight into drivers for
modal split between road and sea transport from the shipper’s perspective a multi-period mixed integer optimization model is formulated.
The model is used to study how different demands, inventory policies
at bases and shipper commitments to sea transport affect modal split.
The results show that commitments and inventories are major drivers
towards environmental friendly sea transport.
3 - Preparedness Logistics for Arctic Offshore Operations
Peter Schütz
One of the main challenges of industrial operations in Arctic waters
is remoteness. The long distances to the supply bases not only affect
regular operations, but also preparedness logistics are affected. We
present a model for the problem of designing a preparedness logistics
system for offshore operations. The solution to the problem aims at
minimizing the cost of the resources assigned to the preparedness system while satisfying all preparedness requirements and accounting for
resources that can be used to serve several preparedness tasks.
41
MD-06
IFORS 2014 - Barcelona
4 - Industry-wide Information Sharing in Oil and Gas Upstream Supply Chain: Analysis of Potential Impacts
Anastasiya Karalkova
Tightly interlinked activities, uncertainty and dynamic environment of
upstream oil and gas supply chain raise the needs of information sharing among the companies. However, information sharing is a controversial issue. Available information may be beneficial for one of
the parties, and at the same time it may benefit less or detriment another party in the supply chain. In this paper we use multi-stakeholder
framework to analyze the potential impacts of industry-wide event information sharing hub in upstream oil and gas supply chain.
MD-06
Monday, 14:00-15:30 - Room 211
Behavioral Research on City Logistics
Stream: City Logistics and Freight Demand Modeling
Invited session
Chair: Cara Wang
1 - Freight Deliveries Directly Generated by Residential
Units: An Analysis with the 2009 NHTS Data
Cara Wang, Yiwei Zhou
Using the 2009 U.S. National Household Travel Survey (NHTS) data,
this paper studies truck deliveries generated by residential units. A
count data model is used to identify the impacts of influential factors
such as housing density, type of house and house ownership. A closer
examination at the state level further discloses the spatial variation in
their relationship. Such a study will supplement city logistics studies that traditionally focus on business behaviors, help reconstruct the
complete picture of freight activities in urban areas.
2 - A Reference Model for Determining Road Toll
Charges
Mario Dobrovnik, Sebastian Kummer
In recent years, numerous European countries have introduced tolls
as a means of traffic guidance and control. These policy decisions
have significantly affected entire economic regions as well as individual companies along the supply chain. For transport companies (especially for carriers), passing the additionally incurred cost to the (final)
customer as reasonably as possible therefore is of utmost importance.
We propose a reference model which involves solving a network problem based on effective toll distances that allows for determining the
additional toll costs for individual shipments.
3 - Policy-Sensitive Vehicle Routing: An Optimization
Approach for Evaluating Differentiated Transport Policy Measures
Gernot Liedtke, Stefan Schröder
We develop a carrier model and couple it with a transport simulation
to analyze the impacts of congestion and differentiated policy measures. The model is formalized as rich vehicle routing problem and
solved with a meta-heuristic based on a large neighborhood search and
a time-dependent least cost path calculator. We benchmark the algorithm and conduct sensitivity studies varying attributes of the problem
and the traffic system. In a case study, we show that the model reacts
sensitively to congestion and fine-tuned policy measures differentiating between vehicle-type, area and time-of-day.
4 - Correlation Between Speeds in a Congested Road
Network in the City of London
Saeideh D. Nasiri
This study uses real traffic data, from the City of London, to explore
temporal and spatial correlations between travel speeds in a congested
road network. It is shown that, in contrast with results found in other
studies on non-congested networks, the first-order Markovian property
does not hold for spatial correlations. Indeed, for our data set the spatial correlations are still significant for roads up to twenty links apart.
If one analyses the correlations using principal component analysis, it
turns out that only six components are needed to explain over 80% of
the spatial variation.
MD-07
Monday, 14:00-15:30 - Room 003
Modelling the German "Energiewende"
(Energy Transformation)
Stream: Equilibrium Problems in Energy
Invited session
Chair: Daniel Huppmann
1 - How will Electric Vehicles Impact the Spot Market
Prices for Electricity?
Philipp Hanemann, Thomas Bruckner
Depending on how electric vehicles are charged they can impede or
support the integration of renewable energy resources into the energy
system. For reducing CO2-emissions, the German government has set
ambitious goals for increasing the share of electric vehicles up to 6
Mio in 2030. If all of them are charged uncontrolled, the peak load
will increase. So will the prices. In contrast, controlled charging will
smooth out price fluctuations. These will be further smoothed by vehicle to grid charging. Additionally, fossil fuelled power plants might be
substituted.
2 - Carbon Emission Effects of the Power-to-Heat Technology in Germany
Diana Böttger
Power-to-heat plants could be used for the cost efficient provision of
negative secondary control power. Their effects on carbon emissions of
the German power system are evaluated with a power market model.
The model is of mixed-integer type to account for techno-economic
characteristics of thermal power plants. The quantification of carbon
emissions in a German power system with and without power-to-heat
plants shows that the technology could help to reduce carbon emissions
in the power sector.
3 - Integrated Modelling of Reserve and Spot Electricity
Markets in Systems with a Large Share of Variable
Renewable Energy
André Ortner
In the light of an increased penetration of variable renewable electricity
it is expected that due to forecast errors the amount of reserve capacity to be procured will increase as well. It is of interest how much
costs could arise from this provision and how it translates into market
prices given a certain market design. This paper presents a mixed complementary problem considering the economic equilibrium of spot and
reserve markets under the market design implemented in Germany.
4 - National-Strategic Investment in European Electricity
Transmission Capacity
Daniel Huppmann, Jonas Egerer
The transformation of the European energy system requires substantial
investment in (cross-border) transmission capacity to efficiently integrate renewables. We investigate the impact of national regulators deciding on network expansion strategically, with the aim of maximizing
welfare in their jurisdiction. Using a three-stage equilibrium model,
we identify several Nash equilibria and quantify the welfare loss compared to the system-optimal investment. A compensation mechanism
can partly alleviate the problem and yield a second-best equilibrium.
MD-08
Monday, 14:00-15:30 - Room 120
Sustainable Management and Climate
Change
Stream: Energy Economics, Environmental Management and Multicriteria Decision Making
Invited session
Chair: Marcus Brandenburg
42
IFORS 2014 - Barcelona
1 - Geoengineering: Is it a Valuable Option for Climate
Policy?
Olivier Bahn, Marc Chesney, Jonathan Gheyssens, Anca
Pana, Reto Knutti
We investigate geoengineering as a possible substitute for adaptation
and mitigation to address climate change. With the help of an integrated assessment model, we distinguish between the effects of solar
radiation management (SRM) on atmospheric temperature levels and
its side-effects on ecosystems. To address the uncertainty regarding the
magnitude of side-effects, we rely on a distributional analysis. Our results indicate that mitigation and adaptation are the preferred strategies.
We then discuss additional concerns with SRM that further reduce its
feasibility.
2 - Baseline Setting Problems of the Offset Mechanisms
in the International Scheme for Climate Change
Haruo Imai
There are several offset schemes (both existing and proposed) in the
international negotiation over climate change for which baseline emission level must be determined. The major obstacle for these is the
uncertainty and asymmetric information inherent in the baseline levels,
and the trade-off between environmental integrity and transaction costs
involved. With a help of multi-objective optimization, we compare
several proposals via generalized (self-selection) models and show that
the standardization proposed could perform very well if the transaction
costs are properly accounted for.
3 - Dynamic Capabilities and Policies for Sustainable
Supply Chain Management — a System Dynamics
Approach
Marcus Brandenburg, Daniel Thiel, Stefan Seuring
The link between sustainable supply chain management and dynamic
capabilities has been conceptualized and operationalized by adequate
policies. The proposed paper complements this conceptual and empirical research by quantitative modeling, which is based on the conceptual
framework and related literature. A system dynamics model, which reflects the high complexity of different constructs and their dynamic interplay, is designed to assess the behavior of supply chains with regard
to triggers and performance outcomes of sustainability. The poultry
supply chain is chosen as application area.
4 - Lessons in Operations Management from State of
Victoria’s Department of Education Bushfire Infrastructure Improvement Program
Maria Cherilyn Marquez, Leorey Marquez
Following the devastation from Victoria’s February 2009 bushfires, the
state government issued directives requiring public buildings be designed and built so as to withstand the attack of a bushfire. This paper
presents the multi-disciplinary approach to project management and
decision-making processes that were applied to effectively deliver the
Department of Education’s bushfire program in 2011. It discusses the
experiences and knowledge gained for future planning and design of
schools and formulation of policies on risk mitigation and adaptation
of schools in bushfire-prone areas.
MD-10
This paper proves the relation between a given non-deterministic discrete decision process (nd-ddp) and subclasses of non-deterministic
monotone sequential decision process (nd-msdp) which is a finite automaton with a cost function. We show some strong representation
theorems for the subclasses of the nd-msdp. Each strong representation theorem provides a necessary and sufficient condition for the existence of the subclass of nd-msdp with the same set of feasible policies
and the same cost value for every feasible policy as the given process
nd-ddp.
2 - Heuristics for the Optimal Routing of Customers in
Queueing Systems with Heterogeneous Service Stations
Rob Shone, Vincent Knight, Paul Harper, Janet Williams
The problem of routing customers to parallel heterogeneous service
stations in such a way as to optimise a queueing system’s performance
is known to be one for which optimal policies are difficult to characterise. The application of dynamic programming is impractical in
problems of realistic size, and there is a need for effective heuristics
to be developed. Some possible approaches to the problem include the
development of indices for the stations similar to the Gittins indices for
multi-armed bandit problems, and simulation-based methods including
those based on artificial neural networks.
3 - Primal Function and Dual Function Through Conjugation
Yutaka Kimura, Seiichi Iwamoto
For a multi-stage division problem, we consider a duality between primal function and its dual function through conjugate function. We
derive a duality between both the functions, which is called a primaldual inequality. This is a dynamic generalization of Young’s inequality.
Moreover, both optimal values of (primal and dual) problems are characterized by the first element in the optimal solutions. In particular, for
the multi-stage division problem with quadratic criterion, we show that
the Fibonacci complementary equality holds.
4 - A Comparison of Methods to Evaluate the Probability
of Excessive Waiting in the M(t)/G/s(t)+G queue
Stefan Creemers, Mieke Defraeye, Inneke Van Nieuwenhuyse
The M(t)/G/s(t)+G queue (with a time-varying arrival rate and general
distributions for the service and abandonment processes) is highly relevant in practice, though it is notoriously difficult to analyze. Our computational experiment compares methods for determining the timedependent probability of excessive waiting in an M(t)/G/s(t)+G queue
with an exhaustive service discipline. The comparison includes two
simulation-based approaches, the Modified Offered Load (MOL) approximation, and a randomization method. We investigate their accuracy and computational requirements.
MD-10
Monday, 14:00-15:30 - Room 122
Robust and Stochastic Models for
Electricity Systems
Stream: Optimization Models and Algorithms in Energy
Industry
Invited session
MD-09
Chair: Alexandre Street
Chair: Rodrigo Moreno
Stochastic and Deterministic Dynamic
Programming and its Applications 1
1 - Contracting Strategies for Generation Companies
with Ambiguity Aversion on Spot Price Distribution
Bruno Fanzeres, Alexandre Street, Luiz-Augusto Barroso
Monday, 14:00-15:30 - Room 121
Stream: Dynamical Systems and Mathematical Modelling in OR
Invited session
Chair: Yukihiro Maruyama
1 - Strong
Representation
Theorems
for
Deterministic Sequential Decision Processes
Yukihiro Maruyama
Non-
The typical approach to obtain contracting strategies for power companies is to simulate paths for the uncertainties and optimize the portfolio
to maximize some measure of value. However, spot price simulation
is a challenge due to its high dependence on parameters that are difficult to predict. Therefore, decisions are usually made under ambiguity,
i.e., whenever the agent is aware that the scenarios represent only an
approximation of the true underlying distribution. In this work, robust optimization is used to treat ambiguity in the optimal contracting
strategy of renewable companies.
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MD-11
IFORS 2014 - Barcelona
2 - Two-Stage Robust Optimization Models for Power
System Operation and Planning under Joint Generation and Transmission Security Criteria
Alexandre Street, Alexandre Moreira, José Manuel Arroyo
Recent major blackouts have been a driving force to make power system reliability a subject of worldwide research. In this work, the main
objective is to incorporate the joint generation and transmission general security criterion n-K in optimization models for power systems
operation and planning. Our main contributions are: two-stage robust
models to consider n-K security criteria and load variability in power
systems operation and planning, solution methodologies that finitely
converges to global optimal solution, and valid constraints to boost
computational efficiency.
3 - CVaR Constrained Planning of Renewable Generation with Consideration of System Inertial Response,
Reserve Services and Demand Participation
Rodrigo Moreno, Andres Inzunza, Alejandro Bernales, Hugh
Rudnick
Although higher penetration of renewables may increase the mean cost
of generation investment and operation, recent studies have demonstrated benefits of renewables in terms of the reduction in risks on
system operation cost (e.g., less exposure to volatile fuel prices). In
this context, we present an optimisation model that determines robust
mix of generation technologies, including renewables, by minimising
the mean cost of investment and operation while constraining risk exposure through CVaR. The model considers effects on system inertial
response and reserves, and demand participation.
4 - Electricity Market Equilibrium Models — A Robust
Solution Approach
Emre Çelebi
This presentation will examine the market equilibrium models for
competitive electricity markets using a robust optimization approach.
We cast our models as monotone and affine variational inequality problems where transmission network constraints and intermittent suppliers
(e.g. wind) with uncertainty data sets are considered. For linear priceelastic demand response case, we have obtained a "robust" equilibrium
solution. We have illustrated the models and solution approach using an electric power market model of Hobbs (2001) and realistic data
from Turkish electricity market.
MD-11
The design of efficient Home Care Services represents a societal and
economic challenge. Home Care services play a crucial role in reducing the hospitalization costs due to the increase of chronic diseases of
elderly people. At the same time they represent a means to improve
the patients’ quality of life. Recently, mathematical models that jointly
address assignment, scheduling, and routing decisions have been proposed. However, their solution is not affordable for big instances. In
this study, we propose a series of two-phase decomposition approaches
and we test them on real instances.
3 - Network Design under Multi-Source Uncertainty
Martin Tieves
In the network power consumption problem, the size oft communication flows is determined by two factors: the initial traffic volume and
a (potential) compression rate. Data on both factors is inherently uncertain in practice. We show how an extension of Gamma-Robustness,
i.e., multi-source uncertainty, can be included in a MIP formulation of
this problem, taking account of these uncertainties. We illustrate and
evaluate the concept and the resulting solutions. A comparison with
solutions obtained by the Gamma-Robustness concept concludes this
talk.
4 - The Job-Scheduling and Tool Switching Problem
Martine Labbé, Daniele Catanzaro, Luís Gouveia
We investigate the Job Sequencing and Tool Switching Problem (JSTSP), a NP-hard combinatorial optimization problem arising from
manufacturing systems. Starting from the results described in Tang
and Denardo (1987), Crama et al. (1994) and Laporte et al. (2004),
we develop three new integer linear programming formulations for the
problem that are provably better than the alternative ones currently described in the literature. Our results suggest new insights on the combinatorics of the problem and provides new directions for the development of future exact solution approaches.
MD-12
Monday, 14:00-15:30 - Room 004
Graphs and Networks III
Stream: Graphs and Networks
Invited session
Chair: Reinhardt Euler
Monday, 14:00-15:30 - Room 113
Impact of Combinatorial Optimization on
Solving Challenging Applications
Stream: Combinatorial Optimization
Invited session
Chair: Maria Grazia Scutellà
1 - A Branch and Benders Cut Approach for Nonlinear
Location-Design in Green Wireless Local Area Networks
Maria Grazia Scutellà, Bernard Gendron, Rosario G.
Garroppo, Gianfranco Nencioni, Luca Tavanti
We study a problem arising in the design of Green (energy-saving)
Wireless Local Area networks (GWLANs). Decisions on the location of access points, on the assignment of user terminals to the access
points, and on the assignment of a power level to each opened access
point, have to be taken simultaneously. The power level assigned to
an access point affects, in a nonlinear way, the capacity of the connections between the access point and the user terminals assigned to
it. We model the problem as an integer program with nonlinear constraints and solve it by a Branch and Benders Cut approach.
2 - Decomposition Approaches to Assignment and
Routing Problems in Home Health Care Services
Paola Cappanera, Semih Yalcindag, Andrea Matta, Maria
Grazia Scutellà, Evren Sahin
44
1 - Pareto-Optimal Many-to-Many-Matchings: Complexity and Integer Programs
Yiannis Mourtos, Katarina Cechlarova, Pavlos Eirinakis,
Tamas Fleiner, Dimitrios Magos, Eva Potpinkova
We examine Pareto optimality in the context of a many-to-many
matching market involving two finite sets A and C. Each member of A
has preferences over a set of subsets of C that is downward closed and
each member of C has a quota. We provide necessary and sufficient
conditions for a such a matching to be Pareto optimal (POM) and a
polytime recognition algorithm. A generalized version of serial dictatorship obtains any POM, whereas finding a minimum or a maximum
cardinality POM is NP-complete. Last, we discuss integer programming formulations of POM along with its relation to matroid kernels.
2 - On the Polytope of Closed Subsets of Directed
Graphs and its Extension to Ordinal Transportation
Pavlos Eirinakis, Dimitrios Magos, Yiannis Mourtos
For a directed acyclic graph G(V,A), a subset C of V is closed if A
contains no arc from a node not in C to a node in C. We examine the
polytope describing the set of closed subsets of such a graph. Specifically, we show that the polytope is full-dimensional and identify all
families of facet-inducing constraints, hence providing a minimal linear description. Our analysis is then extended to non-acyclic graphs.
Moreover, it is utilized in the context of the Stable Allocation (or Ordinal Transportation) and the Stable Flow problem to obtain their first
linear description, which is also minimal.
IFORS 2014 - Barcelona
3 - Hybrid Approaches for the Multi-Index Assignment
Problem
Stathis Plitsos, Dimitrios Magos, Yiannis Mourtos
We study the (k,s)-assignment problem as a unified framework for the
axial and planar assignment problems. The idea is to intensify the combined use of Integer and Constraint Programming methods, while also
encompassing effective heuristics. In that direction, we propose an integrated solver that combines feasibility pump and tabu search with
constraint propagation and problem-specific cutting planes. After employing these tools at several nodes of a Branch & Cut tree, while also
using problem-specific branching schemes, we discuss computational
findings on large-scale instances.
4 - Modeling the Geometry of the Endoplasmic Reticulum Network
Reinhardt Euler, Laurent Lemarchand, Imogen Sparkes,
Congping Lin
We study the network geometry of the endoplasmic reticulum by graph
theoretical and integer programming models. We determine plane
graphs of minimal total edge length satisfying degree and angle constraints and we show that the optimal graphs are close to the ER network geometry. We use a binary linear program, that iteratively constructs an optimal solution, and a linear program, that iteratively exploits cutting planes. All formulations were tested on real-life and randomly generated cases. The cutting plane approach turns out to be
particularly efficient for the real-life testcases.
MD-14
4 - Single Machine Just-in-Time Scheduling Problems
with Two Competing Agents
Gur Mosheiov, Enrique (Tzvi) Gerstl
In the single-machine two-agent problem studied here, the goal is to
find a joint schedule that minimizes the total deviation of the job completion times of the first agent from a common due-date, subject to an
upper bound on the maximum deviation of job completion times of the
second agent. The problem is shown to be NP-hard in the ordinary
sense even for a non-restrictive due-date. For the case of a restrictive
due-date, a faster dynamic program is presented. We also study the
multi-agent case, which is proved to be strongly NP-hard. A heuristic
is introduced and tested.
MD-14
Monday, 14:00-15:30 - Room 124
Other Real and General Problems in
Production Scheduling
Stream: Realistic Production Scheduling
Invited session
Chair: Jacques Teghem
MD-13
Monday, 14:00-15:30 - Room 123
Single Machine Scheduling
Stream: Scheduling
Invited session
Chair: Gur Mosheiov
1 - Genetic Algorithm for a Two-Agent Scheduling Problem with Position-Dependent Learning Effects
Jin Young Choi
We consider a two-agent single-machine scheduling problem with linear job-dependent position-based learning effects. Specifically, two
agents competing for the usage of the common single machine have
their own objectives to minimize the sum of the weighted completion
times and to limit the makespan within a given upper bound, respectively. Moreover, the job processing times are determined by the learning effects and the processing sequence. To solve this problem, we
developed an efficient genetic algorithm to find a near optimal solution
and verified its performance by a numerical experiment.
2 - Minimization of the Tool Switches Problem - Polynomial Algorithm for a Special Case
Horacio Yanasse
The minimization of the tool switches problem consists in finding a
sequence to process a set of jobs that minimizes the total number of
required tool switches. Each job requires a set of tools to be in the
machine in order to be processed. If a tool required to process a job is
not in the machine, it must be placed in the tool magazine that has limited capacity. Therefore, tool switches must occur. The general case
of MTSP is NP-Hard. We present a polynomial algorithm for a special
case of the problem, where each one of the jobs requires at most two
different tools.
3 - Due Date Quotation in Dynamic Single Machine Environment with Family Setups under Stochastic Job
Characteristics
Zehra Duzgit, Ali Tamer Unal
We consider the due date quotation problem in dynamic single machine environment with family setups. A due date is to be assigned to
jobs immediately at arrival. Two conflicting objectives are to be minimized: average quoted lead time and average tardiness. A two phase
methodology is proposed. The first phase generates a batching configuration for families based on expected workload, before job arrivals.
In the second phase, due dates are assigned. For each phase, an MIP
model and a heuristic are constructed. The delivery performance and
the competitive power of the system will be analyzed.
1 - A Branch and Bound Based Local Search for
Consumable Resource-Constrained Single Machine
Scheduling
Mehenni Tahar
Given the initial stock level of a consumable resource (e.g. raw materials, money, energy), a set of resource consuming jobs has to be scheduled on the machine such that there is enough quantity of the resource
for starting each job, and the total completion times is minimized. We
develop a local search method, based on the branch and bound algorithm to find the neighborhood, where its length is increased iteratively
to avoid the local optima. We perform several tests on the algorithm,
in order to evaluate the effectiveness of their main components.
2 - Iterated Local Search Algorithm for Flexible Job
Shop Scheduling Problems with Resource Constraints
Dimitris Paraskevopoulos, Panagiotis Repoussis, Christos
Tarantilis
This work presents an Iterated Local Search algorithm for flexible job
shop scheduling problems with resource constraints. Focus is on production floors with unrelated parallel machines. Multiple consumption
rates of renewable resources (e.g. energy, workforce) are considered
per machine and production phase. The proposed approach consists
of a local search, equipped with new compound moves, and an adaptive perturbation mechanism. A dual solution representation scheme is
adopted that is based on the job permutation and the temporal ordering.
Experiments on modified benchmark sets are reported.
3 - A Comparative Study of Evolutionary Algorithms
in Two-Machine Flowshop Problem with Availability
Constraints and Subject to Release Dates with Total
Tardiness Criterion
Abdelaziz Berrais, Mohamed Ali Rakrouki, Talel Ladhari
In this work we consider minimizing the total tardiness in a twomachine flowshop problem with release date of jobs and with unavailability periods of machines. Despite its theoretical and practical importance, this NP-hard problem has not been investigated before. Five evolutionary algorithms are developed for the problem under
consideration: Particle Swarm Optimization (PSO), Differential Evolution (DE), Genetic Algorithm (GA), Imperialist Competitive Algorithm (ICA), and Ant Colony Optimization (ACO). The computational
experiments provide evidence that the ICA perform consistently well.
45
MD-15
IFORS 2014 - Barcelona
4 - Minimizing the Maximum Lead Time in a Three-Stage
Supply Chain Scheduling Problem
Jacques Teghem, Walid Besbes, Taicir Loukil
A supply chain scheduling problem with three stages is analyzed with
several actors at each stage. Three types of constraints are considered: each job is dedicated to only one path of the supply chain; there
exist transportation times and batch deliveries between two successive
stages. The maximum lead time minimization is the performance measure. Two approximate methods are proposed. The first one is inspired
by the Johnson’s algorithm whereas the second is a genetic algorithm.
Additionally, a lower bound is proposed to evaluate the effectiveness
of both algorithms.
MD-15
Monday, 14:00-15:30 - Room 125
Novel Models and Applications in
Revenue Management
Stream: Revenue Management I
Invited session
Chair: Timo P. Kunz
1 - Optimal Keyword Bidding in Search-Based Advertising
Baris Selcuk
In search-based advertising, advertisers bid on keywords to have an impact on their ad’s placement, which in turn affects the response from
potential customers. An advertiser must choose the right keywords
and then bid correctly for each keyword. We construct and examine a
deterministic optimization model that maximizes total expected advertising revenue while keeping the total costs below a given advertising
budget. We investigate the characteristics of the model and provide an
exact solution. Numerical results are presented that give managerial
insights on bidding strategies.
2 - Learning and Pricing for Substitutable Products
Yalin Bi
We consider a choice-based dynamic pricing problem with substitutable products. The company chooses a price policy that maximizes
their expected total profit with a capacity constraint. A multinomial
logit (MNL) choice model is used to describe the customer choice
behavior. The parameters of the choice model are unknown and updated with Markov chain Monte Carlo (MCMC) method. We propose a
scheme with Multi-armed bandit (MAB) to solve the trade-off between
pricing to find a good estimation of customer behavior and pricing near
the optimal price to obtain better revenue performance.
3 - The Use of Marginal Revenues in Revenue Optimization
Thomas Winter
Marginal revenues (MR) are often used in practical revenue management applications, e.g., in airline RM systems. MR offer the possibility to model and measure the inter-dependency between pricing and
demand. Mathematically, they are defined as difference quotient of the
revenue difference divided by the demand difference when offering/not
offering a product. Hence, MR give indication about the benefit of a
product. The drawback is that MR are numerically unstable, in particular for small demand values. We investigate the behavior of MR and
discuss alternatives for more robust measures.
4 - The Value of Intra-Category Information in an LAAIDS Based Retail Price Optimization System
Timo P. Kunz, Sven F. Crone
A key challenge in the application of Revenue Management to retail is
the reliable estimation of a demand model that allows to individually
price large amounts of products under the consideration of cross-price
effects. We describe a price optimization system based on the Almost
Ideal Demand System and evaluate a number of estimation methods
that rely on, and combine information from different hierarchical levels of the category, including product attribute data. We use simulation
to quantify the additional monetary value that the estimation procedures add to the optimized price sets.
46
MD-16
Monday, 14:00-15:30 - Room 127
Copositive and Polynomial Optimization
III
Stream: Copositive and Polynomial Optimization
Invited session
Chair: Luis Zuluaga
1 - Tractable Relaxations of Polynomial Optimization
Problems
Bissan Ghaddar, Martin Mevissen
This talk presents an inequality generation scheme to improve semidefinite relaxations of polynomial optimization problems. Contrary to the
computationally expensive classical methods that build hierarchies of
semidefinite-based relaxations to approximate polynomial programs,
the proposed scheme improves the semidefinite relaxations without incurring exponential growth in their size. This approach combines techniques from real algebraic geometry and convex conic programming.
Computational results on instances from water and energy distribution
networks are presented.
2 - Appointment Sequencing: Moving Beyond The
Smallest-Variance-First Rule
Qingxia Kong, Zhichao Zheng
We study the design of healthcare appointment system when patients’
service durations are random. Numerous studies reported that sequencing patients in increasing order of variances of service durations (Smallest-Variance-First or SVF rule) performs extremely well
in many environments. We propose in this paper a copositive program
to model the appointment sequencing problem and obtain a general approach to construct interesting appointment sequencing rules that beat
the SVF rule in numerical simulations.
3 - On New Classes of Nonnegative Forms
Zhening Li
In this paper we introduce three new classes of nonnegative forms
(or equivalently, symmetric tensors) and their extensions. The newly
identified nonnegative symmetric tensors constitute distinctive convex
cones in the space of general symmetric tensors (order 6 or above). For
the special case of quartic forms, they collapse into the set of convex
quartic homogeneous polynomial functions. We discuss the properties
and applications of the new classes of nonnegative symmetric tensors
in the context of polynomial optimization.
4 - New Bounds for the cp-Rank in Copositive Optimization
Immanuel Bomze, Werner Schachinger, Reinhard Ullrich
In copositive optimization, it is essential to determine the minimal
number of nonnegative vectors whose dyadic products form, summed
up, a given completely positive matrix (indeed, one of these vectors
necessarily must be a solution to the original problem). This matrix
parameter is called cp-rank. Since long, it has been an open problem
to determine the maximal possible cp-rank for any fixed order. Now
we can refute a twenty years old conjecture and show that the known
upper bounds are asymptotically equal to the lower ones.
MD-17
Monday, 14:00-15:30 - Room 005
Global Optimization and Applications in
Development II
Stream: Global Optimization
Invited session
Chair: Herman Mawengkang
Chair: Gerhard-Wilhelm Weber
IFORS 2014 - Barcelona
1 - A Nonlinear Stochastic Optimization Model for Water
Distribution Network Problems with Reliability Consideration
Asrin Lubis, Herman Mawengkang, Herman Mawengkang
Water treatment and distribution is undoubtedly of high priority to ensure that communities could gain access to safe and affordable drinking water. Therefore the distribution network should be designed systematically. We propose a nonlinear stochastic optimization model for
tackling this problem under the consideration of reliability in water
flows. The nonlinearities arise through pressure drop equation. We
adopt sampling and integer programming based approach for solving
the model. A direct search algorithm is used to solve the integer part.
2 - Nonlinear Mixed-Integer Programming model for
Sustainable Production Planning of Multi-Product
Seafood Production
Tutiarny Naibaho, Herman Mawengkang
A multi-product fish production plant produces simultaneously multi
fish products from several classes of raw resources. The sustainable
production planning problem aims to meet customer demand subject
to environmental restrictions. This paper considers the management
which performs processing fish into several seafood products. The uncertainty of data together with the sequential evolution of data over
time leads the sustainable production planning problem to nonlinear
mixed-integer stochastic programming. Direct search is used for solving the deterministic equivalent model.
3 - Neighborhood Based Search Approach for Solving a
Class of Mixed-Integer Nonlinear Programming Problems
Devy Mathelinea, Herman Mawengkang
Integer programming is not new subject in optimization. However,
given its practical applicability, we face computational difficulties in
solving the large scale problems. In this paper we solve a class of
mixed-integer nonlinear programming problem by adopting a strategy
of releasing nonbasic variables from their bounds found in the optimal
continuous solution in such a way to force the appropriate non-integer
basic variables to move to their neighbourhood integer points. Some
computational experience are presented.
4 - An Improved Interactive Approach for Solving Sustainable Land Revitalization Planning Problems
Allysha Rahmi Darwin, Herman Mawengkang
Land revitalization refers to comprehensive renovation of farmland,
waterways, roads, forest or villages to improve the quality of plantation, raise the productivity of the plantation area and improve agricultural production conditions and the environment. The objective of
sustainable land revitalization planning is to facilitate environmentally,
socially, and economically viable land use. Therefore we use participatory approach to fulfill the plan. This paper addresses a multicriteria
decision aid to model such planning problem, then we develop an interactive approach for solving the problem.
MD-19
always lies "between" their objective mappings. The upper shell is not
an operational construct whereas its relaxation (upper approximation)
is. Therefore, in the presentation we investigate instances of multiobjective optimization problems in which an upper approximation is an
upper shell.
2 - Computationally Expensive Multiobjective Optimization - Survey and New Method
Seyed Mohammad Mehdi Tabatabaei, Jussi Hakanen, Markus
Hartikainen, Kaisa Miettinen, Karthik Sindhya
We first present a survey on surrogate-based methods to tackle computationally expensive multiobjective optimization problems. We split
the surrogate-based methods into sampling-based and optimizationbased ones. In particular, we focus on the capabilities of the methods in handling black-box functions and non-convex as well as disconnected Pareto optimal fronts. Secondly, based on the findings of
the methods studied, we propose a new, general-purpose scalarizationbased method. It handles computationally expensive multiobjective
optimization problems in an effective and intelligent way.
3 - Pareto Set Identification for Expensive Multiobjective
Optimization Problems
Ingrida Steponavice, Rob Hyndman, Laura Villanova, Kate
Smith-Miles
We discuss strengths and weaknesses of a new method for identifying
the Pareto optimal set: Efficient Pareto Iterative Classification (EPIC).
The method classifies evaluated decision vectors into two classes - nondominated and dominated - using machine learning, and then predicts
the Pareto optimal set for unevaluated vectors. Different strategies for
selecting the next decision vector to evaluate are developed to improve
the approximation of the Pareto set while minimizing the number of
evaluations. We test EPIC performance on benchmark problems and
compare the results to existing methods.
4 - The Interactive HyperBox Exploration Method for
Computationally Expensive Nonconvex Multiobjective Optimization Problems
Jussi Hakanen, Tomi Haanpaa, Kaisa Miettinen
We present a novel method for computationally expensive multiobjective optimization problems that the decision maker (DM) can use to explore Pareto optimal front. It uses an approximation of the Pareto front
based on a surrogate function and pre-computed Pareto optimal objective vectors (POOVs). By specifying desirable upper and lower bounds
for the objective vectors, the DM can investigate what kind of approximated POOVs exist for the problem. The method either presents the
approximated POOVs satisfying the given bounds or helps the DM in
adjusting the bounds if such POOVs could not be found.
MD-19
Monday, 14:00-15:30 - Room 128
Retail Labor Scheduling
MD-18
Monday, 14:00-15:30 - Room 112
Surrogate-Assisted Multiobjective
Optimization I
Stream: Multiobjective Optimization - Theory, Methods
and Applications
Invited session
Chair: Markus Hartikainen
1 - On the Validity of Replacing Upper Shells by Upper
Approximations
Janusz Miroforidis, Ignacy Kaliszewski
In order to find discrete Pareto front approximations most algorithms exploit only feasible solutions, deriving feasible approximations
(lower shells) of the Pareto set. We define an upper shell, a set of infeasible solutions, for which and for a given lower shell the Pareto front
Stream: Demand and Supply Planning in Consumer
Goods and Retailing
Invited session
Chair: Armann Ingolfsson
1 - Retail Labour Planning Considering Customer Impatience
Agust Thorbjornsson, Eyjolfur Asgeirsson, Armann
Ingolfsson, Pall Jensson, Thorlakur Karlsson
We study impatience for retail customers and its implications for
labour planning. Tracking customer behavior in retail is more difficult
than in call centers. By comparing stated preferences (through surveys) to revealed preferences (through tracked behavior) for call center
data, we hope to be able to extrapolate from data on retail customers
collected through surveys to predict actual customer behavior in retail
settings. We will work in close cooperation with three call centres and
three retail chains, where we can conduct customer surveys and video
recording.
47
MD-20
IFORS 2014 - Barcelona
2 - Retail Traffic: Arrivals, Labor Productivity and
Staffing Decisions
Jayashankar Swaminathan, Saravanan Kesavan, Vidya Mani
In this talk, I will focus on the notion of conversion rates as an important measure of retail performance and then discuss the impact of retail
labor on store productivity and discuss results on staffing decisions in
retail store and how to quantify the impact of accurate staffing.
3 - Box Office Demand-driven Labour Scheduling at the
Movies
Saeed Zolfaghari, Katherine Goff
New opportunities for operational efficiencies in movie exhibition exist as a result of the digital era and big data analytics. The scheduling
problem has been addressed in the literature at a macro level, allocation of movies to cinemas, and at a micro level, allocation of movies
to screens and times. This work extends the current research by addressing the labour scheduling problem and presenting opportunities to
leverage big data analytics in the development of new demand driven
decision support systems for optimizing theatre staff labour scheduling
across networks of multiplex cinemas.
aimed at creating Disaster Risk-Sensitive Shelter Plans (DR-SSP) for
nine barangays in the city of Legazpi. The results show the importance of building capacity in civil society organizations and local government, and the effectiveness of the participatory approach in data
collection, risk assessment, and disaster planning.
MD-21
Monday, 14:00-15:30 - Room 006
Optimization-Related Modeling &
Software
Stream: Optimization Modeling in OR/MS
Invited session
Chair: József Smidla
Chair: Qi Huangfu
4 - Optimising and Testing Traffic-Based Staff Schedules for a Retail Chain
Armann Ingolfsson, Osman Alp, Ivor Cribben, Michele
Samorani
1 - Adaptive Stable Additive Methods for Linear Algebraic Calculations
József Smidla, Péter Tar, István Maros
We report progress on a project in which we use time series models
to forecast retail store traffic, use predicted traffic and staffing levels to forecast sales, and use the resulting models to develop profitmaximizing staff schedules. A Canadian retail chain has agreed to test
our schedules.
Operations with floating point numbers in linear algebraic calculations
can cause numerical errors which can lead optimization algorithms to
wrong directions. Numerical errors can be handled using relative and
absolute tolerances with some overhead. A new method is proposed,
which automatically recognizes the necessity of these tolerances using
special SIMD instructions of the most recent CPU architectures in order to minimize overhead or even surpass standard implementations.
"This publication has been supported by the project TÁMOP-4.2.2.C11/1/KONV-2012-0004."
MD-20
Monday, 14:00-15:30 - Room 129
IFORS Prize for OR in Development 2014 3
Stream: IFORS Prize for OR in Development 2014
Award Competition session
Chair: Andrés Weintraub
1 - Measuring the Effectiveness of Development Programmes for Vulnerable Indigenous People in India
Bijaya Krushna Mangaraj, Upali Aparajita
This paper tries to measure as well as benchmark the effectiveness of
development programmes meant for the vulnerable indigenous people
of India. These people who live in different parts of the country are
named as particularly vulnerable tribal groups (PTGs) by the Ministry
of Tribal Affairs, Government of India. In this work, development effectiveness has been explained in a multi-dimensional framework and
multi-criteria decision-making methodologies have been employed to
measure it. The identification of the multiple criteria of the complex
effectiveness construct has been done with the help of an ethnographic
survey followed by a confirmatory analysis. The concept of relative
effectiveness has been introduced to benchmark the effectiveness from
that of the relatively ineffective ones. A twophase fuzzy goal programming methodology has been adopted to determine an effective
portfolio for the purpose. Two case studies were also presented to
demonstrate the measure of development effectiveness of the government sponsored development programme for the PTGs who are in the
weakest section of the Indian society.
2 - Disaster Risk-Sensitive Shelter Plans from
Community-Based Risk Analysis for Legazpi City,
Philippines
Leorey Marquez, Sarah Redoblado, Maria Cheryl Prudente,
Ernesto Serote, Nicasio Nicasio de Rosas, Myrna Llanes,
Jenifer Belarmino, Evelyn Sierra, Bernard Apuli
Improving social protection and community-driven development
(CDD) interventions and linking these mechanisms to disaster risk
management (DRM) increases the effectiveness of DRM programs.
This paper describes the implementation and impact of a CDD project
48
2 - Optimization Modeling in Heterogeneous Distributed
Computing Infrastructure
Vladimir Voloshinov, Sergey Smirnov
We present an approach to deploy optimization systems in a heterogeneous distributed computing environment on the base of RESTservices and coarse grain decomposition of the problem. These services provide remote access to state-of-the-art solvers and translators
of AMPL (A Modeling Language for Mathematical Programming),
e.g. it enables to run any AMPL-script in distributed mode, when all
independent intermediate sub-problems are solved in parallel by remote optimization services. Implementations of Dantzig-Wolfe and
coarse grain type of branch-and-bound algorithms are considered as
examples.
3 - A Parallel Dual Simplex Method
Qi Huangfu
The dual simplex method is a fundamental and widely used technique
for solving Linear Programming (LP) and Mixed Integer Programming (MIP) problems, yet has been remarkably difficult to parallelize
efficiently. We present a new parallel dual simplex method that has
been developed for the FICO Xpress Optimization Suite. We will also
present benchmarks on large scale LP problems and the root solve (as
a sequence of LP problems) of large and hard MIP problems, that show
how such problems can often be solved twice as fast as with the traditional sequential dual simplex method.
4 - An Application of Queue Modelling to the Customers
in a Gas Station
Abdullah Ozcil, Irfan Ertugrul
In this work, the service process of a gas station having heavy customer
traffic in Denizli (Turkey) is simulated through a review of the available literature related to queue modelling and is determined by process
efficiency and performance level. The queue modelling is identified
related to waiting in the queue of gas station, customers and optimal
service levels and service needs are tried to be determined. The data related to the gas station queue problems are evaluated using Microsoft
Excel and WinQSB software packages for planning the capacity, increasing the productivity.
IFORS 2014 - Barcelona
MD-22
Monday, 14:00-15:30 - Room 007
DEA, AHP and Statistical Analysis
Stream: Health Care Data Analytics
Invited session
Chair: Kwok Leung Tsui
Chair: Simone Angelo
1 - Case-Mix Adjusted Efficiency Score: the Case of the
South African Private Hospital Industry
Shivani Ramjee, Kathryn Dreyer
We examine the impact of risk adjusting a DEA hospital model for the
mix of clinical cases, and find that ignoring case mix can distort the
efficiency scores of individual hospitals. On comparison of three different techniques for case-mix adjustment, it is evident that if there is
sufficient data to construct a case-mix adjustment factor, adjusted admissions should be used, rather than using the factor as an additional
output. In the case where insufficient data is available, disaggregating
admissions captures some of the differences in case mix but substantial
power is lost.
2 - Efficiency and Quality implications in Health Care
Management
Ioannis Mitropoulos, Panagiotis Mitropoulos
Efficiency and quality constitute the fundamental goals of any contemporary Health Care system. Especially nowadays where the economic pressures impose major restrictions in fiscal policy, this study
investigates the implication of efficiency and quality in primary healthcare centers. Cluster analysis of patient satisfaction and bootstrapped
DEA analysis scores are performed. Implications are examined by regressing these scores with variables that represent clusters from alternative dimensions of patient satisfaction. Significant interactions of
efficiency with quality are apparent.
3 - Demand Forecast and Optimal Allocation of ICU
Beds: A Case Study in Rio de Janeiro
Simone Angelo, André Salles, Edilson Arruda, Miranda
Albino Martins Muaualo
Determining the optimal number of ICU beds in a given neighborhood
is essential due to both the expensive cost of these beds and the ever
increasing demand for them. This paper is concerned with finding
the optimal number or ICU beds in the metropolitan region of Rio
de Janeiro, making use of information on the daily requests for ICU
beds in a set of selected hospitals in 2010 and 2011. This information
is used to obtain a demand forecast by means of exponential smoothing and Box-Jenkins models, which is the input of the queueing model
whose output is the optimal number of ICU beds.
MD-24
2 - An Affective Model for an Autonomous Decision
Agent
Pablo Gómez Esteban, David Rios-Insua
We provide a decision making model which includes four basic emotions and mood as affective elements, dynamically influencing the
weights in a multiobjective expected utility model. We also incorporate the possibility of triggering impulsive behavior when sufficiently
high intensities of certain emotions are reached. Our motivation for
this is the development of algorithms that control the behavior of autonomous robots, aiming at improving interactions. We present some
simulations in which our agent faces differently behaving users and
compare its performance with an emotionless agent.
3 - Why Emotional Behaviors Matter for the Design of
Decision Support Systems (DSSs): Evidence from
Text-based Electronic Negotiations
Patrick Hippmann
Emotional behaviors shape the progression of negotiation processes
and can steer negotiations toward success or failure. The present work
shows that DSSs impact emotional behaviors throughout the negotiation process, and explains why the research on and design of DSSs
should incorporate this interconnection. We elicitate emotional behaviors from the communication process by using multidimensional scaling, and analyze emotional behaviors in line with a multi-level research
framework, which addresses behavioral (i.e., intra- and inter-personal)
and procedural (i.e., temporal) dynamics.
4 - Emotions in a Repeated Cournot Duopoly: A Psychophysiological Experiment
Ilkka Leppänen, Raimo P. Hämäläinen
We study emotions in a Cournot duopoly, where experimental subjects
often cooperate but also reciprocate. We measure psychophysiological reactions that include the skin conductance response (SCR) and
facial electromyography (EMG) on three muscle regions. We find that
choices that would lead to higher own payoffs are accompanied by
higher SCR than choices that lead to lower own payoffs. The SCR is
also increasing in own payoffs. We also find that low own payoffs are
accompanied by negative emotions in EMG. Our research provides a
method of observing directly emotions in strategic interactions.
MD-24
Monday, 14:00-15:30 - Room 212
Preference Learning III
Stream: Preference Learning
Invited session
Chair: Andranik Tangian
MD-23
Monday, 14:00-15:30 - Room 008
Emotions and Human Behaviour in
Interactions
Stream: Behavioural Operational Research
Invited session
Chair: Raimo P. Hämäläinen
1 - Preference Learning from Managerial versus Data
Mining Point of View
Peter Vojtas, Ladislav Peska
We consider the CRISP-DM process for preference learning for an eshop. We discuss the problem along several dimensions: # users; #
items; complexity of items; explicit-implicit user feedback; registeredanonymous user; frequent-rare visit repetition; data sparsity (user x
item matrix); data real-artificial. We focus specially on relation between measuring quality of offline data mining and MCDA for the
manager deciding deployment (online A/B testing). We illustrate it
on real implicit behavior data from an e-shop travel agency (content
based recommendation with collaborative aspect).
1 - PoSITeams - Positive Systems Intelligent Teams,
an Agent Based Simulator for Studying Group Behaviour
Juha Törmänen, Raimo P. Hämäläinen, Esa Saarinen
2 - Improve Infrastructure Stakeholder Collaboration
through e-Participation: A Strategic Analytics Planning Approach
Xiaojun Wang, Isabella Lami, Leroy White
The agent based simulator analyses the effects of positive interaction
in groups with different organisational and interaction structures. The
ideas in the model draw from our work in human systems intelligence
and broaden and build the theory of positivity by Barbara Fredrickson.
The software is used to explore structures that generate and support
positivity in teams. We have planned to allow the customization of the
reactions of the agents. Then PoSITeams could be used in self development by allowing a member agent to analyze the effects of his/her
behavioural changes on the whole team.
This research describes a Strategic Infrastructure Analytics Planning
approach that is internet/cloud based and seeks to foster collaboration
amongst infrastructure providers and the public. The approach provides a highly beneficial means for organisations to manage their own
infrastructure delivery programmes and share high-level information
with stakeholders in an efficient manner. The approach will facilitate
greater sharing, analysis and action upon infrastructure ’big’ data, and
combines e-participation with MCDA to ensure community consultation and participation in decision-making.
49
MD-25
IFORS 2014 - Barcelona
3 - Regional Anti-Desertification Management with a
Multi-Criteria Inference Approach: A Study of the
Khorasan Razavi Province in Iran
Tommi Tervonen, Adel Sepehr, Milosz Kadzinski
We apply a multi-criteria inference approach for classifying 28 administrative zones of the Khorasan Razavi province in Iran into three equilibrium classes which indicate the zones’ susceptibilities for desertification (collapsed, transition or sustainable). The model is parameterized with enhanced vegetation index measurements from 2005 and
2012, and 7 other indicators measured in 2012. Results indicate that
the resulting model is underdefined in terms of attributes, but the approach is promising in providing usable decision support for managing
anti-desertification efforts.
4 - Proportional Coalitional Values for Monotonic
Games on Convex Geometries with a Coalition Structure
Qiang Zhang
A new model called games on convex geometries with a coalition
structure is proposed where the player set and the coalition structure
both form a convex geometry. A value called the proportional coalitional solidarity value is defined. From the expression of this value,
we know that any union’s proportional coalitional solidarity value coincides with the solidarity value of the union in the quotient game and
the players in a union share this amount proportionally to their solidarity values in the original game on convex geometries (i.e., without
unions).
4 - How German Parties Learn the Electorate’s Preferences
Andranik Tangian
The goals of the paper are empirically finding the political preferences
of the German electorate at the moment of the 2013 Bundestag election and evaluating the representative capacity of the political parties
and that of the Bundestag. The 2013 election winner, the CDU/CSU,
is shown to be the least representative among the 28 parties considered. The representativeness of the Bundestag is about 50%, not much
surpassing the decision results when on every policy issue a coin is
tossed.
MD-25
Monday, 14:00-15:30 - Room 009
Mathematical Methods of the Economic
Theory
MD-26
Monday, 14:00-15:30 - Room 010
Neural Networks and Applications
Stream: Fuzzy Decision Support Systems, Soft Computing, Neural Network
Invited session
Chair: Hans-Jörg von Mettenheim
Chair: Georgios Sermpinis
1 - Towards a Better Explanation of Asset Pricing Puzzles in Emerging Markets
Leoni Eleni Oikonomikou
1 - A Theory for Estimating Consumer’s Preference from
Demand
Yuhki Hosoya
The aim of this presentation is to test the existence of asset pricing
puzzles in BRICS equity markets and to quantify them. The empirically tested model is the Long-Run Risks model developed by Bansal
and Yaron (2004) and this is the first study that uses this model with
BRICS equity markets data. In this model, the consumption and dividend growth rates contain a small long-run component and fluctuating
economic uncertainty. The performance of the model is tested using
Epstein-Zin and external habit preferences. The empirical results for
BRICS are compared with US data for the last 20 years.
This study shows that if the estimate error of the demand function
is sufficiently small with respect to local C1 topology, then the estimate error of the corresponding preference relation is also sufficiently
small. Furthermore, this study shows that if the estimate error of the
inverse demand function is sufficiently small with respect to local uniform topology, then the estimate error of the corresponding preference
relation is also sufficiently small.
2 - Rolling Genetic Support Vector Regressions: An Inflation and Unemployment Forecasting Application
in EMU
Georgios Sermpinis, Andreas Karathanasopoulos,
Charalampos Stasinakis, Konstantinos A. Theofilatos
Stream: Mathematical Economics
Invited session
Chair: Alexander Zaslavski
2 - R&D Strategies with Uncertain Outcomes and Potentially Misleading Spillovers
Fouad El Ouardighi, Konstantin Kogan
This paper investigates the research and development accumulation
and pricing strategies of two firms competing for consumer demand
in a dynamic framework. A firm’s research and development is
production-cost-reducing and can benefit from part of the competitor’s
research and development stock without payment. However, the R&D
outcomes are uncertain for both firms so that spillovers are potentially
misleading. To evaluate the impact of mutual observability of the current R&D stocks between rivals, open-loop and feedback Nash equilibria are compared.
3 - Locally Robust Mechanism Design
Chaowen Yu
The purpose of this paper is to investigate locally robust implementability of a social choice function. Locally robust implementation
captures the idea that the social planner knows the agents’ believes
well, but not exactly. It is known that in many economic models, almost all social choice functions are not locally robust implementable.
However, by considering the replica economy, we show that, asymptotically, well-known mild conditions are sufficient for a social choice
function to be locally robust implementable.
50
In this paper a hybrid Rolling Genetic — Support Vector Regression
(RG-SVR) model is introduced in economic forecasting and macroeconomic variable selection. The proposed algorithm is applied in a
monthly rolling forecasting task of inflation and unemployment in
eight EMU countries. The RG-SVR genetically optimizes the SVR parameters and adapts to the optimal feature subset from a feature space
of potential inputs. The feature space includes a wide pool of macroeconomic variables that might affect the two series under study of every
country.
3 - High-Order Multivariate Neural Network Based Fuzzy
Time Series Model for Car Road Accidents
Ozer Ozdemir, Memmedaga Memmedli
Multivariate and high order neural network based fuzzy time series approach might obtain better forecast results than other approaches for
fuzzy time series. So, we used a new high order multivariate neural
network based fuzzy time series model for forecasting. We used various degrees of membership in establishing fuzzy relationships with
various numbers of hidden nodes. The time series data of the total
number of annual car road accidents casualties in Belgium from 1974
to 2004 are used for the proposed method and other methods in the
literature. All results are compared with each other.
IFORS 2014 - Barcelona
MD-27
Monday, 14:00-15:30 - Room 213
OR in Quality Management III
Stream: OR in Quality Management
Invited session
Chair: Chien-Wei Wu
1 - Process Yield Assessment for Processes with Multiple Manufacturing Lines
Yu-Ting Tai, Huei Chun Wang
Process yield assessment is critical since it could provide feedback on
what actions need to be taken for yield control. Process capability indices have been widely applied in quality assurance since some manufacturing processes require very low fraction of defectives. Due to
economic scale considerations, multiple manufacturing lines are common. However, existing research works only deal with processes with a
single manufacturing line extensively. In this paper, we provide a new
and effective index method for assessing the process yield for those
processes with multiple manufacturing lines.
2 - Skewed Correction Average Control Chart Based on
Sample Standard Deviation
Shih-Chou Kao, Yi-Chuan Huang
This study proposes an average control chart with the skewed correction and the standard deviation (SCS) based on the generalized lambda
distribution (GLD). Constants of SCS average control chart are calculated in accordance with the GLD and the method of moments by using Monte-Carlo simulation. This study also compares type I risks and
type II risks among control charts, including skewed correction based
on range and weighted variance control charts. The average control
chart with the SCS gives good effectiveness for monitoring the both
type I risks and type II risks.
3 - A Variable Quick Switching Sampling System for
Controlling Lot Fraction Nonconforming
Shih-Wen Liu, Chien-Wei Wu
In this paper, a new variable quick switching sampling system based
on process yield is developed for lot sentencing when the quality characteristic follows a normal distribution and has bilateral specification
limits. The operating characteristic (OC) function of the proposed sampling system is derived based on the sampling distribution of process
yield index and the OC curve is required to pass through two designed
points for satisfying business contract. The computation result shows
that the proposed plan is more economic in terms of needing fewer
required sample size for inspection.
4 - A New Sampling Plan by Variables Inspection for
Product Acceptance Determination
Chien-Wei Wu, Shih-Wen Liu
Acceptance sampling plans provide the producer and the consumer a
general rule for lot sentencing to satisfy the desired quality requirements and protections. In this paper, a new concept of sampling strategy is applied to develop a sampling plan by variables inspection based
on process yield for product acceptance determination. The results
show that the proposed sampling plan requires smaller sample size for
inspection while providing the same projection to the producer and the
consumer.
MD-28
Monday, 14:00-15:30 - Room 130
MD-30
1 - Using genetic optimization algorithms for optimal
project investment sequencing. How to evaluate
project risks using Monte Carlo simulation.
Manuel Carmona
@RISK performs risk analysis using Monte Carlo simulation to show
outcomes in your spreadsheet, and their likelihood of occurrence.
@RISK also helps you plan the best risk management strategies
through the integration of RISKOptimizer, combining Monte Carlo
simulation with the latest solving technology. We will demonstrate
a number models such as; how to plan a capital investment considering probabilistic variables and strategic risks. We will also optimize a
portfolio of projects, considering probabilistic returns and capital inflow rates.
MD-29
Monday, 14:00-15:30 - Room 011
Volatility Modeling and Investment
Strategies
Stream: Financial Optimization
Invited session
Chair: Qi Wu
Chair: Nan Chen
1 - Mean-Field Formulations for Optimal Multi-period
Mean-Variance Portfolio Selection
Xun Li
When a dynamic optimization problem is not decomposable by a stagewise backward recursion, it is nonseparable in the sense of dynamic
programming. The classical dynamic programming-based optimal
stochastic control methods would fail in such nonseparable situations
as the principle of optimality no longer applies. Among these notorious
nonseparable problems, the dynamic mean-variance portfolio selection
had posed a great challenge to our research community until recently.
We propose a novel mean-field framework that offers a more efficient
modeling tool and a more accurate solution scheme.
2 - Multi-curve Term Structure Modeling with Lowdimensional Differing Short Rates
Qi Wu
We approach the joint modeling of discount curve and forward curve
using short rates based on the premise that low-dimensional quasiGaussian short rate models can be as effective as a full-blown LIBOR
market model. In our specificaiton, the discount curve stems from
the yields of the posted collateral and the forward curve is associated
with the usual LIBOR forwards. The joint dynamics of differing short
rates are modeled in the collateralized martingale measure with timedependent volatility and correlation to generate flexible swaption skew.
Analytical formulas of swaption vol are derived.
3 - Capturing the Term Structure of FX Smile
Pui Yin Chan
The term structure of volatility smile is the aggregated market expression of forward implied vol at a series of future horizons, yet retrieving
them asks for a model that calibrates the non-ATM maturity curves
well besides the ATM term structure. In this paper, we focus on the
FX vol market and propose a dynamic SABR model with deterministic
volatility shift functions and contrast it with the better known lambdaSABR model that uses mean-reversion in vol drifts. Our extensive
numerics suggest that the vol-shifted SABR, although structurally different, is as competitive as the lambda-SABR.
MD-30
Optimal Project Investment Sequencing
(Palisade)
Monday, 14:00-15:30 - Room 012
Stream: Sponsored Sessions
Sponsored session
Stream: Financial Mathematics and OR
Invited session
Chair: Manuel Carmona
Chair: Masamitsu Ohnishi
Financial Mathematics 1
51
MD-31
IFORS 2014 - Barcelona
1 - Regime Switching among Several Short Rate Models
Keiichi Tanaka
We study the evaluation of contingent claims under a regime switching environment where either the dynamics or the level of the short
rate is switched among ones of several short rate models. This paper
decomposes the solution to the system of partial differential equations
with terms represented by recursive integrals in a meaningful way by
making use of the homotopy perturbation method. Some examples of
the bond price decomposition and the derived term structure of yield
curve are presented and discussed. The greeks of the contingent claim
price is also derived in the same form.
2 - Equilibrium Relationship between the Performance
and the Information Ratio with Transaction Costs
Shingo Nakanishi, Masamitsu Ohnishi
We study that both the potential loss of performance and its information ratio which is a risk-adjusted measure of active management make
the equilibrium relationship. At the same time, we consider it with
transaction costs. That is, it is considered that the decision-making
measure for active investment that is the probability based on financial
mathematics indicates the ratio of important investment in the equilibrium relationship when we think of the information ratio. Moreover,
we clarify that the other equilibrium relationship is shown mathematically to explain above mentioned.
3 - Limit Order Book Dynamics and Optimal Execution
Strategy
Seiya Kuno, Masamitsu Ohnishi
In this study we consider the resilience effect on optimal execution
strategy by the institutional trader taking the Limit Order Book (LOB)
into account. Under the assumption of linear market impact, we specify how the new orders from the noise traders are provided in the LOB,
then derive the optimal execution strategy for the institutional trader
focusing mainly on the resilience. By analyzing a price model from
the LOB in which the liquidity is provided by many noise traders, the
optimal execution strategy is varied by the characteristic of the noise
traders, in particular the patience.
4 - Free Boundary Problem for Double Stopping Russian
Option
Kyohei Tomita, Tomatsu Takumi, Katsunori Ano
We study the double exercise Russian option. For two times exercise chances, the system of the corresponding free-boundary problem
(FBP) are derived and the optimal stopping strategy are studied in details. Then all componets in the free-boundary problem such as the
smooth-fit condition are proved. The verification theorem of the FBP
for the pair of the optimal price and the optimal stopping boundaries
are proved.
MD-31
Monday, 14:00-15:30 - Room 013
Public Sector Networks and Applications
Stream: Decision Processes
Invited session
Chair: Zhili Zhou
1 - Risk-Averse Network for Disaster Preparedness
Miguel Lejeune, Nilay Noyan, Xing Hong
We propose a new risk-averse stochastic modeling approach for the
design of a pre-disaster relief network. We introduce a probabilistic
constraint on the existence of a feasible flow to ensure that the demand
for relief supplies across the network is met with high probability. Local chance constraints ensure the responsiveness and self-sufficiency of
each region. The Gale-Hoffman inequalities represent the conditions
on the existence of a feasible network flow. The solution method rests
on a preprocessing algorithm and on a Boolean reformulation method
for chance constraints.
52
2 - ICT and Humanitarian Supply Chains
Ioanna Falagara Sigala, Tina Wakolbinger, William Kettinger
This paper aims to explore the role of information systems in supporting humanitarian organizations in efficiently and effectively delivering
essential medicines. The study deploys both qualitative and quantitative methods. First, we look at the current implementation of an ERP
at a medical humanitarian organization’s missions. Second, we use
agent-based modeling and simulation to highlight how the technology
adoption will spread throughout the organization, where points of resistance might exist.
3 - Allocation Models for Shared Ambulance Services
Lavanya Marla
We consider the setting where multiple ambulance services compete
to serve a population. Such settings have been observed in emerging
economies where 911-type services are just being set up, and they compete with existing ad-hoc services; as well as in cities like New York,
where multiple EMS companies exist. First we show, using existing
data from a densely populated city, that this can have high opportunity costs due to phenomena like abandonment. Second, we discuss
game-theoretic models that can facilitate better ambulance utilization
and improve service levels for the population.
4 - Incident Response Bus Routes Planning and Management for Public Transit Networks
Zhili Zhou
In this paper, we study the subway system incident response in public
transit networks by utilizing both existing public bus service and express bridging bus service. We design the express bridging bus routes
and frequencies and rearrange the existing bus stops and frequencies
to minimize the waiting time of impacted passengers. We propose a
column generation based method to select bridging bus routing, rearrange existing bus stops, and determine bus frequencies in a time-space
network. We implement solution approaches for incident cases in Singapore MRT system and demonstrate results.
MD-32
Monday, 14:00-15:30 - Room 014
Humanitarian Operations Research for
Developing Countries
Stream: Humanitarian Operations Research
Invited session
Chair: Gerhard-Wilhelm Weber
Chair: Joao Neiva de Figueiredo
1 - An Objective Methodology to Measure Corruption
Levels and Institutional Maturity in Developing Countries
Joao Neiva de Figueiredo
Corruption intensity across countries is mostly gauged through rankings based on surveys which often render subjective results. We suggest an objective methodology to evaluate corruption levels and institutional maturity in different jurisdictions which takes into account local
cultural values and attitudes towards corruption and is based on operations research and industrial engineering statistical quality control
sampling techniques. The conceptual framework is developed, theoretical backing is provided, and an illustrative example of corruption
levels in Brazil is presented.
2 - Better Queue Management Using Data Envelopment
Analysis: An Application in a Large Public Hospital
of a Developing Country
Komal Aqeel Safdar, Ali Emrouznejad, Prasanta Kumar Dey
Queuing is considered as a key efficiency criterion in any service industry, including healthcare. Despite numerous healthcare applications,
Data Envelopment Analysis (DEA) has not been used before for evaluating queuing systems. In developing countries, overloaded health
systems and absence of appointment systems result in extensive waiting times. This paper aims at employing DEA to assess the queuing
system of a large and busy public hospital in Pakistan, where all patients are walk-ins. Hence the objective is to develop a framework for
improving the patient flow at the designated hospital.
IFORS 2014 - Barcelona
3 - Multi-Objective Decision Analysis for Force Analysis
of Conventional Forces Problem
Mehmet Durkan
One of the most important problems in Defense and Operation Planning is being able to make a detailed force analysis and then make
force comparisons. This research approaches the problem statically.
It considers air power as an example of a force and uses conventional
air force specifications to see how to analyze a force statically. This
research identifies the analysis of an air force as a decision analysis
problem and applies the Value Focused Thinking method to build a decision model. It is recommended to future operation planners to use
this model in operation planning processes.
4 - A Stakeholder-based Approach for Assessing the Effects of Land Use Scenarios on Ecosystem Services:
Cases of Bolgatanga and Bongo Districts in Upper
East Region, Ghana
Hongmi Koo, Christine Fürst
In Ghana where most inhabitants rely on utilizing natural resources,
agricultural land uses faced with unfavorable climate condition affect
the ecosystem services (ESS). Our study suggests a stakeholder-based
assessment and scenario modeling framework for estimating the potential capacity of land use to provide ESS. ESS to interpret the regional
conditions, relations between ESS and land-use types, and eligible land
use scenarios are determined based on opinions of stakeholders. The
GISCAME platform is used to balance place-specific/overall targets
for developing successful planning scenarios.
MD-34
4 - When and for Whom Would e-Waste be a Treasure
Trove? Insights from a Network Equilibrium Model of
e-Waste Flows
Fuminori Toyasaki, Tina Wakolbinger, Thomas Nowak, Anna
Nagurney
One of the major concerns of many electrical and electronic equipment waste (WEEE) take-back schemes is whether adequate amounts
of WEEE flow into the designed recycling systems. We analyze how
technical, market, and legislative factors influence the total amount of
e-waste that is collected, recycled, exported and disposed of. The results of the numerical examples highlight the importance of considering the interaction between the supply and the demand side for precious materials in policy-decisions. Furthermore, the results emphasize the need for cooperation between recyclers.
MD-34
Monday, 14:00-15:30 - Room 016
Energy Analytics
Stream: Data Mining in Finance and Commodities
Invited session
Chair: Marcus Hildmann
MD-33
Monday, 14:00-15:30 - Room 015
Closed-loop Supply Chains and Reverse
Logistics
Stream: Environmental Sustainability in Supply Chain
Invited session
Chair: Fuminori Toyasaki
1 - The Redesign of Extended Producer Responsibility
and its Impact on a Producer’s Recovery Strategies
Wenyi Chen, Beste Kucukyazici, Maria Jesus Saenz
This research investigates the economic and environmental impacts of
potential legislative changes on consumers and producers. The model
consists of a regulator and an OEM engaged in a Stackelberg game
with perfect information. We use CED (cumulative energy demand),
toxic waste and virgin material usage as our measures of environmental
impact. A frontier of efficient policies is developed for the regulator
to balance the economic and environmental impacts. The proposed
methodology is illustrated using a case based on a German company.
2 - Accurate Response with Refurbished Consumer Returns
Marc Reimann
In this paper we study a retailers’ optimal accurate response policy under consumer returns that can be refurbished and resold on the primary
market. Using a newsvendor-type formulation, we analyze the impact
of the optimal reaction including the refurbishing option on the anticipative supply decision taken under uncertainty. We then extend the
model by including partial backlogging, where some of the demand
may be lost when shortages occur. For both, the basic model and its
extension we provide analytical and numerical insights into the retailers’ optimal behavior.
3 - Reverse Logistics Decision Making for Modular Products
Thomas Nowak, Fuminori Toyasaki, Tina Wakolbinger
Product design issues play a crucial role in determining a product’s
life-cycle duration, costs and environmental impacts. In this paper,
we study how supply chain strategies and reverse logistics activities
influence a product’s level of modularity. We develop inter-temporal
optimization problems for companies following a push and a pull supply chain strategy. The model analysis provides insights concerning
product design and reverse logistics decisions.
1 - Review of Day-ahead Planning Models for Electricity
Trading
Minja Marinovic, Milena Popovic, Uros Sosevic
Since the nineties, electricity markets have been deregulated, allowing customers to choose their providers. This situation opened new
optimization problems in electricity trading. The literature on different aspects on this subject is extensive and gives a variety of different
approaches and solutions. The aim of this paper is to present various
models for solving a problem of day-ahead planning in electricity trading. Day-ahead planning refers to finding an optimal plan, which will
maximize the daily profit considering demands, supply and the available transmission capacities.
2 - Application of Modern Portfolio Theory for the Evaluation of Onshore Wind Power Investments in EU
Countries
Dimitrios Angelopoulos, Konstantinos Milios, Haris Doukas,
John Psarras
Onshore wind power currently is one of the most competitive renewable energy technologies. In this study, the problem of optimal geographic distribution of new onshore wind power plants is examined
from the investor’s perspective. This methodology focuses on technical and economic parameters of different EU countries to extract the
efficient portfolios that maximize the inverse levelized cost of electricity generation and minimize its volatility. An illustrative example is
provided to evaluate this methodology and sensitivity analysis of the
key input variables of the model is performed.
3 - Apply Genetic Algorithms to Estimate Wind Energy
Function Parameters
Sheu-Hua Chen, Hong Tau Lee
Wind power is one of the green energies. Theoretically, a wind turbine
is expected to produce a certain amount of energy given a specific wind
speed. Based on the analysis of historical data of wind turbines, it revealed that the corresponding power curve is similar to a logit function.
We used the least squares method to construct the logit function with
four parameters. The models are solved by a designed GA. The calculated parameters are used in the power function for monitoring the
effectiveness and efficiency of the wind turbine.
53
MD-35
IFORS 2014 - Barcelona
4 - A MINLP Model for the Bidding Design Problem
of a Hydroelectric Producer: The Case of a HeadDependent Cascaded Reservoir System in Spain
Javier Diaz, Luis Moreno
It is presented a large-scale mixed-integer non-linear programming
(MINLP) model to maximize the day-ahead profit of a hydroelectric
generation company (H-GENCO) in a pool-based electricity market.
Incorporating some variants to the basic model it can be used for decision making about questions associated with three classical problems:
when to generate?, the Unit Commitment Problem; how much to generate?, the Economic Dispatch Problem; how to offer?, the Bidding
Design Problem. Price scenarios are considered. Results of the case
study are discussed.
MD-35
Monday, 14:00-15:30 - Room 131
Stochastic Models
Stream: Stochastic Modeling and Simulation in Engineering, Management and Science
Invited session
Chair: Koichi Nakade
1 - System Failure Probability of a k-out-of-n System
Considering Common-Cause Failures
Tetsushi Yuge, Shigeru Yanagi
This paper discusses the system failure probability of a k-out-of-n system considering the common-cause failures. The conventional implicit technique is introduced at first using the failure probabilities of
common-cause basic events. Then the system failure probabilities are
formulated when the symmetry assumptions, i.e., all components have
the same failure probabilities, are introduced. We also provide algorithms to enumerate minimal cut sets and to calculate the system failure
probability. These methods can apply to the systems with non-identical
components.
2 - Advertisement on Social Network
Hiroshi Toyoizumi
Many companies are starting to rely on marketing activities on social
networks. Main marketing method on social network is advertisement
by word of mouth (WOM). On the other hand, it is known that largedegree nodes can become the bottleneck of spreading information on
complex networks. In this research we will analyse the spread process
of WOM advertisement on social network by using extended heterogeneous SIR (Susceptible-Infectious-Recoverd) model. Further, we will
discuss the possible improvement of WOM advertisement.
3 - Optimal Control Problems in a Closed Loop Manufacturing System with Stochastic Variability
Kenichi Nakashima
This paper deals with a closed loop manufacturing system problem
with stochastic variability such as the demand. The system is formulated into a Markov decision process (MDP) that gives us the optimal
control policy that minimizes the expected average cost per period.
We define the state of the system by some kinds of inventory levels
and the cost function is composed of various cost factors such as holding, backlog and some kinds of production costs etc. We obtain the
optimal production policy using policy iteration method. Numerical
results show the properties of the optimal policy.
MD-36
Monday, 14:00-15:30 - Room 132
Forestry Industry Production Planning
and Management
Stream: OR in Agriculture, Forestry and Fisheries
Invited session
Chair: Ola Eriksson
1 - Designing Value Chains in the Forest Sector
Sophie D’Amours, Mikael Rönnqvist, Marc-André Carle
Over the years, models and solution methods have been proposed to
design value chains in the forest sector. The strategic design is viewed
as a combination of assets (including timber licences) and coordination
mechanisms (including partnership contracts and policies), to meet the
goals of the stakeholders within a highly regulated social, environmental and economic environment. A review with focus on the challenges
face by the forest industry is presented. Issues are linking forest and
industry, considering uncertainties, ramp-up investment strategies and
coordination mechanisms.
2 - Optimizing the Log Yard Assignment Problem given
Different Diameter Distributions and Volumes
Maria Anna Huka, Manfred Gronalt
We present an optimization approach to minimize the log yard round
wood transportation time for a medium sized hardwood sawmill. Simultaneously taking into account the log transportation time, storage
capacity, and yard crane deployment an optimal assignment of ejection
boxes, storage boxes and feeding carriages can be found. Furthermore,
several diameter distributions and the stepwise increase of the overall
volume are investigated. The solutions of an optimization model and a
partition model are compared to heuristic approaches with and without
the partition of assortments.
3 - Tactical Planning as the Focal Point of Forest Company Planning: A Suggestion
Ola Eriksson, Malin Nilsson, Olof Wahlberg
The forest planning system followed by Swedish forest companies
is sequential (longer-term plans form the framework for shorter-term
plans) and hierarchical (top-level management prepare the long range
plans and the lower management plans with shorter horizons). This approach tends to uncoordinated planning activities and unused knowledge at lower levels of the organizational ladder. Here, an alternative,
bottom-up oriented, approach is demonstrated that illustrates potential
advantages and drawbacks of the approach and its viability in perspective of new market and technical developments.
MD-37
Monday, 14:00-15:30 - Room 017
Fuzzy AHP and ANP
Stream: AHP (Analytic Hierarchy Process) /ANP (Analytical Network Process)
Invited session
Chair: Maznah Mat Kasim
Chair: Amy H. I. Lee
4 - Optimal Maintenance Policy of Multiple Parts with
Repair-Dependent Operating Cost
Koichi Nakade
1 - Decision Making for the Type of Wind Turbines by
DEMATEL and FANP
Meng-Chan Hung, Amy H. I. Lee, W. L. Pearn, He-Yau Kang
A machine is assumed to consist of multiple identical main parts. During operation, parts are periodically inspected and if a part has a crack
below the threshold level then it is either repaired or replaced with a
new one. If the crack of a part is above the threshold then it must
be replaced. The part which is repaired is used with operating cost,
which is not incurred to a new part. Repair and replacement costs are
also needed for maintenance. An optimal parts repair and maintenance
policy is developed theoretically and numerically by using a Markov
decision process.
Wind energy production is a fast growing renewable energy source
in the world, and an effective use of wind turbines can enhance the
long-term energy production. In this study, a comprehensive evaluation model, which incorporates decision making trial and evaluation
laboratory (DEMATEL) and fuzzy analytic network process (FANP),
is developed to evaluate various types of wind turbines. Interactive
relationships among criteria are considered by the experts, and recommendations are provided for constructing a wind farm. A case study
implemented to examine the practicality of the model.
54
IFORS 2014 - Barcelona
2 - A Multi-Criteria Decision Making Model for Developing Solar Cells
Amy H. I. Lee, He-Yau Kang, Chun Yu Lin, Jian-Shun Chen
New product development (NPD) is an important source of competitive advantage for solar firms. Literature review and interviews with
domain experts are done first to construct a house of quality (HOQ) for
quality function deployment (QFD). Fuzzy interpretive structural modeling (FISM) is applied next to determine the relationships among the
factors, and the results are input to the HOQ. Fuzzy analytic network
process (FANP) is then used to generate the outcome for the HOQ.
The proposed model can provide a framework for helping designers to
systematically consider relevant NPD information.
3 - Combining Fuzzy Integral and DANP Model to Improve Transportation Service Quality
James Liou, Chao-Che Hsu
In this study, we propose a novel, fuzzy integral-based model to evaluate and improve the service quality of transport systems. The relations
structure between the criteria and the influential weights of the criteria is constructed with the aid of the DEMATEL and a basic form
of the ANP method called DANP. A fuzzy integral is used to aggregate the gaps with influential weights modeled by DANP. The hybrid
model remedies prior shortcomings and should be more applicable to
real-world situations. Data from Taipei city bus companies are used to
demonstrate this method.
MD-38
Monday, 14:00-15:30 - Room 214
Biomass-Based Supply Chains III
Stream: Biomass-Based Supply Chains
Invited session
Chair: Taraneh Sowlati
1 - An Optimization and Stochastic Simulation Approach for Economic Feasibility Analysis of Biofuel
Supply Chains
Jörn C. Meyer, Philip A. Hobson, Magnus Fröhling, Frank
Schultmann
Economic feasibility of fuel production from biomass depends on regional factors and on the choice of feedstocks and conversion technologies. The objective of this contribution is to demonstrate how strategic planning and uncertainty analysis can be integrated with technoeconomic modelling to support biofuel investment and commercialisation decisions. A three step approach that includes techno-economic
modelling of supply chain elements, strategic supply chain design and
uncertainty and variability analysis is developed and applied to a case
study for biofuel production in Australia.
2 - RDEA Heuristic Algorithm for the Optimal Design of
Biomass Supply Chain Networks
Konstantinos Petridis, Evangelos Grigoroudis, Garyfallos
Arabatzis
In the world literature, biomass supply chain network (BSCN) design
is based on economic (cost/profit) or other objectives. Yet, most of the
models and algorithms tend to leave out the efficiency of the solutions.
In this work we present a recursive DEA heuristic algorithm for the optimal design of BSCN. An application of the algorithm is shown on the
optimal installation of biomass facilities problem where each facility
is treated as a DMU, determining a-priori the inputs and outputs based
on which the efficiency measurement will be performed, selecting only
those DMUs with higher efficiency.
3 - Uncertainties in Forest Biomass Supply Chain for
Electricity Generation
Taraneh Sowlati
In this work, the supply chain of a typical forest biomass power plant
is optimized considering the uncertainties in different parameters. The
optimization model includes biomass procurement, storage, electricity production and ash management in an integrated framework at the
tactical level. It is applied to a real biomass power plant in Canada.
MD-40
Monte-Carlo simulation, stochastic programming, robust optimization
and a hybrid model are used to consider uncertainties in the amount of
biomass supply, its quality and cost, and electricity price in the modeling and incorporate them in the decision.
MD-39
Monday, 14:00-15:30 - Room 018
ORAHS II - Quality Improvement
Stream: Health Care Applications
Invited session
Chair: Sally Brailsford
Chair: Turgay Ayer
1 - Optimal Strategies for Hepatocellular Carcinoma
Surveillance in Hepatitis C Patients: A Societal Perspective
Turgay Ayer, Qiushi Chen, Jagpreet Chhatwal
The practice guidelines recommend surveillance for hepatocellular carcinoma (HCC), the main type of liver cancer, in high-risk hepatitis C
patients every 6-12 months. However, the optimal surveillance interval
is controversial. We present a mixed-integer programming-based approach to evaluate the cost-effectiveness of routine and dynamic policies. We found that dynamic policies outperform routine policies.
2 - Routing and Scheduling of Urban Home Health Care
Transport Systems
Christian Fikar, Patrick Hirsch
We provide a solution procedure for a real-world routing and scheduling problem in home health care motivated by challenges caused by
urbanization (e.g. congestions, limited parking spaces, staff without
driver’s permits). A transport service delivers nurses to clients and
picks them up after completion of their services. Furthermore, nurses
can also walk to their next clients. Different objective functions for
real-world instances of three Austrian cities are investigated to discuss
trade-offs and benefits of the concept.
3 - Competing on Quality: Evidence from Award Winning Hospitals in California
Bogdan Bichescu, Wei Wu, Randy Bradley
Healthcare is a highly competitive environment in which hospitals
compete against one another to both provide services to patients and
attract indispensable resources (i.e., nurses and physicians) to deliver
their services. We investigate the marketing, operational, and financial benefits associated with winning quality awards, by performing a
matching study that compares quality award-winning hospitals from
the state of California to comparable hospitals without quality awards
during the period of our study.
4 - Simulation of an Elevator Bank
Preston White
The University of Virginia Children’s Hospital is constructing a
200,000-square-foot, seven-story complex to consolidate pediatric outpatient services in a central hub for interdisciplinary care. In order to
resolve facility layout and scheduling issues prior to occupancy, we
developed a discrete-event simulation to analyze the flow of patients,
staff, and material within the complex. Central to this simulation is a
sub-model of the main transportation system—a bank of four elevators. In this paper we describe the design and implementation of the
elevator simulation.
MD-40
Monday, 14:00-15:30 - Room 019
Supply Chain Optimization
Stream: Production and the Link with Supply Chain
Invited session
Chair: Lionel Amodeo
Chair: Jonathan Oesterle
55
MD-41
IFORS 2014 - Barcelona
1 - Investigating the Relation between Product Modularity and Supply Chain Decoupling Level through MultiObjective Optimization
Metehan Feridun Sorkun, Ozgur Ozpeynirci
This study investigates the relationship between the product modularity (PM) and the organizational decoupling. Proponents of this link
assume high PM leads to less coordination cost, shorter product development, and higher flexibility. The opponents list strategic and logistics concerns; so assert the necessity of integral supply chain (SC) in
spite of high PM. These views motivate us to investigate the main explanatory of SC integration level. We develop a multi-objective MILP
program and analyze the optimal solutions at different PM levels, with
distinct supplier and module peculiarities.
2 - Operations Planning in Dynamic Production Networks
Atour Taghipour
A production network includes ensemble of organizations connected
by information, financial and physical flows. When these networks
involve independent entities without any central control unit, it is difficult to provide a near optimal plan for global system. The difficulty increases when production planning problem is considered in a dynamic
context in which information change and it is necessary to re-plan the
production of all independent companies. This research addresses the
problem of dynamic planning of production networks using a heuristic
search and linear programming.
2 - Bi-Objective Algorithm for Unidirectional Flow Path
Design
Julie Rubaszewski, Alice Yalaoui, Lionel Amodeo
3 - Numerical Analysis of Flow Time Oriented Lot Sizing
Models: A Simulation Study of a Serial Production
System
Simon Jutz, Hubert Missbauer
The flow path design is the determination of each segment direction
and the paths that will be used by vehicles in production units. Important points when designing a new network are construction costs
and the cost of its utilization. An efficient optimization method based
on ant colony optimization is developed in order to solve the case of
minimizing the total travel distance considering both loaded and empty
travels and the construction costs. These two objectives are not dependent. To ensure the efficiency of the proposed optimization method,
computational experiments are carried out.
Lot sizes for multi-stage production traditionally are determined based
on the trade-off between setup and inventory holding costs. Incorporating the impact of lot sizing on manufacturing flow times has been
performed for single-stage production. The resulting decision rules
for standard lot sizes are difficult to integrate into a multi-stage environment and seem to change certain structural insights from inventory
theory. Motivated by a practical case, we investigate this issue for a
two-stage production system by means of a simulation model with different lot sizes for the operations.
3 - Implementing Decomposition Approaches in MultiPeriod, Multi-Stage Supply Chain
Amirhossein Sadoghi, Helene Lidestam
4 - A Discrete Particle Swarm Algorithm for Solving the
JIT Part-Supplying Problem at Mixed-model Assembly Lines
Masood Fathi, María Jesús Alvarez, Victoria Rodriguez
We model the capacitated, multi-commodity, multi-period, multi-stage
facility location problem. The literature on such problem is still sparse.
However there is still room for improvement of the algorithms or finding the initial solutions for exact ones. We proposed an effective
heuristic approach based on the primal and dual and hybrid decomposition methods to solve the Large-scale linear programming. Results
show that our approach significantly improves solvability of the problem. We exemplified the supply chain of distribution and production
of forest residues are to be converted into fuel.
4 - Option Contract Performance in a Supply Chain
Alejandra Gomez Padilla, Tsutomu Mishina
This document studies a bi-directional option contract. In an option
contract a retailer may order a number of units and modify the ordered
quantity as he receives more accurate information on demand. The
modification may go in both directions, that is, it may be higher or
lower than the initial order. The purpose of this research is to analyze
the performance of this contract for the retailer, the supplier and the
chain as a unit, when it is used under several demand patterns. We
conclude on the coordination of this contract for different demand patterns and the best parameter combination.
The assembly line part-supplying problem can be defined as mixed
scheduling and decision problem so that for having a reliable part delivery schedule a number of decisions should be made. In this study
a mathematical model for the JIT part-supplying problem at mixedmodel assembly lines is introduced and due to the complexity of the
problem a discrete particle swarm algorithm is also suggested. A set
of computational experiments is carried out and the result of comparisons reveals that the proposed algorithm is efficient in term of both
provided solution and computational time.
MD-42
Monday, 14:00-15:30 - Room 215
Green Freight Transportation 2
Stream: Green and Humanitarian Logistics
Invited session
Chair: Emrah Demir
MD-41
Monday, 14:00-15:30 - Room 216
Lot-Sizing and Related Topics 3
Stream: Lot-Sizing and Related Topics
Invited session
Chair: Diego Klabjan
1 - Product Assortment and Production Planning
Luis Guimarães, Diego Klabjan, Herbert Meyr, Bernardo
Almada-Lobo
The intense competition in consumer packaged goods industry has motivated companies to expand their product lines. A wider variety tends
to satisfy more customers and attract variety-seeking shoppers. On
the other hand, the manufacturing complexity increases lead to extra
changeovers, lower productivity, higher safety stocks and more frequent stockouts. This talk considers the problem faced by a manufacturer that simultaneously makes product assortment and production
planning decisions. The goal is to analyze the trade-off between sales
revenue and its consequences in operational costs.
56
1 - A New Mathematical Formulation to Support Fleet
Management Decisions
Emrah Demir, Efstathios Dimarelis, Tom Van Woensel
The assignment of vehicles to freight shipments is investigated to propose better allocation decisions to the planners so that both operational
costs and carbon dioxide equivalent emissions can be reduced. This
approach facilitates planners to define different scenarios and compare
decisions to select the most economical fleet schedule including using
their own and chartered vehicles. We show that this approach remarkably helps logistics service providers improve their planning processes.
2 - CO2 Reduction by Using Inhomogeneous Fleets
Herbert Kopfer, Jörn Schönberger
The proposed approach aims at minimizing CO2 emissions caused by
transportation. Based on the observation that vehicles of different sizes
have different payload-dependent CO2 emission characteristics, the
option of choosing different vehicle types is added to vehicle routing
problems. Then, the total amount of fuel consumption is minimized in
dependence of the types of the used vehicles and their payload during
route fulfillment. The quantity of fuel needed to serve a given request
portfolio can be reduced tremendously by using an inhomogeneous
fleet with vehicles of different size.
IFORS 2014 - Barcelona
3 - Modal Shift and Sustainable Network Design for Municipal Solid Waste Transport Routing
Dirk Inghels, Wout Dullaert
A modal shift from road transport towards vessel or train transport can
increase the sustainability of the municipal solid waste management
process if it shows to be beneficial. The main challenge is to minimize
transport costs using vessels or trains on distances shorter than 100 km.
This problem is modeled as a Service Network Design Planning problem. We present an MILP model to solve the transport mode allocation
problem. Preliminary results show that using vessels can be beneficial
if external costs are taken into account and shipped volumes can be
increased.
4 - Critical Review of CSR Indicators on Extended Producer Responsibility
Cristobal Miralles
After some years of evolution, Reverse logistics systems are considered quite important, becoming crucial to design business processes
through a closed loop perspective that aims to restore as much value
as possible to the system. However, the clear link between Planned
obsolescence of products and Extended producer responsibility should
be carefully analyzed. This contribution makes a critical review of the
CSR indicators on this issue, proposing some useful indirect indicators
that can provide a better tracking on the environmental performance of
companies.
MD-43
Monday, 14:00-15:30 - Room 217
MD-44
4 - A Mathematical Formulation for Data Mule Scheduling in Sensor Networks
Pablo Luiz Araujo Munhoz, Philippe Michelon, Lucia
Drummond, Luiz Satoru Ochi
The Data Mule Scheduling Problem is a special case of a wireless sensor network where a special sensor (mule) is responsible for collecting
the data from other sensors. This can be applied in critical areas such as
disaster relief and military communications. The objective is minimizing the travel time while solving 3 steps of the problem: define the path
of the mule, management of speed of the mule through this path and
finally the communication scheduling between the mule and sensors.
We propose a mathematical formulation and use adapted instances of
Close-Enough TSP to validate the model.
MD-44
Monday, 14:00-15:30 - Room 218
Simulation in Management Accounting
and Management Control III
Stream: Simulation in Management Accounting and
Management Control
Invited session
Chair: Alexander Brauneis
Algorithms and Applications - 3
Stream: Algorithms and Computational Optimization
Invited session
1 - Metaheuristic to Improve Career Progression in an
Organization with N Functional Careers
João Barata, Rui Deus
Chair: Edilaine Soler
1 - Controlling Dynamical Systems with Branch-andBound
Ingmar Vierhaus, Armin Fügenschuh
We consider the optimal control of dynamical systems, given in terms
of a set of ordinary differential equations. We allow non-smooth functions in the model equation. In order to solve these problems, we reformulate the problem into a mixed-integer nonlinear optimization problem and apply a tailored branch-and-bound approach which employs
an extensive presolving bound propagation technique. This approach
has the advantage of potentially finding a proven globally optimal solution. The talk will present the approach as well as numerical results
for test instances.
2 - Interior Point Method for Solving the Maximum Loading Problem with Discrete Control Variables
Edilaine Soler, Edmea Cássia Baptista, Vanusa Sousa,
Geraldo R. M. da Costa
The problem of finding the maximum loading of a power system can be
formulated as a mixed integer nonlinear programming problem. In this
work, a function that penalizes the objective function when the integer
variables assume non-integer values is proposed. Thus, a sequence of
nonlinear programming problems with only continuous variables is obtained and the solutions of these problems converge to the solution of
the mixed integer nonlinear programming problem. The nonlinear programming problems are solved by an interior point method. Numerical
tests with the IEEE test systems are presented.
3 - Impact of Sovereign Rating Actions on Holdings
of Government Debt in Developed and Emerging
Economies
Tomasz Orpiszewski
Using a new broad dataset on holdings of government bonds in 30
countries, this article investigates the impact of sovereign rating actions on changes in bondholding positions for different investors types.
A paradox emerges with regards to investors’ risk aversion, as initial
downgrades in the Peripheral Eurozone and Safe Haven countries were
followed by a rise in demand by both foreign institutional investors and
non-resident central banks. Surprisingly, rating actions can trigger significant changes in bondholdings that are not necessarily coupled with
a change in yields and vice versa.
The matrix Q establishes the number of individuals in each functional
career and competence level in a certain organization. Q is determined
every year in order to satisfy the organization needs and provide an
equal flow of promotions in each career. N careers are evaluated by a
set of indicators using a career simulator. We use the Hellinger distance
to compare two different careers and a genetic algorithm to search the
optimal transfer of vacancies in Q within a 40 year time frame that
minimizes the overall difference in k careers intended to have similar
progression velocities.
2 - Modeling Innovation Resistance in Technology Diffusion: An Agent-Based Approach
Martin Zsifkovits, Markus Günther
Several innovation resistances influence or even hinder the adoption
process. Although widely accepted, previous models on the diffusion
of new technologies have either reduced those multiple dimensions to
only one parameter or neglected them completely. This might lead to
a pro-innovation bias. Therefore we present an Agent-Based model
considering a multi-generation and a multi-technology environment
with various market players that allows for analyzing possible influences arising from multiple innovation resistances and discuss possible
strategies and measurements for these challenges.
3 - Simulation Approach for the Distribution Strategy
and Fleet Design of a Major e-Commerce Provider in
Santiago-Chile
Cristián Cortés, Jaime Miranda, Cristobal Pineda, Pablo A.
Rey
We develop a simulation scheme to provide insights for distribution
strategy and fleet design of a major e-commerce provider, in which
customers can choose composition and delivery TW of their food and
general merchandise orders. The approach comprises 4 steps: demand
generation, VRPTW, fleet design and execution of routes with uncertainty in both travel and delivery times. The scheme allows computing
performance indicators in terms of costs and level of service of various
scenarios of operation, including reduction of delivery TW, opening a
storage center different from the original CD, etc..
57
MD-45
IFORS 2014 - Barcelona
4 - Negotiation Mechanisms, Mutually Carried out Investments, and Incentive Compatibility
Alexander Brauneis, Stephan Leitner, Alexandra Rausch
Financial resources are scarce which is why corporate budgeting needs
to allocate them efficiently. We emanate from the idea of the competitive hurdle rate (Baldenius et al 2007), and — for the case of mutually
carried out investment projects — derive an incentive compatible rule
for allocating the initial capital expenditure among departments. In
an experimental setup we assign the job of allocation to our subjects.
We investigate to what extent the optimal allocation of the initial capital expenditure (on the basis of the derived rule) can be achieved with
various negotiation mechanisms.
MD-45
Monday, 14:00-15:30 - Room 219
Stochastic Programming in Logistics and
Transportation
Stream: Stochastic Programming
Invited session
Chair: Patrizia Beraldi
1 - Robust Constrained Shortest Path Problems under
Budgeted Uncertainty
Luigi Di Puglia Pugliese, Francesca Guerriero, Michael Poss
Bertsimas and Sim (2003) showed how to efficiently solve combinatorial optimization problems under cost uncertainty, characterized by
the budgeted uncertainty set. Unfortunately, their approach does not
extend to problems with uncertain constraints, which still need specific algorithms to be handled efficiently. In this talk, we study the
constrained shortest path problems under budgeted (variable or not)
uncertainty. We discuss some differences between capacity and time
window constraints, propose dynamic programming-based algorithms
for the problems, and present computational results.
2 - A Progressive Hedging Method for the Multi-Path
Traveling Salesman Problem with Stochastic Travel
Times
Francesca Maggioni, Luca Gobbato, Guido Perboli
In this talk we propose a two stage stochastic programming model for
multi-path Traveling Salesman Problem with stochastic travel costs.
Tour design makes up the first stage decision, while recourse actions
select the best paths, minimizing the total traveling cost. To solve the
problem, we propose a heuristic method inspired by the Progressive
Hedging algorithm. New instances representing a medium-sized city
derived from the speed sensor network of Turin are introduced. The
impact of the stochastic travel time costs on the problem solution is
examined showing the benefits in solution quality.
3 - The Traveling Repairman Problem with Stochastic
Profits
Maria Elena Bruni, Patrizia Beraldi, Demetrio Laganà,
Roberto Musmanno, Francesca Vocaturo
We deal with a vehicle routing problem arising in situations where a
server visits nodes of a graph in order to collect time-dependent profits that depend on the arrival time to nodes. Not all nodes need to be
visited and the aim is to maximize the total revenue. We propose an
extension of the traveling repairman problem in which the travel times
are stochastic and the profit collected at each node depends on the uncertain arrival time. We describe a heuristic solution approach and we
present preliminary computational results.
4 - Mixed-Integer and Continuous Constrained Optimisation via Simulation
Felisa Vazquez-Abad
The problem is motivated by the optimisation a local public transportation system subject to a chance constraint. Scheduling is parametrised
by a continuous random variable. We use local gradient information
and Lagrange multipliers in combination with random (integer) search
methods in order to obtain the optimal fleet size and scheduling. The
large number of function evaluations makes Monte-Carlo simulations
58
impractical. We use the ghost method that combines discrete event
simulation max/plus modelling and Monte-Carlo filtering to do retrospective estimation of the chance constraint.
IFORS 2014 - Barcelona
Monday, 16:00-17:30
ME-01
Monday, 16:00-17:30 - Room 118
Delays and Disruptions II
Stream: Railway and Metro Transportation
Invited session
Chair: Leo Kroon
1 - Simultaneous Train Rerouting and Rescheduling on
an N-track Network: A Model Reformulation with
Network-based Cumulative Flow Variables
Lingyun Meng, Xuesong Zhou
This paper develops integer programming models for the train dispatching problem. The track occupancy is reformulated using cumulative flow variables. This technique can provide an efficient decomposition mechanism through modeling track capacities as side constraints which are dualized through a Lagrangian relaxation solution
framework. We further decompose the original complex rerouting and
rescheduling problem into a sequence of single train optimization subproblems. We present a set of numerical experiments to demonstrate
the system-wide performance benefits of the proposed models.
2 - Optimization for the Real-Time Railway Traffic Management: Case Studies in European Networks
Paola Pellegrini, Grégory Marlière, Sonia Sobieraj Richard,
Joaquin Rodriguez
Railway operations management must cope with system failures and
external disturbances that may cause delays. In heavy traffic areas,
these delays can quickly propagate. This study details the results of
a railway traffic optimization tool based on a MILP formulation. The
case studies tackled represent different European locations. These experiments are part of a task the European FP7 project ON-TIME. The
project aims to develop a prototype for a new generation of railway
traffic management systems which will increase capacity and decrease
delays for railway customers’ satisfaction.
3 - Disruption Management for High Speed Trains
Leo Kroon, Lucas Veelenturf, Joris Wagenaar, Shuguang
Zhan
In this presentation we describe a macroscopic rescheduling model for
dealing with a temporary blockage of a railway line, thereby also considering the station capacities. One important aspect to be handled in
such a situation is the uncertainty about the duration of the disruption.
Main decisions to be taken then are: which trains are to be cancelled,
in which stations trains must wait until the disruption is over, and in
which order the trains are leaving there once the disruption is over.
The model is tested on the High Speed railway line between Beijing
and Sjanghai in China.
4 - Rapid Transit Rail Systems: A Robust Design Model
with Consistent Disruption Probabilities
Ángel Marín, Esteve Codina, Luis Cadarso
A robust network design may be expensive for daily basis train operations. In practice, a) only the most likely disruptions are taken into
account and b) the fail probability depends on the train unit characteristics and the infrastructure usage level. We propose a recoverable
robust network design model as a two recourse stochastic programming problem. The proposed model has a bilevel programming structure and it is solved by a heuristic method. Computational experiments
are conducted using data drawn from RENFE (the major Spanish train
operator).
ME-02
Monday, 16:00-17:30 - Room 111
Maps, Zones and Routing
Stream: Vehicle Routing
Invited session
Chair: Marco Colombi
ME-03
1 - Map Matching and Route Optimization
Kaj Holmberg
When optimizing routes for snow removal, the problem of map matching appears when evaluating GPS-tracks recorded by vehicles, and utilizing GPS-information in graphs suitable for route optimization. The
task is to associate sequences of GPS-points to links in a graph, suitable
for optimization, and thereby obtain paths or tours in the graph. Difficulties are errors in the GPS-coordinates and possible lack of GPSpoints on short street segments. We discuss several possible methods
for off-line solution of this problem, based on heuristics, shortest paths
and rural postman problems, etc..
2 - The Hierarchical Mixed Rural Postman Problem
Marco Colombi, Angel Corberan, Renata Mansini, Isaac
Plana, Jose Maria Sanchis
We introduce the Hierarchical Mixed Rural Postman Problem where
required arcs and edges are partitioned into hierarchies. The problem looks for a minimum cost tour starting and ending at the depot
and serving all the required edges and arcs in the predefined hierarchical order. We propose a mathematical formulation to the problem
and introduce several valid inequalities. We develop a branch and cut
algorithm as well as a Tabu Search meta-heuristic. All the proposed
algorithms have been tested on existing instances for the Mixed Rural
Postman Problem suitably modified.
3 - Using Cluster Analysis to Identify STops in GPS Data
Hannelie Nel, Stephan Krygsman
The focus of transport modelling is on trips between home and work.
Employees at a university took part in a GPS tracking study, and completed a corresponding travel diary and a household travel questionnaire. A procedure, using cluster analysis, was developed to convert
the GPS records of each participant into an activity diary and a travel
diary. Trip statistics and activity statistics were compared with actual
values extracted from the completed travel diary. Home and work locations were identified without the use of additional sources and compared favourably.
4 - An Iterative Cluster-First Route-Second Approach
for a Sales Territory Design Problem with Balanced
Workload Requirements
Matthias Bender, Anne Meyer, Stefan Nickel
We consider a territory design problem in which customers are assigned to salesmen with fixed sites in a way that workload is balanced.
Since workload contains travel times, it is variable. We decompose the
problem by an iterative cluster-first route-second approach: (1) The assignment problem is solved using estimated proportionate travel times
for each customer. (2) For each territory a TSP is solved, and the results are communicated to (1) through adapted travel times. The good
estimation of travel times is an important task in practice. We evaluate
the approach on real-world instances.
ME-03
Monday, 16:00-17:30 - Room 001
Addressing Uncertainty in Passenger
Aviation
Stream: Aviation
Invited session
Chair: Amy Cohn
1 - Mechanism Design for Setting the Parameters of Traffic Management Initiatives
Vikrant Vaze, Michael Ball, Cynthia Barnhart, Prem Swaroop,
Chiwei Yan
A traffic management authority is expected to take airline preferences
into account when setting parameters of traffic management initiatives.
We propose and evaluate a Majority Judgment-based mechanism to replace the existing ad-hoc methods. It captures airline preferences via
airline-submitted grades for candidate parameter vectors. Several important sub-problems are formulated and solved, e.g., 1) optimal candidate vector generation problem, 2) optimal strategic voting problem
for the airlines, and 3) optimal airline recovery problem to evaluate
true costs of a chosen vector.
59
ME-04
IFORS 2014 - Barcelona
2 - Minimizing Aircraft Lost Time on Tarmac
Gregoire Spiers, Olivier Ratier
Actual trips include a significant amount of time lost on the tarmac
waiting for a free departure slot on the runway, representing both an
inconvenience for passengers and a cost for airlines.
It is possible to support departure managers at the airport to make the
best out of their resources by optimizing the departure sequence based
on the list of flights and their forecast take-off time. With past data
analysis, this optimization can be improved to take into account the
variability of the processes and to become less sensitive to perturbations.
3 - Can Planned Time Buffers Result in Delays?
Milind Sohoni
Given an aircraft rotation schedule, the airline builds tactical schedules
that determine the resources available to complete the various tasks
during the scheduled ground-time. While the planned aircraft rotation lays out the scheduled time buffers, the actual arrival time of the
aircraft is uncertain. Thus, the actual ground-time available could be
different from the scheduled ground-time. We address the question of
how the actual and scheduled ground-times affect the operational performance. Specifically, and intriguingly, we show that delays increase
with planned scheduled buffers.
4 - True Demand Estimation – A Novel Approach
Cheng-Lung Wu, Tomasz Drabas
In Revenue Management, a fundamental concept of true demand is defined as a set of passengers that would book a flight if there was no
capacity constraint. Traditionally, statistical methods were used to unconstrain the demand for a single booking class at a time. In this paper
we present an unconstraining model that simultaneously estimates true
demand for all the booking classes in a given market. We use Segment
Specific Cross-Nested Logit model to manage spill and recapture rates
between each booking class. Our approach significantly reduces the
error of true demand estimates.
3 - A Lagrangian Relaxation Heuristic to Determine the
Methods for used-Product Return
Jiyin Liu, Hendrik Lamsali
We consider a nonlinear integer programming model for locating usedproduct collection centres, assigning incentives for users to return their
used products, and selecting the return methods for customer zones. A
Lagrangian Relaxation (LR) heuristic is proposed to solve this complex model. While the general LR procedure is followed, the steps for
solving the relaxed problem and generating feasible solutions are carefully designed considering the problem structure. Computational tests
show that the algorithm can generate reasonably good solutions within
a relatively short computation time.
4 - The Implementation of the Discrete Artificial Bee
Colony Algorithm on a Real Facility Layout Problem
Mehmet Akif Sahman, Abdullah Oktay Dundar, Ali Alagoz
Locating machines, workstations and other elements in production facilities in a proper way is an important and complicated problem. Parameters such as material handling and movement of workers are affected as a result of layout planning as well as spaces to be utilized.
Improper applications can result in complexity and difficulty in controlling layout operations. In this paper, a layout problem of a production facility is discussed and solved by the discrete artificial bee
colony algorithm. The differences between the current layout and the
proposed layout are compared.
ME-05
Monday, 16:00-17:30 - Room 002
Fuel Logistics
Stream: Petroleum Logistics
Invited session
Chair: Rapik Saat
ME-04
Monday, 16:00-17:30 - Room 119
Supply Chain Design 2
Stream: Supply Chain Management
Invited session
Chair: Mehmet Akif Sahman
1 - Using Integrated Location Routing Approach to
Study the Effect of Vehicle Mix Strategies on Cost of
a Milk Collection Network
Mohammad Mumtaz, Muhammad Naiman Jalil, Kamran
Chatha
1 - Sufficient Density of Refueling Stations for Alternative Fuel Vehicles
Masashi Miyagawa
This paper develops an analytical model for determining sufficient density of alternative fuel stations required to achieve a certain level of service. The service level is represented as the probability that the vehicle
can make the repeated round trip between randomly selected origin
and destination. Distance is measured as the Euclidean distance. The
probability is obtained for regular and random patterns of stations. The
result demonstrates how the vehicle range, the trip length, and the refueling availability at origin and destination affect the sufficient density.
2 - Measuring the Availability of Fuelling Solutions
Emőke Ila Baladincz, Péter Bajor
Previous work on milk collection network has considered the development of vehicle routing models and heuristics to design routes that
minimize collection cost. However, there has been no effort to understand the impact of system design and operational strategies on performance of the network. We use integrated location-routing approach to
investigate the effect of various vehicle fleet mix strategies on milk
collection cost of a general milk collection network. Results show
how different vehicle mix strategies affect cost under various conditions prevalent in dairy sector.
There is a strong need to provide alternative fuel for the transportation
industry, but the structure of the infrastructure is still problematic. First
of all we have to be clear with the current retail network - what are the
characteristics of the network, how long the fuelling procedure takes,
and how to define the density of available refuelling stations. In order
to obtain the most accurate data we developed a measurement system
and exact measurement protocol. With the consideration of the measurement results about the existing system it is possible to develop the
alternative fuel network.
2 - A Location-Routing Problem for Waste Oil Collection
Fahriye Karabak, Burcu Balcik
3 - Risk Management of Rail Transport of Petroleum
Crude Oil
Rapik Saat, Xiang Liu
We consider a biodiesel production company which collects waste
cooking oil from various sources, e.g., households. The company is interested in placing collection bins to a set of community centers (CCs)
where people can bring their waste oil. We develop a mathematical
model to simultaneously determine the locations of the CCs, the number of bins to assign to each CC and the collection routes for vehicles.
We develop a simulated annealing heuristic, perform computational
experiments to evaluate the performance of our heuristic, and illustrate
our model using real-world data from the company.
60
The interest in the safety of rail transport of crude oil has intensified
in the wake of several recent severe crude oil train accidents. We develop a generalized risk analysis model to estimate railroad crude oil
transportation risk accounting for a series of principal risk factors. The
model is used to estimate nationwide crude oil transportation risk by
rail. Some results of this research have been used in evaluating the
safety effectiveness of more robust tank car designs.
IFORS 2014 - Barcelona
ME-06
Monday, 16:00-17:30 - Room 211
Passenger Transportation in Cities
Stream: City Logistics and Freight Demand Modeling
Invited session
Chair: Alok Choudhary
1 - A Survey of Travel Times at Shinjuku Skyscraper District in Tokyo
Takeshi Koshizuka
The author has been studying many urban spaces by distance distribution method which is based on the measure of the point pairs whose
distance are less than any value at all points of a given space. We can
obtain the theoretical result about low buildings, but we cannot derive
the theoretical distribution about skyscrapers. So we made a survey
about the travel times of 523 point pairs at allthe real floors in Shinjuku. Finally, with respect to travel time we conclude that Shinjuku
district is almost equivalent to the set of low buildings which have the
same total floor area as Shinjuku.
2 - A Simulation Framework for the Operational Problem
of One-Way Car Sharing Systems
Burak Boyaci, Martin Repoux, Nikolas Geroliminis
Electric vehicle sharing systems have been introduced to a number of
cities as a means of increasing mobility, reducing congestion, and pollution. One-way systems provide more flexibility to users since they
can be dropped-off at any station. However, their operation involves a
number of complexities arising from asymmetric demand. In this paper
we develop a simulation framework associated with efficient heuristics for relocation to investigate the performance of one-way systems
for different levels of flexibility and types of services (with or without
reservations) to the users.
3 - Public Transit Network Optimization and Stop Configuration
Michael Klier
Deciding on lines and frequencies is essential for planning public transit networks. In addition, the configuration of stops can also be part
of this strategic decision. Empirical studies suggest that real-time displays at stops reduce the perceived waiting time (PWT). On account of
the crucial role of PWT for mode choice, one could expect to increase
the number of transit passengers when displays at stops are available.
A model for line optimization and stop configuration is presented. It
can be used to derive an optimal configuration of stops regarding the
equipment with real-time displays.
4 - Optimizing the Shape of Rectangular Parking Lots
Based on Lot Capacity and Door Location
Letitia Pohl
Large retail supercenters provide one-stop shopping, with a huge variety of products. The convenience of parking is an important aspect
of the shopping experience. However, the volume of business dictates
a large parking lot, which translates into long walking distances. The
typical customer seeks to minimize their walking distance, often willing to spend longer driving (and possibly waiting), to achieve a slightly
closer parking spot. This paper investigates parking lot designs that
minimize walking distance by using techniques developed for designing warehouse layouts.
ME-07
Monday, 16:00-17:30 - Room 003
Multi-Level Programming and Equilibrium
Models in Electricity Markets
Stream: Equilibrium Problems in Energy
Invited session
Chair: Juan Miguel Morales
ME-08
1 - Integrating Intermittent Renewable Energy Sources
in Electricity Markets
Cristian Pelizzari, Giorgia Oggioni
The increased penetration of unpredictable renewable energy sources,
due to the 20-20-20 European targets, has significantly affected the
dynamics of electricity markets. In this paper, we investigate the effects of wind energy penetration through generation capacity expansion models. The equilibrium of the electricity market is determined
assuming that agents can be either risk-neutral or risk-averse. Models
are formulated as complementarity problems and are implemented in
GAMS. The analysis is performed on a prototype electricity market.
2 - Modeling the Impact of Imbalance Costs and Market
Design on Generating Expansion of Stochastic Units
Salvador Pineda Morente, Juan Miguel Morales
Imbalance costs of stochastic power producers due to forecast errors
have a high impact on their total profit and thus, they need to be accounted for when making investment decisions. We present a mathematical program with equilibrium constraints that incorporates both
the day-ahead and balancing markets to determine the optimal generating expansion of stochastic units. This model allows us to investigate the effect of both imbalance costs and market design on such
investment decisions. The main features and results of the models are
discussed using a 2-node example and a 24-bus case study.
3 - Transmission Expansion Planning in Electricity Markets: A Bilevel Multi-Objective Framework
Raquel García-Bertrand, Natalia Alguacil-Conde
This paper presents a multi-objective model for transmission expansion planning in electricity markets. The model simultaneously minimizes investment and congestion costs. We present a novel bilevel programming approach in which prices associated with congestion costs
are explicitly characterized as decision variables of the optimization.
Thus, expansion plans are determined by the upper-level problem with
the goal of minimizing both objective functions through the augmented
epsilon-constrained method while prices are obtained by an optimal
power flow in the lower level.
4 - A Method to Identify Competitive Wind Locations
Juan Miguel Morales, Henrik Madsen
New transmission investments are required to integrate wind resources
that are far away from the large power loads. If wind power producers
are, however, made to bear the investment costs, they may see their
competitiveness seriously impaired. Taking this potential conflict as
starting point, we present a model to decide the amount of wind resources that are economically exploitable at a given location from a
transmission-cost perspective. This model builds on stochastic optimization to account for the uncertain character of wind and has a bilevel structure to simulate market competition.
ME-08
Monday, 16:00-17:30 - Room 120
Optimal Design in Environmental
Management
Stream: Energy Economics, Environmental Management and Multicriteria Decision Making
Invited session
Chair: Eleni Zografidou
Chair: Konstantinos Petridis
1 - Optimal Design of the Renewable Energy Production
Map of Greece using a Multi-Period Goal Programming Model
Eleni Zografidou, Konstantinos Petridis, Garyfallos Arabatzis
Renewable energy sources are considered to be a clean energy form
due to the low levels of hazardous and GHG gas emissions. Nowadays, there is a noticeable switch to electrical energy production from
renewable power plants, taking into account specific environmental directives. Considering the energy needs of Greece, we suggest a mix of
different renewable energy plants and their locations in Greek Prefectures, applying a 0-1 weighted goal programming model. Finally, an
optimal design of the present and future renewable energy production
map of Greece is presented.
61
ME-09
IFORS 2014 - Barcelona
2 - Optimal Design of Capacity Market with Startup
Costs and Capacity Constraints
Marina Dolmatova, Alexander Vasin
We consider a model of electric capacity market, where demand is
given by a load duration curve and capacity constrained suppliers are
characterized by their fixed, variable, startup and shutdown plant costs.
We provide an algorithm that finds an optimal capacity structure satisfying the demand with minimal costs. We formulate sufficient conditions for perfect competition and suggest an auction design such that
there exist a dominating strategy for each supplier, and the outcome
corresponds to the optimal capacity structure.
3 - Probabilistic Pricing for Wind Farms
Natália Addas Porto, Regiane Silva de Barros, Paulo Correia
Auctions are procedures for disclosure of the market price where the
bidding strategy seeks to balance the expected benefit and the probability of winning the auction. Therefore it is necessary to express
the expected benefit and the probability of winning the auction as a
continuous function of the bid, taking as starting point the probability distribution of the net present value of the object that will be sold
which involves algebraic operations with random variables. The paper
shows the results for the wind power farm pricing.
4 - An Energy Environment Economy (3E) Model for Assessing Building Components from a Life Cycle Perspective
Giulia Sonetti, Patrizia Lombardi
We extend the life cycle assessment (LCA) method to a 3E (energy, environment and economy) model studying three hypotheses of building
components, intended as a group of elements fulfilling the same function. A green, a reverse, and a simply waterproofed roof have been
studied according to four different impact assessment methods. Afterwards, an advanced multi-criteria decision making (MCDM) method
is improved to integrate economic values. In conclusion, we try to set
a comprehensive model which could allow decision-makers to assess
LCA results with respect to economic revenues and costs.
3 - An Analysis of Deterministic Random Walks on Hypercubes using the Krawtchouk Polynomial
Takeharu Shiraga, Yukiko Yamauchi, Shuji Kijima, Masafumi
Yamashita
The rotor-router model is a deterministic process in analogy with a
random walk. It is also known by the name of deterministic random
walk, implying a deterministic version of random walk. Discrepancy
between a deterministic random walk and a random walk is intensively investigated, recently. This paper is concerned with a generalized model of the rotor-router model, which we call functional router
model, and investigates single-vertex discrepancy of the number of tokens between a functional-router model and a random walk on a hypercube, using the Krawtchouk polynomial.
4 - Compare the Ratio of Symmetric Polynomials of
Odds to One and Stop
Tomomi Matsui, Katsunori Ano
We deal with an optimal stopping problem that maximizes the probability of selecting k out of the last L successes, given a finite sequence of independent Bernoulli trials. This problem includes some
natural problems as special cases, e.g. Bruss’ odds problem, Bruss and
Paindaveine’s problem of selecting the last L successes, and Tamaki’s
problem for stopping at any of the last k successes. We show that a
threshold strategy gives an optimal stopping rule and present a tight
lower bound of the probability of winning. Our approach is based on
Newton’s inequalities and optimization.
ME-10
Monday, 16:00-17:30 - Room 122
Optimization Methods for Offshore and
Onshore Wind Farms
ME-09
Monday, 16:00-17:30 - Room 121
Stochastic and Deterministic Dynamic
Programming and its Applications 2
Stream: Dynamical Systems and Mathematical Modelling in OR
Invited session
Chair: Tomomi Matsui
1 - Dynamic Linear Bayesian Model for Inventory Optimization with Demand Forecasting
Marisol Valencia Cárdenas, Javier Diaz, Juan Carlos Correa
Morales
Inventory models including all the fixed factors are not robust to uncertainty in variables. Classical models do not have adequate structures
helping to deal with drastic changes or no data. Dynamic inventory
models are necessary to afford changes that affect planning of sales and
production. The Dynamic Linear Bayesian Model is a system which
can be used to forecast when there are few or no data or with changes
mentioned. In this work, we develop an optimal inventory model with
Bayesian demand forecasts, using probability distributions which permits finding optimal production quantities.
2 - Markov Decision Processes with Static Hidden
States and Observations
Takayuki Osogami
We study partially observable Markov decision processes (POMDPs)
with a particular structure where only a part of the state is hidden, and
the hidden part stays unchanged. We show that this structure allows
us to make the standard algorithms for POMDPs significantly more
efficient. We then discuss applications of these particular POMDPs to
the scenarios where machines estimate characteristics of humans while
providing services to those humans. A part of this research was supported by JST, CREST.
62
Stream: Optimization Models and Algorithms in Energy
Industry
Invited session
Chair: Oriol Gomis
Chair: Cristina Corchero
1 - Optimal Power Flow Tool for Mixed HVAC and HVDC
Systems for Grid Integration of Large Wind Power
Plants
Mònica Aragüés, Oriol Gomis
The parallel advances in High Voltage Direct Current (HVDC) and
High Voltage Alternating Current (HVAC) technologies are leading to
electrical systems based on AC and DC transmission. A scenario with
mixed DC and AC interconnected networks is then feasible. Specially,
if HVDC multiterminal is built for delivering the offshore power to the
AC grids. To ensure an efficient power transmission, a tool that solves
mixed optimal power flows is developed, knowing the power available
on the wind farms, the demand on the AC grids and the electrical characteristics of the network.
2 - Optimal Offshore Wind Power Plant (OWPP) Design
based on a Hybrid AC-DC Configuration
Mikel De Prada Gil, Lucia Igualada, Cristina Corchero, Oriol
Gomis, Andreas Sumper
The aim of this paper is to optimize a proposed OWPP design based on
a hybrid AC-DC topology in order to minimize its total cost. This optimal design consists in determining the optimum number and location
of AC/DC converters and collector platforms to be installed between
the AC wind turbine array and the single HVDC platform. Likewise,
the cable route connecting the WTs between each other is also optimized. Each converter is directly connected to a cluster of WTs providing a centralized control. Thereby, the individual converters of each
turbine are not required implying cost savings.
IFORS 2014 - Barcelona
3 - Techno-Economic Optimization of Offshore Grids
Hakan Ergun
In this presentation, two optimization techniques will be shown. The
first methodology optimizes the connection of multiple offshore wind
farms to the main electricity grid. The method optimizes the system
layout for the wind farms, transmission technology and the transmission system voltage. The second optimization methodology is based
on iterative combination of linear integer programming and Dijkstra’s
shortest path algorithm. Transmission layout, cable routes and transmission technology are optimized considering the spatial aspects of the
area of focus.
4 - Effects of Optimal Grouping of Wind Farms in DayAhead Markets Through an External Agent
Victoria Guerrero, Agustín Alejandro Sánchez de la Nieta
López, Javier Contreras
This paper models the optimal joint offer of several wind farms in dayahead market grouped through an external agent considering the imbalance penalty market. This problem is modeled as a stochastic mixed
integer linear one and the objective function maximizes the expected
profit of the daily operation with two kinds of offers: i) Separate wind
farm offers and ii) A coordinated wind farm offer through an external agent. A risk-hedging measure is used and a case study will be
analyzed comparing imbalances and expected profits.
ME-11
Monday, 16:00-17:30 - Room 113
Miscellaneous Topics in Combinatorial
Optimization
Stream: Combinatorial Optimization
Invited session
Chair: Michele Monaci
1 - Self-Splitting Tree Search in a Parallel Environment
Matteo Fischetti, Michele Monaci, Domenico Salvagnin
Parallel computation requires splitting a job among a set of processing
units called workers. Tree search algorithms are particularly suited for
being applied in a parallel fashion, as different nodes can be processed
by different workers in parallel. We propose a simple mechanism to
convert a sequential tree-search code into a parallel one. In the new
paradigm, called SelfSplit, each worker is able to autonomously determine, without any communication with the other workers, the job parts
he has to process. Computational results are reported.
2 - The Split Delivery Vehicle Routing Problem
Hande Yaman
The split delivery vehicle routing problem is a relaxation of the classical capacitated vehicle routing problem where the demand of a customer can be split and delivered using multiple vehicles. We try to
solve this problem with a formulation using variables that do not carry
a vehicle index. This formulation may have solutions where customer
nodes act like depots at which several vehicles arrive and exchange
loads. We try to avoid these solutions using cutting planes or by extending the formulation locally with vehicle indexed variables. We
report some preliminary computational results.
3 - On Two-Branch Split Cuts
Sanjeeb Dash, Oktay Gunluk, Diego Moran
In this talk, we present some properties of two-branch split cuts, which
generalize the split cuts of Cook, Kannan and Schrijver, and were studied by Li and Richard (2008). In particular, we show that the closure of
a polyhedral set with respect to two-branch split cuts is a polyhedron.
Furthermore, we use this result to show that the quadrilateral closure of
the two-row continuous group relaxation – the set of points satisfying
all cutting planes obtained from maximal lattice-free quadrilaterals –
is a polyhedron.
ME-12
4 - A Divide-and-Conquer Heuristic for the Minimal
Steiner Tree Problem
Badri Toppur
We seek the Steiner Minimal Tree on the Euclidean plane using a
divide-and-conquer principle. After a lexicographic sort, the set of
terminal sites is divided into subsets using recursive division. These
subsets contain three, four or five vertices in each set. The optimal
Steiner tree length and topology for each subset are calculated using
an exponential time exact algorithm that now takes constant time. All
the primary bridges between the small trees have been tried to find the
best ones. The search for the best secondary bridges is in progress.
The cycles will lead to the best topology.
ME-12
Monday, 16:00-17:30 - Room 004
Graphs and Networks IV
Stream: Graphs and Networks
Invited session
Chair: Chunhui Lai
1 - Calculating the Network Complexity Index in Directed Acyclic Networks
Bajis Dodin
Directed Acyclic Networks (DANs), known also as diagrams, such
as project networks, are useful models for many decision problems.
Analysis and optimization methods of these models require the determination of the number of paths, criticality of the activities/links, and
complexity index of such DANs. In this paper, procedures are developed to calculate these quantities for any DAN in a linear order of the
number of nodes, O(N), where N is the number of nodes in an Activityon-Arc representation of the DAN. Computational work is provided to
illustrate the proposed procedure.
2 - A New Technique of Embedding of Binary Trees into
Hypercubes
Kamal Kabyl, Abdelhafid Berrachedi
The study of embedding of trees in the hypercube has received much
interest these later years. The problem consists of giving the smallest
dimension of the hypercube in which a given tree T is embeddable.
In this paper, we derive a new technique for the determination of the
cubical dimension of several families of binary trees. Furthermore, by
using this technique we prove that several balanced binary trees satisfy
the conjecture of Havel which states that every balanced binary tree
with 2 to the power of n vertices is embeddable in the hypercube of
dimension n.
3 - Chordal-(k,l) and Strongly Chordal-(k,l) Graph Sandwich Problems
Sulamita Klein, Fernanda Couto, Luerbio Faria, Sylvain
Gravier
In this paper we classify the complexity of graph sandwich problems
when property phi is to be a (strongly) chordal-(k,l)-graph, for all k, l.
We prove that strongly chordal-(0,k), k at least 3 and strongly chordal(k,l), for k, l at least 1, graph sandwich problems are NP-complete.
We also prove the NP-completeness for chordal-(0,k), k at least 3 and
chordal-(k,l), k at least 1,l at least 2 and for k at least 2, l at least 1
graph sandwich problems. Moreover, we prove in P: chordal-(0,k),
chordal-(k,0), strongly chordal-(0,k) and strongly chordal-(k,0) graph
sandwich problems for k=1,2.
4 - Some Problems on Paths and Cycles
Chunhui Lai
In 1976, Thomassen conjectured that every longest cycle in a 3connected graph has a chord. In 1979, Kotzig conjectured that there
exists no graph in which each pair of vertices is connected by a unique
path of length k (larger than or equal to 3). In this talk, some results on
these problems and related conjectures are summarized.
63
ME-13
IFORS 2014 - Barcelona
ME-13
Monday, 16:00-17:30 - Room 123
Project Scheduling 1
Stream: Scheduling
Invited session
Chair: Carlos Cardonha
1 - Project Scheduling using Buffers under Consideration of Psychological Effects of Cutting Down the
Original Estimations
Dorota Kuchta
Each time we are dealing with project scheduling we are facing psychological problems with time estimations and their relevance to future
actual activity realization times. Sometimes the estimations given by
future activity executors are cut down by project managers, sometime
left unchanged. The advocators of cutting them down attach a importance to the so-called student effect, causing that the work is delayed
until the activity completion deadline is very close, independently of
how far in time this deadline has been set. In this paper the estimations
of activities duration are modeled.
2 - Robust Project Scheduling at a Large IT Services Delivery Organization
Elvin Coban, Aliza R. Heching, John N. Hooker, Alan
Scheller-Wolf
We consider a practical project scheduling problem at a large IT services delivery organization with cross-trained employees, heterogeneous projects, schedule disruptions, and service quality guarantees.
Durations of subtasks, disruptions, and project arrival times are uncertain. Our goal is to identify an effective scheduling of project subtasks
and assignments to each employee. We capture uncertainties in a robust scheduling model by uncertainty sets using logic-based Benders
decomposition.
3 - A Framework of Project Management Methods to use
the Resource-Constrained Project Scheduling Problem
Shruthi S Kumar
The resource-constrained project scheduling problem (RCPSP) has
been studied and improved for decades now. Nevertheless, applied resource scheduling has still been identified as one of the most occurred
planning problems in project management. In this talk we will present
a framework of management methods for a structured determination
of the formal optimization model parameters out of unstructured management information. Based on a case study we will show how this
framework can be extended to support also a more advanced versions
of the RCPSP with flexible resource profiles.
4 - The Online Resource Constrained Project Scheduling Problem with Bounded Multitasking
Carlos Cardonha, Ricardo Herrmann, Victor Cavalcante
The Resource Constrained Project Scheduling Problem with Bounded
Multitasking (RCPSPBM) is about the assignment of service requests
to analysts with varying levels of expertise and bounded multitasking
capacity. An optimal scheduling plan minimizes penalties originated
from due dates violations and cognitive overheads, which occur whenever analysts work on two or more requests simultaneously. We propose a MILP-based algorithm for the online version of the RCPSPBM
and show with the support of computational experiments on real-world
scenarios that it outperforms algorithms currently in use.
1 - Analysis of Technical Efficiency and Scale using
Time Series in Higher Education Institutions by
Means of Window Analysis DEA
Gonzalo Eduardo Campos Hernández, Marcela
Gonzalez-Araya
Today the concern of most advanced countries to improve the efficiency and effectiveness of the Universities is evident. In Chile, this
topic is not properly studied. This paper develops a new method that
assesses the evolution of technical efficiency and scale of a Chilean
university, through a time series (nine years). Three methods for selecting variables over time, which led to better discriminate the DMUs
in the study period were created. Then DEA Window Analysis models, CCR and BCC, were applied, both with output, considering the
efficiencies of scale and technological change (IPM).
2 - A Comparative Analysis of the Treatment of Chronic
Obstructive Pulmonary Disease Episodes
Maria Portela, Emmanuel Thanassoulis, Mike Graveney,
Mike Graveney
Chronic obstructive pulmonary disease (COPD) is characterized by a
largely irreversible obstruction of the airways, and is one of the leading
causes of chronic morbidity and mortality worldwide. This paper investigates the efficiency of hospitals in handling this disease, through
an analysis of 900 episodes pertaining to 500 patients. This analysis compares the length of stay of episodes, when the medical conditions of the patient are accounted for through some surrogate measures. DEA is used in this comparison exercise, through a non-oriented
model.
3 - Assessing the Effectiveness of Noncommunicable
Diseases Prevention and Control Using Data Envelopment Analysis: An International Comparison
Carla Amado, Sérgio Santos, Ana Cristina Nascimento
Noncommunicable diseases (NCDs) are leading causes of death worldwide. For policymakers the prevention and control of these diseases is
fundamental to ensure an effective management of healthcare systems.
The main purpose of this paper is to explore the potential of using Data
Envelopment Analysis (DEA) to assess the effectiveness of healthcare
systems in preventing and controlling NCDs. To this purpose, data
from 27 OECD countries has been used. Our results demonstrate the
potential strategic role of DEA for an effective use of the available
resources in NCDs prevention and control.
4 - Benchmarking Portuguese Hospitals through a web
based Platform (HOBE)
Ana Camanho, Maria Portela, Diogo Borges, Luiz Lopes,
Sofia Silva, Ricardo A. S. Castro
This paper describes an internet platform, called HOBE, which compares public hospitals in Portugal. The platform allows benchmarking
hospital services from a managerial perspective. Aggregate performance indicators are constructed for hospital services based on Data
Envelopment Analysis cost models. Aggregate hospital efficiency is
also addressed, where we propose a model to aggregate the performance of a set of hospital services into a single performance measure
at the hospital level. Some results are presented for the trial years of
2008 and 2009.
ME-15
Monday, 16:00-17:30 - Room 125
ME-14
Monday, 16:00-17:30 - Room 124
DEA in Health and Education
Stream: DEA Applications
Contributed session
Chair: Carla Amado
64
Pricing and Strategic Consumer Behavior
in Revenue Management
Stream: Revenue Management II
Invited session
Chair: Rachel Zhang
Chair: Shining Wu
IFORS 2014 - Barcelona
ME-17
1 - Bundle Pricing from Sales Data with Copula Inference
Pavankumar Murali, Wei Sun, Anshul Sheopuri
2 - Counting Arithmetic Progressions using Semidefinite Programming
Erik Sjöland
Letham et al. (2013) considered a bundle pricing scenario where bundle discount did not exist in the sales data and proposed an inference
procedure with copula to model the joint distribution of consumer valuations for the individual items. In this work, we focus on the case
with pre-existing bundle discounts in the sales data. This introduces
biases in estimation and dramatically increases computational complexity, making it impractical for real-world applications. We compare
several heuristics and propose a procedure which approximates the true
joint distribution and is tractable.
One of the most challenging problems in Ramsey theory is to count the
minimal number of monochromatic arithmetic progressions in a group
colored in c colors. Based on Putinar’s positivstellensatz it is possible
to rewrite the problem as a semidefinite program. Inspired by methods
developed by Klerk, Pasechnik and Schrijver we reduce the size of the
problem by understanding its symmetries. The approach is applicable
for any group, including non-abelian groups. We present novel results
for several infinite families of groups.
2 - Pricing of Conditional Upgrades in the Presence of
Strategic Consumers
Izak Duenyas, Yao Cui, Ozge Sahin
In this paper, we study a conditional upgrade strategy that has recently
become very common in the travel industry. After a consumer makes
a reservation for a product (e.g. a hotel room), she is asked whether
she would like to upgrade her product to a more expensive one at a discounted price. We analytically analyze this policy and identify when
offering such conditional upgrades can be beneficial for the firm and
how to set prices for the conditional upgrade. Our results indicate offering conditional upgrades can compensate for a firm’s lack of ability
to set its prices optimally.
3 - Price Drop Guarantee in the Context of Limited Inventory
Dinah Cohen-Vernik, Amit Pazgal
Have you ever purchased an item only to notice a short while later
that its priced has dropped? Many retailers (e.g. Amazon, Best Buy,
Neiman Marcus) offer customers to refund the price difference if the
price drop occurs within a specified period of time. Despite the popularity of such policy, the scope of existing research is surprisingly
limited. In this paper we develop analytical multi-period model to analyze price drop guarantee policy in the context of limited inventory, and
allow the retailers to choose the optimal percentage of refund, contrary
to a common assumption of a full refund.
3 - Linear Matrix Inequalities and Spectrahedra in the
Plane
Daniel Plaumann
We study the problem of characterising the plane spectrahedra, which
are the convex semialgebraic subsets of the real plane described by
linear matrix inequalities and therefore the two-dimensional domains
of semidefinite programs. We present an approach to compute such
descriptions numerically via polynomial homotopy continuation methods. (Based on joint work with Anton Leykin)
ME-17
Monday, 16:00-17:30 - Room 005
Global Optimization and Applications in
Development III
Stream: Global Optimization
Invited session
Chair: Herman Mawengkang
Chair: Gerhard-Wilhelm Weber
4 - The Reference Effects on a Firm’s Dynamic Pricing
and Inventory Strategies with Strategic Consumers
Shining Wu, Rachel Zhang, Qian Liu
1 - An Interactive Approach for Solving Sustainable Production Planning Model of Crude Palm Oil Industry
Hendaru Sadyadharma, Herman Mawengkang
We consider a retailer that sells the same or different versions of the
product season after season. At the beginning of each season (stage 1),
the firm places an order and sells the product at the full price. As the
sales unfold, the firm has an opportunity to mark down the price (stage
2) to match supply with demand. However, the retailer’s markdown
strategies in past seasons give strategic consumers an incentive to time
their purchases in future seasons. We characterize the properties of the
optimal ordering and markdown decisions and show some interesting
properties of the decisions.
Despite obvious benefits of crude palm oil industry for economic development, it contributes to environmental degredation. This paper
addresses a multi-objective stochastic programming model of the sustainable production planning of crude palm oil. The model takes into
account conflicting goals such as return, financial risk and environmental costs. The uncertainty comes from the price of crude palm oil. At
the start, two single objective models are formulated: a maximum expected return model and a minimum financial risk (pollution penalties)
model.
ME-16
Monday, 16:00-17:30 - Room 127
Copositive and Polynomial Optimization
IV
Stream: Copositive and Polynomial Optimization
Invited session
Chair: Cordian Riener
1 - A Semidefinite Hierarchy for Containment of Spectrahedra
Kai Kellner, Thorsten Theobald, Christian Trabandt
We study the computational question of whether a given spectrahedron
(or polytope) is contained in another one. To overcome the situation
that the containment problem for spectrahedra is co-NP-hard, relaxation techniques are of particular interest. Based on a reformulation as
a polynomial optimization problem, we provide a hierarchy of sufficient semidefinite criteria for the containment problem. The hierarchy
is at least as powerful as existing criteria for containment. Finally, we
demonstrate the effectiveness of the approach by providing numerical
results.
2 - An Optimization Model for River Water Quality Problem
Syafari Syafari
Rivers water quality is increasingly under threat from different pollutants, which include conventional pollutants (organic matter and inorganic nutrients) and hazardous substances (organic contaminants and
heavy metals). In this paper dynamic integrated modelling of basic
water quality and organic contaminant fate and effect in rivers are explored. A basic river water quality model and organic contaminant
submodel were developed as an optimization problem and then linked
in order to estimate the wastewater removal efficiencies for discharge
site.
3 - An Improved Iterative Approach for Incomplete Dependent Variables
Sampe Simangunsong, Herman Mawengkang
It is common in some applications that we encounter missing data
problems. Standard ad hoc missing value imputation methods invariably fail to deliver efficient and unbiased parameter estimates. The
typical imputation approach is to assume the blank fields take some ad
hoc (subjective) value. However, this approach fails to deliver efficient
and unbiased parameter estimates. This paper proposes an improved
iterative maximum likelihood based procedure to impute ’most likely’
values for the missing data. This approach could generate fitted values
for the missing data.
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ME-18
IFORS 2014 - Barcelona
4 - An Improved Direct Search Method for Solving Land
use Management Problems
Suryati Sitepu, Siti Rusdiana, Herman Mawengkang
Land is used to meet a multiplicity and variety of human needs and
to serve numerous, diverse purposes. Our study is focused finding an
optimal land/resources portfolio composition through time, in the presence of future market uncertainty. In this paper we formulate a mixedinteger nonlinear programming model, which takes into account the
market value of revenues accruing from the land in different states. In
order to take into account the non-constant incremental benefits accruing from different land allocations. This model is applied to land
management problem in Banda Aceh, Indonesia.
based on the Hausdorff distance for approximation of the Pareto critical set was proposed in 2013 along with a globally convergent method
for bi-objective optimization problems. Now, we present a new globally convergent method for multiobjective optimization problems under a suitable Lipschitz condition.
ME-19
Monday, 16:00-17:30 - Room 128
Retail Distribution and Replenishment
ME-18
Monday, 16:00-17:30 - Room 112
Surrogate-Assisted Multiobjective
Optimization II
Stream: Multiobjective Optimization - Theory, Methods
and Applications
Invited session
Chair: Jussi Hakanen
1 - Parallel Hybrid Multiobjective Derivative-Free Optimization in SAS
Steven Gardner, Joshua Griffin
We present enhancements to a SAS high performance procedure for
solving multiobjective optimization problems in a parallel environment. The procedure, originally designed as a derivative-free solver
for mixed-integer nonlinear black-box single objective optimization,
has now been extended for multiobjective problems. In the multiobjective case the procedure returns an approximate Pareto-optimal set
of nondominated solutions to the user. We will discuss the software
architecture and algorithmic changes made to support multiobjective
optimization and provide numerical results.
2 - A Simple Framework for Parallel Multi-Objective Optimization using JAVA
F. Antonio Medrano, Richard Church
Solving multi-objective combinatorial optimization problems can
quickly become computationally intractable when applied to big data.
Top MIP solvers have parallelism built-in, but specialized solution algorithms are typically programmed serially. Java 7 provides a new
concurrency package that allows for simple conversion of a serial algorithm to parallel, which is particularly well suited to approaches for
finding the supported Pareto front of a multi-objective optimization
problem. These methods, along with extensions for also finding unsupported Pareto solutions, are discussed.
3 - Multiobjective Emergency Room Capacity Planning
using Simulation Goal Programming and Response
Surface Methodology
Felipe Baesler, Oscar Cornejo
This paper presents the results of a real life emergency room case study
in Chile that was modelled using discrete event simulation. The objective was to find the best combination of human and physical resources
that are necessary for an expansion of 40% in demand, maintaining
the current patient’s waiting time. Four different objectives were considered in the analysis using a goal programming optimization model.
This model was used in combination with response surface methodology to perform an optimization iterative process and determine the
best combination of resources.
4 - A Globally Convergent Method for Approximating the
Pareto Critical Set of a Multiobjective Optimization
Problem with any Number of Objectives
Markus Hartikainen, Alberto Lovison
In the 1970s, Prof. S. Smale combined dynamical systems and multiobjective optimization to define the Pareto critical set (a generalization
of the critical point in calculus) and to extend the Morse’s theory to
vector functions. Using these ideas, a global convergence criterion
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Stream: Demand and Supply Planning in Consumer
Goods and Retailing
Invited session
Chair: Thomas Wensing
1 - Multi-product Joint Replenishment Model with Substitution
Mohamed Kharbeche, Bacel Maddah, Shaligram Pokharel,
Ahmed Ghoniem
We propose a novel model for the joint replenishment model with
substitution for multiple products. For fast moving consumer goods
that have a relatively deterministic demand, we determine the ordering quantities for each product taking into consideration substitution
between them. In particular, once the demand is partially met and the
total cost associated with the delivery, holding, and shortage of the
products is minimized, we show that substitution between products
saves in the fixed ordering cost and the holding cost.
2 - Impact of Case Pack Sizes on Retail Instore Logistics
Systems
Heinrich Kuhn, Michael Sternbeck, Thomas Wensing
Case pack sizes influence the performance of retail instore logistics
systems in several ways: They put a constraint on the possible replenishment doctrine and thus pre-determine inventory levels and order quantities, they cause efforts for searching and picking when the
shelf is stocked, and finally, they may cause additional handling efforts
if there are excess items that do not fit onto the shelf. We present a
Markov chain model to analyze the impact of case pack sizes on the
performance of instore logistics. We illustrate scope and benefits on
basis of a real world data set.
3 - Assignment of Transport Jobs to Multiple Contract
Carriers
Thomas Wensing
A manufacturing company employs multiple carriers to ship their
goods from storage points to the customers. Each carrier is contracted
to handle a certain percentage of the total transport volume within a
larger time span, e.g., a month. We examine the problem of assigning transport jobs on a daily basis so that the long-term percentages
are satisfied as good as possible in various dimensions, e.g. revenue,
mileage, number of stops. The problem is closely related to the agent
bottleneck generalized assignment problem. We examine runtimes and
solution quality on basis of real-world data sets.
ME-20
Monday, 16:00-17:30 - Room 129
Managing Risk in Energy Storage and
Trading
Stream: Stochastic Optimization in Energy
Invited session
Chair: Nils Löhndorf
IFORS 2014 - Barcelona
1 - Risk-Sensitive Gas Storage Valuation under a Price
Process with Long and Short term Dynamics
Nils Löhndorf, David Wozabal
We consider the problem of gas storage valuation under a SchwartzSmith two-factor gas price process where risk is controlled by the conditional value at risk (CVaR). To solve the stochastic-dynamic decision
problem, we propose an approach based on approximate dual dynamic
programming that combines efficient discretization of the price process
with learning the optimal policy. We then compare the stochastic value
of storage with the (rolling) intrinsic value, study the influence of the
CVaR on profit distribution and policy, and discuss the effect of time
granularity on the value of storage.
2 - Quantile Optimization in Electricity Trading in the
Presence of Storage with Heavy-Tailed Prices
Ricardo Collado, Warren Powell, Jae Ho Kim
We consider the problem of electricity trading in the presence of storage, where electricity prices are heavy-tailed with infinite variance.
In this case traditional stochastic dynamic models relying on optimizing the expectation fail. Instead, we propose a quantile optimization
model that avoids many of the pitfalls of expectations in a heavy-tailed
environment. To cope with this, we develop a provably convergent algorithm for computing the quantile of a continuous random variable
that does not require the existence of expectation or storing all of the
sample realizations.
3 - Bidding Strategies in Electricity Markets with Long
and Short Term Objectives
Enrique Munoz de Cote
We present ColdPower, an autonomous energy retailer (broker agent)
in a smart grid environment whose task is to provide energy to consumers through tariff offerings, and then manage its consumer portfolio loads by trading in a wholesale market. The main focus of this
work is on the broker’s bidding strategy in the day-ahead (wholesale)
market. In particular, we formulate the problem as a Markov decision
process with a three-fold objective: i) to buy energy in the wholesale
market at low prices (long-term objective), ii) satisfy energy demands
(short-term objective) and iii) balance supply.
4 - Models for Optimizing Market Bids from Hydroelectric River Chains
Faisal Wahid, J. Frederic Bonnans, Andy Philpott
We consider the problem of offering energy to an electricity market
from a chain of hydroelectric generation plants with a single operator,
but situated on a cascaded river system. In each trading period, the
offers with prices below the market clearing price are dispatched and
paid at that clearing price. We consider the multiple period and plant
problem in uncertain reservoir inflows and prices. This can be approximated as a linear stochastic control problem and solved through ADP
and SDDP methods. We will present some simple models with examples of how these can be applied.
ME-21
Monday, 16:00-17:30 - Room 006
Optimization Modeling Applications in Air
Transportation
Stream: Optimization Modeling in OR/MS
Invited session
Chair: Kaan Aliefendioğlu
ME-22
2 - Operations Research Air Traffic Management (ATM)
of the Future: A Support System for Free Flight Concept
Charis Ntakolia, John Coletsos
We transform the ATM system from ’airport’ to ’airplane’ centered by
developing a mathematical model in order to: (i) support free flight
concept, (ii) prioritize airline preferences, (iii) distribute fairly groundholdings and air delays, (iv) relax the existing distance limits between
airplanes since the human factor has been annihilated, (v) increase air
sectors’ capacity, (vi) avoid congestions and adverse weather, and (vii)
increase safety and efficiency. The formulation aids to decrease computational efforts and problem’s complexity, and to increase decision
making flexibility.
3 - Robust Operation Model for Airline Ticket Distribution Channels with Uncertian Market Demands
Rong HU
Airlines are attempting to shift consumers from traditional booking
channels to more cost-effictive online channel. The paper develops a
robust operation model of airline ticket distribution channels with uncertain market demands in traditional and online channels. What airlines pursue is to minimize the total channels cost. Uncertain demands
are expressed as a scenario set with given probability, and the robust
operation model is set up by using the robust optimization based on
scenario analysis. The results showed that the model proposed is robust to uncertain demands by a numerical example.
4 - A Mathematical Programming Approach to Aircraft
Maintenance Scheduling
Kaan Aliefendioğlu, Fadime Üney-Yüksektepe
Aircraft maintenance scheduling is a complex problem with hard restrictions and a changeable environment. In this study, a mathematical programming based approach is proposed to solve a real-life problem of Turkish Technic. Using past data, different scenario analyses
are performed to test the accuracy and applicability of the developed
model. In conclusion, a convenient method will be suggested to the
companies to efficiently plan their aircraft maintenance.
ME-22
Monday, 16:00-17:30 - Room 007
Machine Learning in Healthcare
Stream: Health Care Data Analytics
Invited session
Chair: Samuel Buttrey
1 - Application of an HIV Risk Scorecard Model to Track
Changes in Risk Profile of Demographic Characteristics using Antenatal HIV Seroprevalence from 2001
to 2010
Wilbert Sibanda, Philip Pretorius
A thorough understanding of causal relations based on antenatal HIV
seroprevalence data is paramount to the elucidation of HIV/AIDS
mechanism and disease etiologies. The antenatal data obtained from
each pregnant woman contains a number of demographic characteristics. In this research we aim to develop HIV risk scorecards for
each year from 2001 to 2010 to investigate the changes in weightsof-evidence and information values as measures of risk of acquiring an
HIV infection. This work is based on the research supported by the
National Research Foundation of South Africa (Grant no. 86946).
1 - Solving the Airspace Track/Level Scheduling Problem
Mona Qablawi, Mohamed Kharbeche, Ghada Allowh,
Abdelmagid S. Hamouda, Ameer Al-Salem
2 - Data Mining Application for Blood Consumption
Forecasting in a Private Hospital
Saliha Karadayı, Aydın Tanrıverdi
We consider a real-life scheduling problem that consists in optimizing
the track and level assignments at the airspace after disruptions. By
ensuring the minimum separation time between any consecutive and
nonconsecutive flights on the same track and level, the objective aims
at determining alternate flight schedules with minimal changes from
the original schedule. We propose linear and nonlinear models that
were modeled using AMPL and solved by the linear solver CPLEX
and the nonlinear solver KNITRO. To compare the performance of
both solvers, random generated experiments were conducted.
Both the available huge amount of data and the urgent need of extracting a meaningful knowledge have increased the data mining’s importance. In the recent studies, the data mining healthcare applications
have become more of an issue owing to the healthcare activities’ own
vital significance such as immediate blood inventory requirements in
hospitals. In this study, we investigated the hospitals’ blood bank demands in order to forecast the successor blood consumptions. According to this blood consumption prediction, we generated three and six
months plans by using dynamic programming.
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IFORS 2014 - Barcelona
3 - Correlating Influenza Prevalence with Twitter Mentions of Flu
Samuel Buttrey
The Twitter micro-blogging service generates hundreds of millions of
messages a day. In this paper, we examine a 1% sample of Twitter
messages for incidence of the words "flu" or "influenza" in Englishlanguage messages originating in the United States. This incidence
rate is compared to the actual prevalence of flu as reported by the Centers for Disease Control.
Our sample of about 18 months of data occupies thousands of files and
requires on the order of 10TB of disk space. Some of the practical difficulties associated with handling and analyzing data of this magnitude
are addressed.
4 - Precipitation Prediction by Hidden Markov Models
Inci Batmaz, Nevin Sivrikaya, Ceyda Yazici, Ceylan
Yozgatligil
Recently, we have been experiencing extreme weather events such as
floods or droughts frequently because the climate change is in effect.
As a result, precipitation forecasting has become important matter for
both managing water resources efficiently and preventing disasters beforehand. There exist several forecasting methods used for this purpose such as regression models, time series models, neural networks
and MARS. In this study, we propose to use Hidden Markov Models (HMMs) to developed precipitation models for the case of Turkish
data.
ME-23
Monday, 16:00-17:30 - Room 008
Behavioural Issues in Modeling and
Simulation
Stream: Behavioural Operational Research
Invited session
Chair: Stewart Robinson
1 - Models, Optimality, Experts and Alternatives
Julian Scott Yeomans
Optimization models remain a core tenet of "hard" OR. In real-world
mathematical programming applications, some researchers point to expert modellers’ innate feel in solving problems, while others highlight
that modellers are frequently ignorant of their own ignorance. Can
these diametrically competing perspectives be effectively reconciled
so that OR modelling can remain central to supporting the decisionmaking process? One practical approach is modelling-to-generatealternatives (MGA). In MGA, numerous alternatives that provide very
disparate perspectives to the problem are created.
2 - Learning from Discrete-Event Simulation: Exploring
the High Involvement Hypothesis
Tom Monks, Stewart Robinson, Kathy Kotiadis
We detail a laboratory experiment to test learning in discrete-event simulation studies, identify mechanisms that explain how involvement in
model building or model reuse affect learning and explore the factors
that inhibit learning from models. Measurement of learning focuses
on the management of resource utilisation in a case study of a hospital emergency department and through the choice of scenarios during
experimentation. Findings suggest that there may be a learning tradeoff between model reuse and model building when simulation projects
have a fixed budget of time.
3 - Generating Insights: Experimental Study on the Effectiveness of Simulation Models in Creative Problem Solving
Anastasia Gogi, Antuela Tako, Stewart Robinson
There is no empirical evidence to support claims that simulation models are beneficial in generating insight. A laboratory experiment is
designed to examine which features of Visual Interactive Modelling
and Simulation, animation, statistics or none, support insight generation. The task requires participants to find solutions to a model of the
UK’s NHS111 service, a telephone service for urgent health care. Performance is measured based on whether insights occurs and the time
taken. This research contributes towards a better understanding of how
simulation models support decision-making.
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4 - Impacts of Mobile Internet on Customer Behavior
Yubo Chen, Liu Yang
In this paper we study how mobile internet affects customer behavior. The fast growing mobile internet is becoming a driving force to
shift the marketplace. Based on the data from a leading Chinese online retailer, we investigate how mobile internet influences customer
engagement and purchase behaviors in the online markets.
ME-24
Monday, 16:00-17:30 - Room 212
Preference Learning IV
Stream: Preference Learning
Invited session
Chair: Michael Rademaker
1 - Checking Classifiers Sensitivity to Non-Monotone
Noise
Irena Milstein, Arie Ben David, Rob Potharst
Dealing with noisy data sets is a major concern in data mining, and
monotone classifiers are no exception. Since there have been no comprehensive reports so far about the sensitivity of monotone and nonmonotone classifiers to non-monotone noise, we have developed a
novel algorithm which generates monotone data sets with varying levels of non-monotone noise. Using these data sets we check the effects
of this type of noise on the accuracy of several well known classifiers.
The accuracy is measured by different metrics, like accuracy, Cohen’s
Kappa, and the area under the ROC curve.
2 - Alternative Decomposition Techniques for Label
Ranking
Massimo Gurrieri, Philippe Fortemps, Xavier Siebert
In this work we propose some alternative reduction techniques for label
ranking that, similarly to the standard reduction technique, decompose
the original problem into binary classification related to pairs of labels.
The proposed reductions aim at taking into account label correlations
during the learning process to improve the classification performance,
while limiting computational complexity.
3 - Efficient Label Tree Structures for Top-k Classification
Krzysztof Dembczynski, Arkadiusz Jachnik
In many multi-class classification problems we are interested not only
in the most probable class, but also in the list of top k classes. For
example, the information or image retrieval systems usually present
a list of the most relevant documents or images. Since many of the
modern classification applications concern thousands or even hundred
thousands of classes, we need to rely on fast algorithms for these problems. Label tree classifiers belong to the most efficient approaches.
We discuss in the talk how this approach can be used for delivering the
top-k class predictions.
4 - Looking for the Right Noise: A Decision Rule as a
Maximum Likelihood Estimator.
Michael Rademaker, Bernard De Baets
More than 200 years ago, Condorcet examined voting rules as maximum likelihood estimators, for a specific noise function in the setting
of a limited number of candidates. Almost 20 years ago, Young extended his work to an arbitrary number of candidates, identifying Kemeny’s method as the solution. We will examine a voting rule based
on stochastic dominance from this perspective. This will be done by
attempting to construct a noise model for which the rule is a maximum
likelihood estimator. If such a noise model can be constructed, we will
assess whether it can be considered reasonable.
IFORS 2014 - Barcelona
ME-25
Monday, 16:00-17:30 - Room 009
Optimization and Mathematical
Economics
Stream: Mathematical Economics
Invited session
Chair: Maria Carmela Ceparano
1 - Methods of the Parametric Control Theory for Testing
Mathematical Models of Macroeconomic Systems
Abdykappar Ashimov, Yuriy Borovskiy
Within the framework of solving the problem of verification of mathematical models the paper for the first time proposes an algorithm for
testing macroeconomic models for the possibility of their practical application including methods for estimating: (i) structural stability of
dynamical model, (ii) values of stability indicators of the mapping defined by model & (iii) stability of the differentiable mapping defined by
model. There are presented examples of testing of (econometric, computable general equilibrium, dynamic stochastic general equilibrium)
models based on proposed algorithm.
2 - On Vertical Separated Equilibrium for Two-Stage
possibly Discontinuous Games
Maria Carmela Ceparano
ME-27
1 - On Geometric Mean Generated Weights in Interval
AHP
Jiri Mazurek
Since 1980s the analytic hierarchy process (AHP) became the standard
tool for a group and multiple criteria decision making. When an uncertainty is present in a decision making interval or fuzzy AHP is often
considered. The aim of this paper is to propose a new method for interval AHP. In the proposed method weights of alternatives (criteria) are
estimated by an interval generalization of the geometric mean, and for
the final ranking of alternatives a formula based on a possibility measure is employed. The proposed method is computationally simple and
its use is demonstrated on examples.
2 - Aggregation of Pairwise Comparison Matrices by
Fuzzification
Zuzana Kiszova
The paper deals with the problem of aggregation of individual preferences into one consistent and acceptable group decision which will
reflect standpoints of all concerned subjects. A new way of aggregation by means of fuzzification of individual pairwise comparison matrices and subsequent finding of solution by ordering fuzzy numbers is
proposed. An illustrative example is attached.
3 - Microsoft Excel as a Tool for Multicriteria Decision
Problems
Radomir Perzina, Jaroslav Ramik
We consider a multi-leader multi-follower game in which the strategy
of each leader is not common knowledge among all agents, for instance
when leader manufacturers delegate the sale through exclusive retailers. A selection of Nash equilibria, based on a belief (passive belief)
that each follower has about the strategy of the other leaders, is investigated. Properties of the equilibria are presented under conditions of
minimal character, in particular results of existence and stability under
perturbations on the data, both in uncoupled and coupled constraint
cases.
This paper introduces a Microsoft Excel add-in called DAME - Decision Analysis Module for Excel. The add-in is free, can work with scenarios or multiple decision makers, allows for easy manipulation with
data, offers instant calculations and utilizes capabilities of Microsoft
Excel. Decision models can be structured into three levels — scenarios/users, criteria and variants. Various methods for the evaluation of
the weights with multiplicative and additive syntheses are supported.
The proposed module will be demonstrated on couple of illustrating
examples of real life decision problems.
3 - An Interior-Point Path-Following Method for Computing Perfect d-Proper Equilibria for Strategic Games
Chuangyin Dang
4 - Pairwise Comparison Matrix with Fuzzy Elements on
Alo-Group
Jaroslav Ramik
The perfect d-proper equilibrium is a strict refinement of perfect
equilibrium for strategic games, whose degree of properness is controlled by d. To determine such an equilbrium, an interior-point pathfollowing method is developed in this paper. The method is derived
from a close approximation to a perturbed game through an appropriate convex combination of payoff function and a barrier term. It is
shown that there exists a smooth path starting from a totally mixed
startegy profile and ending at a perfect d-proper equibrium. Numerical
results show that the method is effective and efficient.
This contribution is aimed on pairwise comparison (PC) matrices with
fuzzy elements. We deal with PC matrices with elements from the
alo-group over a real interval. Such an approach allows for a generalization dealing with additive, multiplicative and fuzzy PC matrices
with fuzzy elements. Moreover, we deal with the problem of measuring the inconsistency of fuzzy PC matrices by defining corresponding
indexes. Numerical examples are presented to illustrate the concepts
and derived properties.
4 - Eigenbehaviors in Closed Economies: General Economic Equilibrium Constructive Proof
Gabriel Turbay
Considering the world economy as a closed system and based on
von Foerster cybernetic principle that eigenbehaviors emerge in operationally closed systems, we use Krilov sequences to exhibit the
dynamic feedback price formation processes. Eigenvectors convergence with equilibrium and resilience properties is shown and a general equilibrium constructive proof is given. Game theory views are
presented to explain fluctuations around the eigen-prices, thus interrelating macroeconomic structural price formation with microeconomic
supply-demand price determination processes.
ME-26
Monday, 16:00-17:30 - Room 010
Fuzzy Decision Making 1
Stream: Fuzzy Decision Support Systems, Soft Computing, Neural Network
Invited session
Chair: Jaroslav Ramik
Chair: Martin Gavalec
ME-27
Monday, 16:00-17:30 - Room 213
Simulation and Numerical Methods in
Finance
Stream: Simulation Methods in Finance
Invited session
Chair: Katerina Papadaki
Chair: Gerhard-Wilhelm Weber
1 - No-Arbitrage ROM Simulation
Michael Hanke
Random orthogonal matrix (ROM) simulation efficiently generates
multivariate samples matching means and covariances exactly. We
enhance this method by focusing on applications requiring simulated returns to be free of arbitrage. We analytically derive noarbitrage bounds for expected excess returns to be used in ROM
simulations, and establish the theoretical relation between the number of samples and (no-)arbitrage regions. The new algorithm
generates arbitrage-free returns by purposefully rotating a simplex.
http://ssrn.com/abstract=2039922
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IFORS 2014 - Barcelona
2 - Quantile Optimization via SNM-Q
Kuo-Hao Chang
Stochastic Nelder-Mead simplex method (SNM) is a newly-developed
direct-search method for simulation optimization. Because SNM does
not require gradient information and has provable convergence property, it is applicable to many practical problems. In this paper, we
extend the framework of SNM to enable it to handle quantile-based
simulation optimization problems. We prove that the modified SNM,
called SNM-Q, can converge to the true global optimum w.p.1. Numerical experiments show that the efficiency of SNM-Q is satisfactory
and is worth further investigation.
3 - Stochastic Dynamic Programming Methods for the
Portfolio Selection Problem
Katerina Papadaki
We formulate the multistage portfolio selection problem with 100 assets as a dynamic program and solve it using approximate dynamic
programming (ADP) methods. We implement linear and piecewise
linear approximations for the value functions. Extensive simulations
are performed using equity data from the FTSE 100 index, where the
ADP methods are evaluated and compared out-of-sample against the
market, the equally-weighted portfolio, a single-period portfolio and
the multistage stochastic programming method. Simulation results are
provided and some very interesting conclusions are drawn.
4 - A Multistage Linear Stochastic Programming Model
for Optimal Corporate Debt Management
Davi Valladão, Alvaro Veiga, Geraldo Veiga
Large corporations fund their capital and operational expenses by issuing bonds with a variety of indexations, denominations, maturities
and amortization schedules. We propose a multistage linear stochastic programming model that optimizes bond issuance by minimizing
the mean funding cost while keeping leverage under control and insolvency risk at an acceptable level. Based on the proposed model, a
financial planning tool has been implemented and deployed for Brazilian oil company Petrobras.
3 - A Combined AHP-based Approach for Evaluating
and Ranking Economic Partners in a Public Organism
Kamal Hariche, Djamila Boukredera, Mohamed Salah, Rabah
Kassa
Selecting potential economic partners is a very important decision in a
public organism. Several methods have been used to solve this problem but most attention has been paid to the final choice phase in this
process. This paper aims to propose a combined approach using AHP,
centroid and L2 metric methods which integrates the required steps in
the screening process while considering both qualitative and quantitative criteria that affect the partners’ ranking. This allows decisionmakers to reduce the large list of potential partners to a manageable
number and make the best final choice.
4 - Customization Order Screening in Engineering-toOrder Environment
Hwai-En Tseng
In the engineering-to-order environment exist large differences in
product specifications leading to business loss. In the study, the author
attempt to set order screening mechanisms at the order taking stage.
The Fuzzy Suitable Index is proposed to assess the feasibility of order.
Moreover, the Utility Similarity is adopted to distinguish order levels
to eliminate inappropriate orders. After the calculation of costs and delivery, TOPSIS is applied to sort orders according to the corresponding
profit allocation ratio. The machine tools are used as an example to
illustrate the algorithm.
ME-30
Monday, 16:00-17:30 - Room 012
Financial Mathematics 2
ME-29
Stream: Financial Mathematics and OR
Invited session
Monday, 16:00-17:30 - Room 011
Chair: Norio Hibiki
Multiple Criteria Decision Making and
Optimization 1
1 - Rating Models using Logistic and Cox Regression:
Medium and Large Companies Case
Aneta Ptak-Chmielewska, Anna Matuszyk
Stream: Multiple Criteria Decision Making and Optimization
Contributed session
Chair: Hwai-En Tseng
1 - A Multi Objective Decision Making Approach for Determining New Sorting Technology in Order Picking
Systems
Nihan Topuk, Rifat Gürcan Özdemir
This study addresses a decision problem on adoption of a new sorting
technology for picker-to-goods order picking systems. A multi objective mathematical model is developed to compare the performance of
existing and the new technologies with respect to operational costs and
picking time. The formulation considers shelf assignment for items delivered from plants and determining order picking process for a given
sorting technology. This study also presents a heuristic search algorithm for solving the developed formulation. The proposed approach
is implemented for a logistic company in Turkey.
2 - A Multicriteria Ranking Procedure for a MediumSized Set of Alternatives based on Evolutionary Multiobjective Optimization
Jaime Solano, Juan Carlos Leyva-Lopez, Diego Alonso
Gastélum Chavira
The aim of this paper is to present an approach to solve the multicriteria ranking problem with a medium-sized set of alternatives. Using a new heuristic based on multiobjective evolutionary algorithms, a
known valued outranking relation is exploited and then a ranking recommendation is constructed. An empirical study over different hypothetical medium-sized problems is presented. The results indicate that
the proposed approach can effectively be used to solve medium-sized
multicriteria ranking problems.
70
The purpose of this paper is to answer the questions: Is Cox regression
model more effective than logistic one in measuring the company’s default risk? What are the main advantages of using the survival models?
The accuracy power of these two models is similar. Differences are
small and mostly due to the different models’ specifications. In Cox
regression model the log of turnover (time varying) was significant.
The main reason why it is preferred to use the survival model instead
of the logistic regression is getting the dynamic picture of modeled
events when using the survival approach.
2 - Effects of a Sales Tax Increase on Firm Valuation:
DCF Approach to Individual Firm Data
Hitoshi Takehara, Keiichi Kubota
This paper investigates how firm values change by increased sales tax
rate. Equity values are estimated based on the residual income model
in which we construct pro forma financial statements. We find that
an increase in sales tax rates decreases equity values for a majority of
firms, but not necessarily all firms. An additional corporate tax rate cut
helps increase the equity value for a majority of firms. The trade-off
relationship of a sales tax rate hike and a corporate tax rate reduction
is subtle, but the mix helps increase equity value of firms overall.
3 - Portfolio Selection Based on Bayesian Theory
Yong Fang
On the basis of reviewing Markowitz’s mean-variance model, the three
portfolio selection models are built in the paper, namely the portfolio selection model based on regression analysis, Bayesian-GARCH
(1,1) model and BMS-GARCH (1,1) model. We select data from the
exchanges, and compare the portfolio selection models. The BMSGARCH(1,1) model introducing the Markov states is superior to the
portfolio selection model based on regression analysis and BayesianGARCH (1,1) model.
IFORS 2014 - Barcelona
4 - Multi-Period Stochastic Programming Model for
State-Dependent Asset Allocation with CVaR
Norio Hibiki, Shinya Hirano
We need to solve the multi-period optimization model to decide the
dynamic investment policy under various practical constraints. Hibiki(2001,2003,2006) develop the hybrid model where the conditional
decision can be made in the simulation approach. In this paper, we propose the piecewise linear model for multi-period and state-dependent
asset allocation with CVaR. It is possible to describe the piecewise linear function of the investment proportion with respect to the amount
of wealth. We solve the problem for multiple assets, and compare the
piecewise linear model with the hybrid model.
ME-31
Monday, 16:00-17:30 - Room 013
Recent Advances on Decision Processes
Stream: Decision Processes
Invited session
Chair: Irene Abi-Zeid
1 - Organizational Knowledge to Support Project Selection Activities in the Public Administration
Maria Franca Norese, Valentina Torta
An investigation was required to analyze how the departments of the
Piedmont Region evaluate projects, programs, feasibility studies and
various requests for funding from public or private sources. This produced a map of the situation that was used to transfer indications
and guidelines to the actors of the project selection process. A decision support system was created using a multi-criteria decision aiding method, ELECTRE Tri. The analysis and its results, in terms of
the map and the ELECTRE Tri application to support activities of the
public organizations will be presented and discussed.
2 - Integration of Elements from Prospect Theory into
PROMETHEE
Nils Lerche, Jutta Geldermann
An enhanced approach for the integration of elements from Prospect
Theory into PROMETHEE will be presented. In particular, the effects of reference dependency and loss aversion are incorporated. For
this purpose, defining an adequate reference alternative and adjusting
the existing preference functions is necessary. The procedure as well
as advantages and challenges of the new approach will be illustrated.
Furthermore, results from practical applications concerning the sustainable use of biomass for energy generation are discussed.
3 - Monotonic Additive Preference Model for 3D Fusion
System Parameters Adjustment
Vincent Cliville, Lionel Valet
3D image interpretation to understand complex phenomenon is
achieved thanks to fusion systems having numerous parameters, difficult to adjust. An approximate model is looking for to simulate the
3D fusion process. The problem is described as a ranking problem
and three MCDA methods are considered thanks to holistic preference
information on a set of reference pictures: The ACUTA method with
linear utilities, the ACUTA enriched by the consideration of linearity
pieces and the UTA GMS method. Obtained results show the limit of
using monotonic additive utilities for such identification problem.
4 - The Value of Additional Information in Multicriteria
Decision Analysis with Information Imperfections
Sarah Ben Amor, Kazimierz Zaras, Ernesto Aguayo
In statistical decision analysis, the expected value of information is a
well-known concept where the value of information is assessed regarding sources of uncertainty that are normally considered one at a time.
This has not been the case for multicriteria decision analysis where
several sources of uncertainty in relation to several attributes can be
admitted. The Bayesian model is here extended to the context of multicriteria decision analysis with information imperfections (uncertainty,
imprecision, . . . ) for a pre-assessment of the required resources to obtain additional information.
ME-33
ME-32
Monday, 16:00-17:30 - Room 014
Network Decision Support
Stream: Humanitarian Operations Research
Invited session
Chair: Erik Kropat
Chair: Silja Meyer-Nieberg
Chair: Feixiong Liao
1 - Incorporating Home-Returning and Home-Staying
Decisions in Multi-Modal Multi-Activity Trip Chains of
Multi-State Supernetworks
Feixiong Liao, Theo Arentze, Harry Timmermans
Multi-state supernetworks have been advanced for modeling individual activity-travel scheduling. Choice of home-returning and -staying
is for the first time represented in the multi-state supernetworks. A
path through them still represents a consistent activity-travel pattern.
An admissible heuristic is developed to reduce the choice alternatives.
An earlier proposed bi-criteria label correcting algorithm is adopted
to find the optimal activity-travel pattern. Consequently, the trade-off
between time expenditure on travel, out-of-home activities and homestaying can be systematically captured.
2 - Sensitivity Analysis for Analytic Network Models
Magda Gabriela Sava, Jerrold May, Luis Vargas
We propose an extension of the sensitivity and stability analysis for
analytic network models previously developed. We study simple ANP
models to understand how preference regions are created, and characterize their boundaries as the complexity of the network increases. We
use optimization methods to find the most suitable boundaries between
the preference regions and define the appropriate stability regions.
3 - Modelling of Intermodal Networks
Karl Etlinger, Manfred Gronalt
This work presents an approach to support intermodal network planning and evaluation by providing a framework for terminal location
planning and network design. Therefore a mixed integer linear programming model is introduced to optimize the network structure and
determine the locations for operating intermodal terminals and the according type of terminal. The model also considers empty container
repositioning and optimizes the location of empty container depots
in the network. Within our work the developed model is also implemented in a case study for the area of Central and Eastern Europe.
4 - A Heuristic Approach to Restore Road Network Connectivity after a Disaster
Maziar Kasaei Roodsari, Sibel Salman
We study emergency road restoration problem with the aim of reconnecting a disconnected road network in shortest time. A work troop
is dispatched to open roads and achieve connectivity. Finding a route
with minimum total traversal and road unblocking time is an NP-hard
arc routing problem. We develop an MIP formulation and a Variable Neighborhood Descent (VND) heuristic together with constructive heuristics to get good initial solutions. Tests on Istanbul road network and Rural Postman Problem instances in literature show that the
proposed algorithm gives near optimal solutions in short time.
ME-33
Monday, 16:00-17:30 - Room 015
Measuring and Optimizing Sustainable
Behavior in Existing Systems
Stream: Environmental Sustainability in Supply Chain
Invited session
Chair: Maria Dos Santos
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ME-34
IFORS 2014 - Barcelona
1 - Optimization of a Two-Echelon City Distribution Network with Cargo Bikes
Alexandra Anderluh, Vera Hemmelmayr, Pamela Nolz
In our project we focus on sustainable inner city goods delivery. We
study a distribution problem on two levels, where goods are delivered
from the company depot on the outskirts of a city to customers and to
satellites. From satellites goods are transshipped to cargo bikes which
deliver to customers located in the city center. Hence, we have two
types of customers, those receiving a delivery on the first level and
those receiving a delivery by cargo bikes on the second level, where
synchronization between vans and cargo bikes is needed.
2 - Applying Dynamic, Process-Aware Information Systems to Supply Chain Data Collection
Thomas Bley, Michael Bierkandt, Christian Feick, Andreas
Schiffleitner
Manufacturing companies in the automotive and electronics industries are faced with the need to incorporate suppliers into the measurement of their sustainability performance (e.g. for GHG, RoHS,
Conflict Minerals). The complex nature of products and globally distributed supply chains implies challenges related to gathering and processing heterogeneous data. Existing information systems are not able
to adress these issues. The EU research project SustainHub proposes
a sophisticated data exchange platform which supports automated dynamic data collection from heterogeneous sources.
3 - OREG — Optimal Resource Management of Electric
and Electronic Devices
Maria Dos Santos, Sepp Eisenriegler, Walter Hauer, Rita
Haubenberger-Hahn, Thomas Maier, M. Merstallinger, Harald
Reichl, Gottfried Waizinger
The objective of the project is to investigate the re-use potential and
the characterization of valuable and hazardous materials in small and
big appliances of Waste Electrical and Electronic Equipment (WEEE).
Other objectives are to increase the amounts of appliances for re-use
purposes, to estimate the device categorization and the material composition as well as develop a re-use container to increase the current
amount of WEEE re-used in the observed sites. Fulfilling the objectives will contribute to improve the collection and recycling systems in
the region.
ME-34
Monday, 16:00-17:30 - Room 016
Power Systems Economics
Stream: Data Mining in Finance and Commodities
Invited session
Chair: Marcus Hildmann
1 - Improving Computational Performance of Energy
Market Models
Frieder Borggrefe, Karl-Kien Cao, Yvonne Scholz
This paper evaluates approaches to reduce complexity and increase
performance of forecast models for energy systems by applying partitioning techniques. LP models such as REMix or TIMES are used,
e.g. by policy makers, to analyze policy and technology scenarios.
They became fairly complex to cover market aspects such as fluctuating power from renewables. We compare different techniques to split
up an hourly dispatch problem implemented in GAMS (by differentiating time periods, regions or technologies) and identify the trade-off
between comput. performance, quality of results and optimality.
2 - Photovoltaic Energy Production Forecast using Support Vector Regression
Maila Pietrini, Renato De Leone, Antonio Giovannelli
The aim of this study is to predict the energy production of a PV plant
in Italy, using a methodology based on Support Vector Machines. The
model uses historical data of solar irradiance, environmental temperature and past energy production to predict the PV energy production
for the next day with an interval of fifteen minutes. The technique used
is based on n-SVR, a Support Vector Regression model where you can
choose the number of support vectors. The forecasts of energy production obtained with the proposed methodology is very accurate, with the
R2 coefficient exceeding 90%.
72
3 - Hourly Price Forward Curve for Market Coupling
Marcus Hildmann
We propose an algorithm to calculate the Hourly Price Forward Curve
(HPFC) under market coupling conditions. The algorithm uses the
supply and demand curves, transfer capacity, weather and seasonal indicators to calculate the HPFC based on the market coupling using
implicit capacity auctions.
ME-35
Monday, 16:00-17:30 - Room 131
Simulation and Advanced Optimization, in
Aviation Management and Manufacturing
Stream: Stochastic Modeling and Simulation in Engineering, Management and Science
Invited session
Chair:
Chair:
Chair:
Chair:
Erik Kropat
Silja Meyer-Nieberg
Goran Mihelcic
Henrik Andersson
1 - Delay in Aircraft Routing
Axel Parmentier, Frédéric Meunier
Building sequences of flights for their airplanes that minimize the expected cost of delay is crucial for airline companies. Due to the nonlinear propagation of delay, this aircraft routing minimization problem turns out to be challenging. We use the well-established notion of
stochastic order to obtain bounds and exploit them in the optimization
process. This framework can be adapted to optimize risk measures, or
to handle approximate probability constraints. Numerical experiments
are currently carried out.
2 - An air traffic decision support model for flight departure in an international airport
Eugene Wong, Josephine Chong
The paper investigates the operation efficiency of the two-runway system, the development of the third runway system, and the airspace
congestion problem in the Hong Kong International Airport. A constrained non-linear optimization model is proposed to minimize the
time horizon of airspace, gate-holding, and ground time. The arrival
and departure times with flight sequences are analyzed. The possibility of reducing aircraft fuel consumption and greenhouse gas emission during the gate-holding is reviewed. Future work on the aircraft
scheduling at the taxi runway intersections is suggested.
3 - Hub Location and Fleet Composition in Offshore Personnel Transportation
Eirik Fernández Cuesta, Henrik Andersson, Kjetil Fagerholt
This paper addresses a strategic hub location and fleet composition
problem for personnel transportation in the offshore oil production industry. The task is to find the optimal composition of the helicopter
fleet and select the best offshore hubs and onshore airport bases to use
in the transportation network. We present a mixed integer linear problem (MILP) model for the problem and solve it using a column pregeneration approach. Computational tests are performed on test cases
based on data from an oil company’s new field development outside
the Brazilian coast.
4 - A Semidefinite Optimization Approach to the Parallel
Row Ordering Problem
Philipp Hungerländer
The k-Parallel Row Ordering Problem (k-PROP) is an extension of
the Single-Row Facility Layout Problem (SRFLP) that considers arrangements of the departments along more than one row. We propose
an exact algorithm for the k-PROP that extends the semidefinite programming approach for the SRFLP by modelling inter-row distances
as products of ordering variables. For 2 rows, our algorithm is competitive with a recently proposed mixed integer programming approach.
Furthermore our algorithm is also applicable for more than 2 rows and
even yields better practical results for a larger number of rows.
IFORS 2014 - Barcelona
ME-36
Monday, 16:00-17:30 - Room 132
Forest Planning under Risk
Stream: OR in Agriculture, Forestry and Fisheries
Invited session
Chair: Jordi Garcia-Gonzalo
1 - A Dynamic Programming Approach to Optimize
Short-Rotation Coppice Systems Management
Scheduling under Climate Change
Liliana Ferreira, Miguel Constantino, Jose Borges, Jordi
Garcia-Gonzalo
Research aiming at the development of an adaptive management model
that may take into account climate change for even-aged eucalypt forest ecosystems in Portugal. A Dynamic Programming (DP) approach
is proposed to determine the stand management policy (e.g. sprout
selection, coppice cycles and rotation length) that produces the maximum expected discounted net revenue under climate change scenarios.
The DP model enables an adaptive management, capable to cope with
unexpected changes. Different scenarios are introduced in the model
to analyze the impact of climate change on the optimal policy.
2 - Approaches for Analyzing Risk and Integrating Risk
Attitudes in Forest Management
Kyle Eyvindson, Annika Kangas
ME-38
1 - A Complexity Reduction Method for the Multiobjective Multiclass Support Vector Machine
Keiji Tatsumi, Tetsuzo Tanino
In this paper, we discuss a Support Vector Machine (SVM) for the
multiclass classification. We focus in particular on the Multiobjective
Multiclass SVM (MMSVM), which finds discriminant hyperplanes by
solving a single multiobjective optimization problem. The problem,
which maximizes the geometric margins for the generalization ability,
requires a large amount of CPU resources. Therefore, we propose a
complexity reduction method for the MMSVM by using some pieces
of information obtained by solving binary classification problems extracted from the original multiclass one.
2 - Parameter Tuning in Support Vector Regressions
Yeboon Yun, Hirotaka Nakayama, Min Yoon
Support Vector Machines (SVMs) have been recognized as a powerful machine learning method and shown to provide high performance.
In order to accomplish good generalization ability, it is important to
choose appropriate values of parameters in SVMs. We propose a sequential learning using both bagging and boosting for parameter tuning
in support vector regression and also effectively extend it to problems
with complicated function forms. In addition, it will be shown that the
proposed method can improve the calculation time as well as generalization ability through several numerical experiments.
3 - Optimization over the Efficient Set of a Multiple Objective Linear Programming Problem with Reverse
Convex Constraint
Syuuji Yamada, Tamaki Tanaka, Tetsuzo Tanino
Forest management planning requires decisions to be taken based on
imperfect information and assumptions regarding the future growth of
the forest. Through the use of stochastic programming, the uncertainty
can be modeled in a deterministic fashion. An advantage of stochastic
programming allows for the decision makers attitude towards risk to be
incorporated into the development of a solution. This paper describes
methods for managing the different elements of risk, and demonstrates
the associated cost of the various risk mitigation methods.
In this talk, we consider a problem (OES) to minimize a linear function over the efficient set of a multiple objective linear programming
problem (MOLP), where one constraint is defined by a strictly convex
quadratic function and the other constraint functions are convex. Then,
the feasible set of MOLP is formulated as a dc set. Hence, it is not always true that the efficient set of MOLP is connected. In this case,
we propose a global optimization algorithm for OES by combining a
branch and bound procedure and a method listing all KKT points of a
quadratic programming problem.
3 - Solving the Raw Materials Reception Process with an
Optimization-Simulation Approach
Alexandra Marques, Mikael Rönnqvist
4 - The Unified Split Fixed-Point Variational Inequality
Problem and Algorithmic Consequence
Narin Petrot, Nimit Nimana
The significant contribution of raw materials inbound logistics to the
reduction of the procurement costs have motivated many studies, particularly in routing and wood truck scheduling. Further studies are
needed to avoid trucks congestion and queuing at the mill in order to
reduce even further the duration and costs of the transport. This talk
describes the Raw Material Reception Problem for scheduling in advance trucks unload and also handling their real time arrivals. The
proposed solution method combines an optimization technique based
in revenue management with discrete event simulation.
The main objective of this paper is to introduce a new split type
problem consists in finding a fixed point of a nonexpansive operator
which solves the variational inequality problem over the fixed point
set of such operator in a Hilbert space and such that its image under a
bounded linear operator is a fixed point of a certain nonexpansive operator in another Hilbert space. To find a solution of the problem (if
such a point exists) a modified iterative algorithm is proposed.
4 - A Stochastic Optimization Model to Adressing Climate Change in Forest Planning
Jordi Garcia-Gonzalo, Andrés Weintraub
In this work we consider a short/medium term forest planning problem
considering harvesting decisions in the presence of uncertainty due to
climate change which impacts in the growth and yield. We present
an application in a eucalypt forest where the planning decisions involve which units to harvest in each one of the 15 one-year periods.
We introduce a multistage Stochastic Integer Programming model considering 32 climate change scenarios and including the corresponding
non-anticipativity constraints. This enables the planner to make more
robust decisions than using a single average scenario.
ME-37
Monday, 16:00-17:30 - Room 017
Multiobjective Optimization in Asia (I)
Stream: Multiobjective Optimization
Invited session
Chair: Tetsuzo Tanino
Chair: Tamaki Tanaka
ME-38
Monday, 16:00-17:30 - Room 214
Optimization Techniques for Some
Statistics Models
Stream: Convex Optimization Methods and Applications
Invited session
Chair: Xiaoming Yuan
1 - On How to Solve Large-Scale Log-Determinant Optimization Problems
Chengjing Wang
We propose a proximal augmented Lagrangian method and a hybrid
method, i.e., employing the proximal augmented Lagrangian method
to generate a good initial point and then employing the Newton-CG
augmented Lagrangian method to get a highly accurate solution, to
solve large-scale nonlinear semidefinite programming problems whose
objective functions are a sum of a convex quadratic function and a logdeterminant term. We demonstrate that the algorithms can supply a
high quality solution efficiently even for some ill-conditioned problems.
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ME-39
IFORS 2014 - Barcelona
2 - Exact Relaxations for Rank Minimization Problems in
Euclidean Jordan Algebra
Ziyan Luo, Lingchen Kong, Naihua Xiu
Rank minimization problems, arising from many applied fields such
as system identification and control, are generally NP-hard due to the
combinatorial nature of the rank function. In this talk, several exact
relaxation approaches are proposed for rank minimization problems
in a more general setting - the Euclidean Jordan algebra. Our results
can be regarded as a generalization of the existing relaxation theory
in compressed sensing and the low-rank recovery theory in matrix optimization. Deterministic and easy-to-check exactness conditions for
problems with special structures are also studied.
3 - Optimization in Censored Quantile Regression
Lingchen Kong
In this talk, we will review the basic concepts and results on censored
quantile regression, which include the background, history development and recent works in statistics. In order to understand the optimization models and establish the efficient algorithms, we finally study
the properties of Lòwner operator generated by the quantile function.
More specifically, we will consider its continuity, (locally) Lipschitz
continuity, directional differentiability, F-differentiability, continuous
differentiability and strong semismoothness.
ME-39
Monday, 16:00-17:30 - Room 018
ORAHS III - Emergency Services
Stream: Health Care Applications
Invited session
Chair: Sally Brailsford
Chair: Brigitte Werners
1 - Ambulance Planning with and without Region Borders
Theresia van Essen, Melanie Reuter, Stefan Nickel
Border regions are a major challenge in ambulance planning. The border regions obviously occur between countries, but often also within
a country. These borders within a country lead to an inefficient use
of ambulances as it often happens that there are ambulance bases on
both sides of the border even though one ambulance base could serve
both sides simultaneously. In this talk, we first introduce solution
approaches for efficiently locating ambulance bases and ambulances.
Second, we show the improvement in terms of coverage and efficiency
when borders between regions in a country are ignored.
2 - Ambulance Planning under Uncertain Demand
Melanie Reuter, Francisco Saldanha-da-Gama, Stefan Nickel
4 - Simulation based Evaluation of Different Objectives
for Emergency Medical Services
Brigitte Werners, Lara Wiesche, Pascal Lutter, Dirk Degel,
Dirk Degel
Resources for Emergency Medical Services (EMS) have to be positioned such that emergencies can be reached within a given time frame.
Well-known models in literature consider different variants of demand
coverage as a proxy for EMS quality, defined as the ratio of calls served
within the legal respond time. In order to evaluate the performance of
standard optimization models in literature, a detailed simulation study
is conducted. We evaluate different objective functions and the resulting positioning of EMS resources and their influence on real world
outcome measures.
ME-40
Monday, 16:00-17:30 - Room 019
Advances in Production and the Link with
Supply Chain
Stream: Production and the Link with Supply Chain
Invited session
Chair: Amin Chaabane
Chair: Alice Yalaoui
1 - Inventory Control and Environmental Policies in Reverse Logistics Supply Chain
Amin Chaabane, Marc Paquet, Marthy Stívaliz García
Alvarado
Current environmental regulations and economic conditions force organizations to limit Greenhouse Gas (GHG) emissions. Since inventories have proven their crucial role in supply chains, the aim of this
paper is to study the impact of inventory control in reducing the environmental damage of an organization. Modeled as a Markov Decision
Process (MDP), we dealt with a stochastic recovery inventory system
considering an infinite-horizon, and a cap-and-trade mechanism. We
show that there is a direct link between carbon credit price and inventory policies.
2 - Mathematical Model to Determine the Configuration
of a Reverse Supply Chain (RSC)
Juan Osorio, Carlos J. Vidal, Jose de Jesus Casas Riascos,
Katherine Ceron Naranjo
Ambulance planning minimizes the cost for installing ambulances and
bases assuring a minimum coverage level. We assume stochastic demand and consider a scenario-indexed formulation. However, the number of scenarios becomes prohibitively high even for small instances
and considering one single sample can lead to a misleading solution.
Therefore, we present a sampling approach in which we solve several
samples and then combine the optimal values in order to estimate the
optimal value of the original problem. We test the approach using randomly generated instances inspired by real-world data.
In this paper, we propose a mathematical model to determine the configuration of a reverse supply chain (RSC) that includes the collection,
recovery, treatment, and disposal of electrical and electronic equipment
waste (EEEW). The model objectives consist of maximizing utility and
minimizing CO2 emissions produced by the operation of the chain.
The model is multi-objective, multi-product, and multi-level and considers different types of transportation modes and facility capacities.
The proposed method is validated by its application to a hypothetical
RSC.
3 - Performance Improvement for Emergency Medical
Services (EMS) with Time-Region-Specific Cruising
Ambulances
Jiun-Yu Yu, Kwei-Long Huang
3 - Creating an Advanced Order Stream with the Proportional Order-up-to Policy
Qinyun Li, Stephen Disney
Emergency Medical Services (EMS) refers to both patient transport
and medical support solution for people with illness or injuries. Recent
clinical evidence shows that for out-of-hospital cardiac arrest (OHCA)
cases the response time, time spent by the ambulance to arrive at the
scene, is critical to the survival rate. To reduce the response time, a
time-region-specific ambulance cruising policy is proposed. Analytics
and GIS are applied to generate the joint time-region distributions to
identify high frequency grids. Simulation models are built to examine
various ambulance cruising policies.
Information sharing has been promoted for several decades as a mechanism to enhance supply chain performance but the degree of success
from such a scheme is widely variable. In particular some players
are reluctant to share end-customer demand with others in the supply
chain. We propose an alternative approach where a predicted order
stream is given to the supplier as guidance to coordinate and plan their
activities accordingly. This order stream is determined by the orderup-to policy which incorporates a proportional feedback controller to
enable a smooth, steady order stream to be made.
74
IFORS 2014 - Barcelona
4 - Value of Disruption Information in an EOQ Environment
Ismail Serdar Bakal, Z. Pelin Bayindir, Deniz Esin Emer
We consider an infinite-horizon, continuous-review inventory model
with deterministic, stationary demand where supply is subject to disruption. The supply process alternates randomly between ON and OFF
states. Backlogging is allowed only when the supplier is disrupted. We
seek the value of disruption information which enables the firm to place
an extra order when supply is disrupted. We derive the long-run average cost utilizing the renewal theory, and characterize the order-up-to
levels. We also compare the results to the setting with no disruption
order opportunity.
ME-41
Monday, 16:00-17:30 - Room 216
Lot-Sizing and Related Topics 4
Stream: Lot-Sizing and Related Topics
Invited session
Chair: Michelli Maldonado
1 - Integrated Lot Sizing and Cutting Stock Problem
Gislaine Melega, Silvio de Araujo
The lot sizing and the one-dimensional cutting-stock problems have
an important role in the production sector, such as, tubular furniture
and paper factories, metallurgical, among others and generally these
problem are dealt independently. In this work, we approach both problems in an integrated way. We studied a classical model for lot sizing
problem and its reformulation based on the shortest path problem. For
the one-dimensional cutting stock problem, three different models proposed in the literature were studied. We present a computational study
using randomly generated data.
2 - Integrated Supply and Production Planning
Fanny Hein, Christian Almeder
In this work we assess the benefits of an integrated supply and production planning problem where the routing part corresponds to the
collection of raw materials and the production planning part is concerned with the conversion of those raw materials into end products.
We define two scenarios, one incorporating raw material inventories,
and the other one supposing just-in-time (JIT) supply of the raw materials. Based on extensive computational testing we conclude that an
integrated planning approach is more beneficial in a JIT-environment
but only if there is sufficient excess capacity.
3 - Fuzzy Logic Approach for Dynamic Lot Sizing for a
Warm/Cold Process
Ozgur Toy, Ayca Altay, Yeliz Ekinci
Production systems in which the physical structure of the process allows keeping the system warm in order to avoid expensive shut down
and start up costs. This type of systems have been studied in the literature. A generalisation of such a system is provided by Toy and Berk
(2006) in which the process can be kept into the following period only
if the production in the period is at least as much as a pre-specified
quantity. Optimal structure of the solution for the problem has been
studied and solution algorithm is provided. In this study we present a
fuzzy logic approach for this problem.
4 - Mathematical Models for an Integrated Lot Sizing and
Scheduling Problem
Michelli Maldonado, Socorro Rangel
Different strategies have been used to model scheduling decisions in
the Integrated Lot Sizing and Scheduling Problem (ILSP). To obtain
the production sequence, constraints based on the Asymmetric Traveling Salesman Problem (ATSP) are added to the lot sizing formulation.
Different approaches are used to model the Sub-tour Elimination Constraints (SEC) in the ATSP. We will present mathematical models for
the ILSP based on several SEC approaches to treat the scheduling decisions, and a preliminary computational study to assess the efficiency
of the models.
ME-43
ME-42
Monday, 16:00-17:30 - Room 215
Human Aspects in Transportation and
Logistics
Stream: Green and Humanitarian Logistics
Invited session
Chair: Jeyson Andrés Martínez Gamboa
1 - Innovative Operating Strategies for ADA Paratransit
Services
Luca Quadrifoglio
ADA Paratransit services are a very large industry providing transportation services for disabled and elderly customers across the country. They are very cost-ineffective. We propose innovative scheduling
policies to enhance the operations of ADA Paratransit services using
Zoning strategies. The proposed innovations will allow these services
to maintain their desired zonal structures, improve customer service
level, reduce operating costs and increase the passenger trip per revenue hour. A set of alternative scheduling options are proposed and
discussed, showing pros and cons for each one.
2 - A Relief Distribution Model with Decaying Resilience
of the Affected Population
Eiichi Taniguchi, Ali Qureshi
The disaster relief distribution could make a difference between life
and death of the affected people. Very little academic research has
been done on the planning relief distribution, which only shares specific experiences. None of the relief distribution models has considered
the decrease in the resilience of the affected population due to the delay in relief supply and if it is less than the demand. This research
aims at developing a new relief distribution model capable of providing a multi-period relief distribution plan considering the diminishing
resilience of the affected population.
3 - Public Transportation Preferences of Disabled People
Mehmet Çağlıyangil, Sabri Erdem
In Turkey, almost 15% of people are disabled. However, only a very
little minority can be observed in public transportation. There are various factors affect the decision of going outside and choosing a public
transportation mode. Subway, bus, ferry, taxi et cetera, can be used for
intra-urban transportation by disabled people according to their dysfunctionalities. We classified the transportation mode preferences of
disabled people in İzmir with Discrete Choice Analysis. The results
can be used by public transportation policy makers for increasing transportation quality for disabled people.
4 - Development of a Logistic Model and its Impact on
Resilience
Jeyson Andrés Martínez Gamboa, Ever Angel Fuentes Rojas
There is no distinction when talking about natural disasters. However,
most of the victims are given because of the lack of attention after
the event in contrary to during it. That is why humanitarian logistic
is getting more important among countries, nevertheless the level of
uncertainty managed in its supply chain hampers the objective: Safeguarding life.
As a contribution, a humanitarian logistics system was designed,
through the development of a mathematical model using integer programming to generate an information system that reduce those levels
of uncertainty of the supply chain.
ME-43
Monday, 16:00-17:30 - Room 217
Accounting, Corporate Governance and
Valuation
Stream: Operational Research in Financial and Management Accounting
Invited session
Chair: Matthias Amen
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ME-44
IFORS 2014 - Barcelona
1 - Cost Control for Projects and IAS 11
Matthias Amen
The International Accounting Standard (IAS) 11, called "Construction
Contracts" allows to recognise revenues of long-term contracts according to the degree of completion, which could be measured by the costto-cost method. We expand the general cost deviation approach to
projects and identify some problems that occur when IAS 11 has to
be applied. Furthermore, we improve the approach for cost deviation
analysis while considering the total network of activities. At last, we
suggest some modificatons to IAS 11, especially to the cost-to-cost
method.
2 - A Multi Criteria Network Approach for Evaluating the
Independency of Individuals in the Corporate Governance System
Kai Kurhofer, Matthias Amen
The individuals who are involved in the corporate governance system
should be unbiased and largely independent from the preparers of financial statements and other political influences. We present an approach for analyzing the direct and indirect relations of the individuals
who are involved in the system. In this paper we propose a multiple classification for relations and present a method for calculating the
combined strength of network relations. Furthermore we suggest practical guidelines for redefining independency criteria.
3 - Valuation of Tax Savings
Felix Streitferdt
One of the most common assumptions in finance is the assumption that
all items yielding a tax shield can be deducted from the taxable base in
the same period they are accounted. This is not realistic and the resulting values of future tax savings are therefore too high. To attack this
problem, we develop a binomial model that allows the taxable base to
become negative and to use risk neutral valuation. As a limitng case
we propose an arithmetic brownian motion that is used within a MonteCarlo-Simulation to calculate the value of future tax savings using risk
neutral probabilities.
4 - Corporate Liquidity and Dividend Policy under Uncertainty
Nicos Koussis, Spiros Martzoukos, Lenos Trigeorgis
We develop a computational lattice based model of firm valuation under revenue uncertainty that incorporates liquidity choice (retained
earnings), debt financing, external financing costs and bankruptcy
costs. The irrelevancy of dividend policy and retained earnings holds
only in the absence of default risk. Retained earnings have a positive role in the presence of growth options and when external financing
costs are high. A high level of retained earnings may enhance the value
of debt and improve firm value via larger tax benefits, more importantly
in the presence of high bankruptcy costs.
ME-44
Monday, 16:00-17:30 - Room 218
Game Theory
Stream: Game Theory
Invited session
Chair: Miquel Oliu Barton
1 - Modeling and Solution of COA Development based
on Timed Influence Net and Game Theory
Jincai Huang, Chao Chen, Guangquan Cheng, Baoxin Xiu,
Weiming Zhang, Cheng Zhu
In the process of operation planning, the development of course of
action is one of the key steps. With consideration of conflict game, resource restriction, and the influence of action’s execution time, this paper establish a model of course of action development based on timed
influence net and game theory, and solution by translate this problem
into the standard matrix game model. And at last, an example is given
to illustrate this model and it’s solution.
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2 - Lexicographic Allocations and Extreme Core Payoffs: The Case of Assignment Games
Tamás Solymosi, Marina Nunez
We consider various lexicographic allocation procedures for TU games
where the payoffs are computed in an externally given order of the
players. Their common feature is that if the allocation is in the core, it
is an extreme point of the core. Our main result for assignment games
is the coincidence of the sets of lemarals (lexicograhic maximization
over the set of dual rational payoff vectors), lemacols (lexicograhic
maximization over the core) and extreme core points. This provides
a way to compute the Alexia value with no need to obtain the whole
coalitional function of the assignment game.
3 - A Monotonic and Merge-Proofness Rule in Minimum
Cost Spanning Tree Situations
Juan Vidal-Puga
We present a new model for cost sharing in minimum cost spanning
tree problems, so that the planner can identify the agents that merge.
Under this new framework, we show that, as opposed to the traditional model, there exists a rule that satisfies core selection, costmonotonicity and merge-proofness.
IFORS 2014 - Barcelona
Tuesday, 8:30-10:00
TA-01
Tuesday, 8:30-10:00 - Room 118
(Integrated) Planning Models
Stream: Railway and Metro Transportation
Invited session
Chair: Leo Kroon
1 - Train Routing through Stations
Nikola Besinovic, Rob Goverde, Egidio Quaglietta
Routing trains through busy railway nodes is an important part of the
timetabling process. A route for each train has to be determined to
provide a conflict-free schedule, given the event times of trains. In this
paper, we describe the stability routing model aiming to minimize the
capacity occupation. We formulate the model as a flexible job-shop
scheduling and provide the heuristics based on the max-plus algebra
and heaps theory to solve it. Since the microscopic infrastructure is
considered, the feasibility is guaranteed. The model is tested on the
real-life instances of the Dutch network.
2 - Integrated Rolling Stock Planning for Suburban Passenger Train Services
Per Thorlacius
A central issue for operators of passenger trains is providing a sufficient number of seats while minimising operating costs. This process
must be conducted taking a large number of practical, railway oriented
requirements into account. Because of this complexity, a stepwise solution was previously used, the result being the loss of optimality. The
talk will present a new matheuristic based integrated rolling stock planning model in which many requirements are handled all at the same
time. Real-world results from DSB S-tog, the suburban train operator
of the City of Copenhagen are presented.
3 - Timetabling with Crew Scheduling Integration at a
Freight Railway Operator
Lukas Bach, Twan Dollevoet, Dennis Huisman
We investigate to what degree we can integrate the Train
Timetabling/Engine Routing Problem (TERP) and the Crew Scheduling Problem (CSP). The overall integration is achieved by obtaining an
optimal solution for the TERP, while exploiting the fact that numerous
optimal solutions exist. We extract the solutions where it is possible
to alter the timetable while keeping engine routings intact. This is implemented in a mathematical model for the CSP. The model is solved
using a Branch-and-Price scheme. Hereby it is possible in the CSP to
adjust the timetable, and achieve a better overall solution.
4 - A New Approach to Crew Scheduling in Rapid Transit
Networks
Manuel Fuentes, Ángel Marín
A new approach to the Crew Scheduling Problem is presented. This
approach is oriented to solve the daily planning in Rapid Transit Networks, where movements are typically short and frequencies high,
leading to combinatory complexity. The structure of the resulting formulation can be exploited with decomposition methods, and it can take
advantage of its similarities with the train (or bus) routing problem
when integrating both.
TA-02
Tuesday, 8:30-10:00 - Room 111
Routing and Scheduling
Stream: Vehicle Routing
Invited session
Chair: Hocine Bouarab
TA-03
1 - Multi-Denomination Currency Distribution Problem
with Transportation Security Consideration
King-Wah Anthony Pang, Yan-Feng LI
With rapid development of the social economy in China, the amount
of currency supply and circulation are drastically increasing year-onyear, so as the issuance cost. This issuance cost is significantly affected
by the decision on currency distribution operation. Also, risk management is another critical measure for currency distribution as banknotes
are being transported. We formulate the currency distribution problem
as multi-type currency pickup and delivery model and we propose to
develop heuristic methods to solve the problem using decomposition
technique with local improvement schemes.
2 - Optimization of Inter-Depot Trunking with Heterogeneous Fleet and Semi-Trailer Swap Option
Raza Khan, Jian-Bo Yang, Julia Handl
This research deals with the inter-depot trunking by using heterogeneous and multi-compartment fleets. The unique feature of this problem are swapping of semi-trailers between different trucks and loading
of two categories of products in adjustable-size compartments with an
aim to minimize the total number of vehicles used. Real-life data is
used to test the linear-programming based model. The comparison of
human-generated and model-generated solutions suggests that equally
good-quality solutions are produced thus reducing the dependence and
cost associated with human-planners.
3 - Use Fibonacci Numbers to Improve Performance of a
Genetic Algorithm
Anita Gudelj, Danko Kezić
In this paper, the authors focus on the effect of variable population size
on accelerating evolution in the context of our algorithm which integrates MRF1 Petri net with genetic algorithm GA. Our approach uses
Fibonacci sequence to select the number of individuals in populations.
The motivation is to add new individuals when the GA is reaching a
stagnation phase. This model we tested on some scheduling problems
with shared resources. Results confirm that our model finds solutions
of similar quality to the ones found by Standard GA, but with a smaller
amount of computational effort.
4 - Improving the Quality of Dual Solutions in Column
Generation
Hocine Bouarab, Issmail El Hallaoui, Francois Soumis,
Abdelmoutalib Metrane
Column generation (CG) is a largely used algorithm for solving routing problems. When the columns added to the master problem (MP)
represent routes, the MP is very degenerate and produces poor quality
dual solutions increasing drastically the number of CG iterations. We
propose a new CG algorithm where, at each iteration, the dual solution
is partially given by the MP and completed by an auxiliary problem.
This approach produces more central dual solutions and the iterations
number is considerably reduced. We report numerical results on instances of the Vehicle and Crew Scheduling Problem.
TA-03
Tuesday, 8:30-10:00 - Room 001
Aviation Management and Processes
Stream: Aviation
Invited session
Chair: Stefan Wolfgang Pickl
Chair: Matthias Dehmer
1 - A System Dynamics Approach to the Boarding Process
Elisa Canzani, Joachim Block, Renato De Leone, Stefan
Wolfgang Pickl
As an aircraft generates revenues only when it is flying, airlines aim to
minimize ground times. The boarding process is one of the most time
consuming processes and relevant for airlines but also for passengers.
Feedbacks and nonlinearities inherent to this process makes it difficult for the application of analytical methods. However, coping with
feedbacks and nonlinearities are strenghts of System Dynamics. We
have developed a SD model to get a better understanding of the boarding system’s behavior. Our model allows airline managers to simulate
different policies and to optimize the process.
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TA-04
IFORS 2014 - Barcelona
2 - Flexibility and Customer Value in Airline Revenue
Management
Sebastian Vock, Catherine Cleophas
Flexible products are a powerful tool for airlines to induce new customer markets and generate more revenue while improving the utilization of fixed capacities. In this context, we take a look at customer
value related effects in long-term revenue management. We formulate
a combined model for revenue management with flexible products and
the integration of customer value. In a second step we provide first
numerical results for this approach resulting from several simulation
experiments.
3 - A Game-Theoretic Model for Aviation Management
Processes
Stefan Wolfgang Pickl, Matthias Dehmer
With Game-Theoretic Models certain Aviation Management Processes
might be modeled, simulated and optimized. This talk gives an
overview; especially the tau-value will be introduced. We present an
allocation rule for designing runways, and extend this procedure to
general allocation processes within aviation management.
4 - Shipper Collaboration with Partner Constraints
Gultekin Kuyzu
In truckload shipper collaboration, shippers submit tours with little or
no asset repositioning to a carrier, as opposed to submitting individual
lanes, with the hope of receiving more favorable rates. The shippers
must solve a Lane Covering Problem (LCP) to maximize savings. In
this study, we focus on a new variant of LCP, motivated by the need to
limit the number of partners. We introduce a MIP formulation for this
new variant and develop a column generation based algorithm for its
solution.
TA-05
Tuesday, 8:30-10:00 - Room 002
Stochastic Programming in Maritime
Transportation
Stream: Maritime Transportation
Invited session
Chair: Lars Magnus Hvattum
TA-04
Tuesday, 8:30-10:00 - Room 119
Contracting
Stream: Supply Chain Management
Invited session
Chair: Gultekin Kuyzu
1 - Unsold versus Unbought Commitment: Minimum Total Commitment Contracts with Nonzero Setup Costs
Geoffrey A. Chua
We study a minimum total commitment contract where the buyer commits to purchase a minimum quantity of a single product from the supplier over the contract duration. We consider non-stationary demand
and per-unit cost, discount factor, and nonzero setup cost. Since existing methods fail, we develop a new method based on a state transformation technique using unsold commitment instead of unbought commitment as state variable. We prove for the first time the optimality of
a modified (s,S) policy. We also discuss four extensions to show the
generality of our method’s effectiveness.
2 - Optimal Periodic Flexible Policies for Two-Stage Serial Supply Chains
Fang Liu, Nagesh Gavirneni
In a two-stage serial supply chain, Periodic Flexible (PF) policies can
reduce the inefficiency due to decentralization by 43%. We show a
general way to find the optimal PF policies through an example of periodic flexible policies of length two. Under the optimal policy, the
retailer follows a state dependent capacitated/order upto policy. We
approximate the optimal restricted ordering functions by a piecewise
linear function. We show that the optimal PF(2) policies are able to
reduce the total supply chain cost by 13%. The linear approximation
is effective with an error of less than 1%.
3 - Channel Coordination with a Single Supplier and
Multiple Retailers Considering Customer Arrival
Times and Route Selection
Ilkyeong Moon, Xuehao Feng, Dongwook Kim
We address a decentralized supply chain with one supplier and multiple independent retailers. The supplier distributes a newsvendor-type
product to retailers with one vehicle in one trip. The supplier decides
the delivery route and the arrival time of products. Without any coordinating contracts, the supplier may prefer a local optimal delivery
route. We present a wholesale-price-and-carpooling contract to coordinate such a supply chain. We demonstrate supply chain coordination
under such a contract and show that the profit along the supply chain
can be arbitrarily allocated.
78
1 - Comparing Optimization and Simulation Models for
Stochastic Empty Container Repositioning
Massimo Di Francesco, Alexei Gaivoronski, Paola Zuddas
We consider the problem of moving of empty containers between
ports under uncertainty about supply/demand and we examine two approaches for solving this problem. The first approach is a simulation
model incorporating parametrized decision parameters, which are optimized by a stochastic gradient method. In the second approach we
describe the uncertainty by a finite number of scenarios organized in
scenario tree and construct a deterministic equivalent of the original
stochastic problem in the form of large scale LP of special structure.
The comparison between these approaches is presented.
2 - A Stochastic Model for Vessel Fleet Analysis for
Maintenance Activities at Offshore Wind Farms
Elin E. Halvorsen-Weare, Christian Gundegjerde, Ina
Blomseth Halvorsen, Lars Magnus Hvattum, Lars Magne
Nonås
To execute maintenance activities at offshore wind farms, maintenance
personnel and equipment need to be transported from onshore or offshore bases to the individual wind turbines. Vessels and helicopters
are used for this purpose. To reduce the cost of energy from offshore
wind farms it is essential to keep an optimal or near-optimal vessel
fleet. The optimization problem arising is highly stochastic. We propose a stochastic optimization model and computational experiments
show that our model can be used to provide a decision maker with an
optimal vessel fleet within acceptable time limits.
3 - Optimizing the Maintenance Vessel Fleet at an Offshore Wind Farm
Magnus Stålhane, Elin E. Halvorsen-Weare, Lars Magnus
Hvattum, Lars Magne Nonås
We present stochastic programming model to determine the optimal
vessel fleet size and mix for executing maintenance activities at offshore wind farms. This includes choosing which vessels to buy, which
to charter-in, and selecting which bases to operate from. The model
includes uncertainty in the number of maintenance activities and the
weather conditions at the wind farm. A computational study is conducted based on realistic data, with results showing that the value of
using a stochastic model to solve the strategic fleet size and mix problem is, in many instances, high.
4 - A Maritime Inventory Routing Problem with Uncertain Travel Times
Lars Magnus Hvattum, Agostinho Agra, Marielle
Christiansen, Alexandrino Delgado
We consider a short sea shipping problem where a company is responsible for the distribution of oil products between islands as well
as the inventory management of those products at unloading ports.
Uncertainty in weather conditions and unpredictable waiting times at
ports must be considered when creating vessel itineraries. A two-stage
stochastic programming model with recourse is presented where the
first-stage consists of routing, loading and unloading decisions, and
the second stage consists of scheduling decisions.
IFORS 2014 - Barcelona
TA-06
Tuesday, 8:30-10:00 - Room 211
Health Care System Design
Stream: Logistics in Health Care
Invited session
Chair: Elisa Long
1 - Health Care Supply Chain Design from a Stakeholder’s Perspective
Nico Vandaele, Catherine Decouttere, Stef Lemmens
Health care supply chain modelling starts with a stakeholders analysis,
including functional, financial and decisional dependencies. This reveals a KPI set and system requirements for the alternatives, obeying
technological, financial and human KPI’s. A flow model is used to link
a subset of system characteristics with a subset of KPI’s. The addition
of constraints leads to a group decision process for the final scenario
choice, with a high degree of implementation success. We illustrate
this with a health care supply chain.
2 - Re-Examining the Patient Experience: Using Process Design and Trajectory to Improve Patient Satisfaction in Physician Practices
Grady S. York, Gary Garrison
Patients’ perception of service satisfaction is crucial to healthcare
providers seeking a sustainable practice. Visits encompass multiple patient contact points impacting satisfaction. 15,068 patients and
1,805 providers were surveyed. Factor analysis identified five factors:
provider interaction, medical staff interaction, facility/reception, visit
wait time and, pre-appointment wait time. Understanding and managing points of contact along the process trajectory individually and
cumulatively will increase process performance through reduced wait
times and more efficient use of resources.
TA-08
2 - Improving Do-Not-Exceed Limits for Renewables
with Robust Corrective Topology Control
Kory Hedman, Akshay Korad
The Independent System Operator of New England (ISONE, USA) requires variable renewable resources to stay within a dispatch range (or
face penalties); this range is known as a do-not-exceed (DNE) limit.
The DNE limits are meant to ensure reliability and are determined
based on the availability of reserve and network limitations (e.g., congestion, voltage). With the use of robust optimization and by combining corrective topology control with contingency analysis, this work
demonstrates how topology control can improve reserve deliverability
and, thus, substantially expand the DNE limit ranges.
3 - Self-Commitment of Combined Cycle Units under
Electricity Price Uncertainty
Anthony Papavasiliou
Day-ahead energy market clearing relies on a deterministic equivalent
model with a limited time horizon, which can be inefficient. Instead,
generators may wish to assume the risk of self-committing their units
with the hope of securing greater profits. This may reduce the room for
economic signals in the day-ahead market. We investigate the influence of risk aversion and price volatility on the decision of generators
to self-commit units. We present a Benders decomposition algorithm
for self-committing combined cycle units under price uncertainty with
a conditional value at risk criterion.
4 - Modeling Incentives in Vertically Integrated Electricity Markets
Andy Philpott
Many electricity markets are vertically integrated: generation companies also own retail companies that buy from the wholesale market and
sell to consumers. When entry into the wholesale supply market is
limited, vertical integration is often blamed for a lack of retail competition. We present some models that investigate the effects of vertical
integration on generator offer behavior and investment incentives.
3 - Patients without Patience: An Econometric Model of
Waiting in the Intensive Care Unit
Elisa Long, Kusum Mathews
As demand for hospital intensive care unit (ICU) beds increases, improving patient throughput is needed. High utilization levels in the ICU
and other hospital departments may impact patients’ length of stay and
thus contribute to long wait times for a bed. Using 12 months of data
for Yale-New Haven Hospital (a 51-bed ICU), we estimate the impact
of crowdedness on length of stay and bed transfer time, controlling for
patient characteristics. We then develop an econometric model to estimate the impact of waiting for a bed on mortality and readmission
rates.
TA-08
Tuesday, 8:30-10:00 - Room 120
Electric Mobility
Stream: Energy Economics, Environmental Management and Multicriteria Decision Making
Invited session
Chair: Peter Letmathe
TA-07
Tuesday, 8:30-10:00 - Room 003
Planning and Operation in Electric Power
System
Stream: Equilibrium Problems in Energy
Invited session
Chair: Shmuel Oren
1 - Pricing Models for Electric Vehicle Charging
Peter Letmathe, Ilhana Mulic, Ramajothi Ramsundar
Investments in charging stations in public or semi-public places require
sufficient return on investment. We analyze three types of pricing models, i.e., time-based pricing, energy based charging and parking based
pricing. Employing the NPV method, we find that several factors are
influencing the NPV of charging stations. For example the type of
the charging station, location, utilization, future demand for electric
vehicles, electricity costs are relevant for profitable investments. As
a result, we show that optimal pricing strategies differ depending on
these parameters.
1 - Subsidies to Renewables, Ramping Constraints and
Plants’ Dismantling
Yves Smeers, Sebastian Martin
2 - E-Mobility: Influence of the Second Life of used Batteries on Profit and Demand
Ilhana Mulic, Peter Letmathe, Ramajothi Ramsundar
The European power system is currently undergoing anticipated dismantling of conventional plants because of the low prices on the energy
markets, partially due to wind penetration. We consider a two settlement model, separated Power eXchange and System Operator, posed
as a stochastic equilibrium problem. It assumes a feed in premium incentive for wind generation and risk averse generators. We examine
the impact of various systems features on electricity price, and compare models with price dependent and fixed demand as well as with
different representations of ramping.
We analyze the effect of the second life of used batteries on the profit
of manufacturers, battery price and demand of batteries for electric vehicles. There are three options to benefit from collecting used batteries
namely refurbishing, recycling and reuse. There are also uncertainties
with respect to demand for used batteries, cost parameters and parts
recovered in terms of quality, quantity and time of return. Our analysis
shows that cost savings from collecting used batteries has important
implications for pricing decisions, demand and profit of the manufacturers.
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IFORS 2014 - Barcelona
3 - Electric Vehicles with a Battery Switching Station:
Adoption and Environmental Impact
Buket Avci
We analyze a novel switching-station based business model for the deployment of electric vehicles. We develop a stylized analytical model
that captures the salient features of EV adoption decision by modeling
range anxiety and the impact of different ownership structures (selling miles vs. selling batteries). We find that electric vehicles with
switching stations can incent adoption and reduce oil dependence but,
paradoxically, this increased adoption may not necessarily benefit the
environment.
4 - Combinatorial Optimization to Energy Management
of an Electric Vehicle
Pierre Lopez, Yacine Gaoua, Stéphane Caux
This communication addresses energy management in a multi-source
Hybrid Electric Vehicle. Assuming the objective to minimize hydrogen
consumption of a fuel cell system, as well as, possibly, a battery discharge, and considering the characteristics of the sources constituting
the energy chain of the vehicle involving efficiency and energy losses,
we propose a combinatorial linear modeling to solve the problem to
optimality. Simulations performed on realistic mission profiles lead to
drastically reduced computation times compared to dynamic programming and quasi-Newton methods used previously.
TA-09
Tuesday, 8:30-10:00 - Room 121
Enumeration and Discrete Structures
Stream: Dynamical Systems and Mathematical Modelling in OR
Invited session
Chair: Yasuko Matsui
1 - A Fast Algorithm for Counting the Number of Primitive Sorting Networks
Yuma Tanaka, Atsuko Ikegami, Yasuko Matsui, Katsuki
Fujisawa, Yuichiro Yasui
We address the problem of counting the number of distinct primitive
sorting networks that have a minimal number of comparators for a sequence of n elements. Primitive sorting networks are important models
in mathematics and engineering. The number of such networks is also
the number of oriented matroids of rank 3 on n elements, the number
of Amida-Kuji with minimum bars for reversing a sequence, and the
numbers of other interesting structures. We developed a fast algorithm
for this problem. We present the number of networks for n = 14 and
15, which were previously unknown.
2 - Enumeration of Combinatorial Structures Using Oriented Matroids
Hiroyuki Miyata
Oriented matroids are abstract structures, which provide a unified setting to study various objects such as point configurations and polytopes. In the context of enumeration, they are useful intermediate
structures for enumerating various objects.
In this talk, we explain our recent work on enumerations obtained
by using oriented matroids. It includes enumeration of combinatorial types of point configurations and polytopes (with K. Fukuda and
S. Moriyama), that of P-matrix linear complementarity problem (with
K. Fukuda and L. Klaus), and that of neighborly polytopes (with A.
Padrol).
3 - Enumeration of All Paths Between All Pairs of Vertices by Zero-Suppressed Binary Decision Diagrams
Takashi Horiyama, Koichi Adachi
We consider the problem of enumerating all simple (i.e., vertexdisjoint) paths in a given graph. Knuth proposed an efficient algorithm
for enumerating all s-t paths by Zero-Suppressed Binary Decision Diagrams (ZDDs). It can be considered as one of DP-like algorithms. The
key of the algorithm is to share search-nodes by simple knowledge of
subgraphs. We can generalize this algorithm to enumerate all paths between all pairs of vertices. In this talk, we propose another algorithm
by adding some knowledge on the constructing subpaths. We also give
the experimental results.
80
4 - Enumerating all the Optimal Cost Vertex Coloring of
1-Trees
Yasuko Matsui
In this talk, we propose an algorithm for enumerating all the optimal
cost vertex colorings of given 1-trees without repetitions if the optimal
cost vertex coloring is not unique. In general, the optimal cost vertex
coloring problem is NP-hard for arbitrary graphs. However, there is a
linear time algorithm for trees. Recently, we first gave an enumeration
algorithm for the problem. Our algorithm is also polynomial delay
algorithm. By extending our results, we show the first enumeration
algorithm for the optimal cost vertex coloring of given 1-trees.
TA-10
Tuesday, 8:30-10:00 - Room 122
Decision Support Models for the Energy
Industry I
Stream: Optimization Models and Algorithms in Energy
Industry
Invited session
Chair: Andres Ramos
1 - Accelerating the Convergence of Stochastic UnitCommitment Problems by Using a Tight and Compact MIP Formulation
German Morales-Espana, Claudio Gentile, Andres Ramos
MIP-based Stochastic Unit Commitment (SUC) problems are computationally intensive. Research have been focused on improving computer power and solving algorithms, but not on the quality of the MIP
formulation, which actually defines its computational complexity. Creating tight or compact computationally efficient MIP formulations is
a non trivial task because the obvious formulations are very weak or
very large. We propose an SUC that is simultaneously tight and compact. Consequently, the computational burden is dramatically reduced
in comparison with common SUC formulations.
2 - Optimal Management of Virtual Power Plants in Liberalised Markets
Pedro Sánchez-Martín, Andres Ramos, Javier
García-González
The communication shows the impact of new entrant technologies in
liberalized electricity markets that could choose Virtual Power Plant
(VPP) as a business or operation model. At the same time a generic
model is presented matching liberalized energy markets and VPP implementation. Different technologies are detailed as generation and
consumption VPP components, where VPP acts as aggregator and demands side manager. The study uses a unit commitment model within
a full year time-span. The Spanish Case Study shows how VPP implementation could benefit the electric system in terms of system costs
3 - Operation Reserve Usage for Different Unit Time Periods of a Stochastic Unit Commitment
Andres Ramos, German Morales-Espana, Javier
García-González, Michel Rivier
We analyze the behavior of an IEEE test electric system under different
unit commitment (UC) time periods and scenarios of wind generation
uncertainty and observe the effects in the use of operation reserves.
Firstly, we run a stochastic UC day-ahead planning model where the
unit time period can be 15, 30 and 60 minutes and the commitment
decisions are taken. Then, a 5-minute economic dispatch (ED) model
is run for all the wind generation scenarios to evaluate the operation of
the system with the previously determined UC decisions. We present
the results based on the simulation of the ED.
IFORS 2014 - Barcelona
4 - An Investigation about Package MINOS and Optimal
Power Flow Problem
Edmea Cássia Baptista, Adilson Preto de Godoi, Edilaine
Soler
In this paper, we investigate a method for the solution of Optimal
Power Flow problem which is formulated as a large scale, non-convex,
constrained, nonlinear problem. This method uses the linearization
of constraints, an Augmented Lagrangian and the Reduced Gradient
Method. The numerical tests are realized utilizing its implementation
in the package MINOS, into the GAMS system. The results are presented for different electrical systems, different initialization of the parameters and they are compared with the results obtained by package
KNITRO which uses an Interior Point/Trust region method.
TA-11
Tuesday, 8:30-10:00 - Room 113
Mixed-Combinatorial Methods in Distance
Geometry
Stream: Combinatorial Optimization
Invited session
Chair: Leo Liberti
1 - Universal Rigidity of Bar-and-Joint Frameworks and
Distance Geometry
Abdo Alfakih
A configuration p in r-dimensional Euclidean space is a finite set of labeled points that affinely span this r-dimensional space. Each configuration p defines a Euclidean distance matrix D. A fundamental problem
in distance geometry is to find out whether or not a given subset of the
entries of D suffices to uniquely determine the entire matrix D. This
problem is equivalent to the problem of universal rigidity of bar frameworks. In this talk, I’ll discuss necessary and sufficient conditions for
the universal rigidity of bar frameworks.
2 - Algorithms for Unassigned Distance Geometry Problems Arising in Molecule and Nanoparticle Atomic
Structure Determination
Phil Duxbury, Saurabh Gujarathi, Simon Billinge, Pavol
Juhas, Luke Granlund
Crystallography is effective in solving the structure of materials and
proteins, however preparing large enough crystal samples is difficult.
Finding the atomic structure of non-crystalline or nano-crystalline materials is the key challenge in this area. NMR of proteins or scattering experiments in other materials often yield a list of inter-atomic
distances and we seek to invert the distance lists to find atomic structure. We will describe two algorithms we have developed to solve the
unassigned distance geometry problems arising in molecular and nanoparticle atomic structure determination.
3 - The Importance of Atom Orderings in Distance Geometry Applied to Protein Structure Determination
Carlile Lavor
Distance Geometry is related to the problem of finding an embedding
of a weighted undirected graph G in some space, where there is an edge
between two vertices if their relative distance (the weight associated to
the edge) is known in such space. A very interesting application arises
in the field of biology, where experiments of Nuclear Magnetic Resonance are able to estimate distances between some pairs of atoms of a
protein and the problem is to determine the 3D protein structure based
on the distance information. We will discuss the importance of atom
orderings in solving this problem.
4 - Exact and Approximate Methods for Large Scale Distance Geometry Problems
Leo Liberti
The Distance Geometry Problem (DGP), which asks to find a graph realization in a K-dimensional Euclidean space given K and a weighted
graph, is an NP-hard problem with applications to clock synchronization, wireless sensor network localization, protein conformation, control of autonomous vehicles and more. We present fast exact and approximate methods for solving such problems.
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Tuesday, 8:30-10:00 - Room 004
Graphs and Networks V
Stream: Graphs and Networks
Invited session
Chair: Pavel Irzhavski
1 - Improved Bounds on the Generalized Acyclic Chromatic Number
Guiying Yan, Yuwen Wu
An r-acyclic edge chromatic number of a graph G is the minimum
number of colors used to produce an edge coloring of the graph such
that adjacent edges receive different colors and every cycle C has at
least min(|C|, r) colors. We prove that the r-acyclic edge chromatic
number of a graph G is not larger than (4r + 1)Delta(G), when the girth
of the graph G equals to max(50, Delta(G)) and r ranges between 4
and 10. If we relax the girth restriction to max(220, Delta(G)), the upper bound of the r-acyclic edge chromatic number of a graph G is not
larger than (2r+5)Delta(G) with r between 4 and 10.
2 - New Technique of Coloring of Vertices in the Graphs
Abdelouhab Aloui, Kamal Amroun
The vertex coloring problem has received much interest these later
years. If each vertex of the graph G can be assigned one of the k
colors, such that adjacent vertices get different colors we say that G
is k-colorable. The smallest sufficient number of colors is called the
chromatic number of G. The problem consists of giving the chromatic
number of G. In this paper we give a new technique for the determination of the chromatic number of certains classes of graphs.
3 - A Fast Greedy Sequential Heuristic for the Graph
Colouring Problem
Larisa Komosko
In this talk we present a fast greedy sequential heuristic for the graph
colouring problem. Its high performance is based on two improvements. First after colouring the current vertex we mark its colour as
forbidden for its neighbours. Second we calculate a colour for the current vertex and forbid it for its neighbours by means of bitwise operations with adjacency and colour matrices. In the colour matrix c_ij=1 if
vertex j can be coloured in colour i and c_ij=0 if colour i is forbidden
for it. In comparison with the classical greedy heuristic the speedup
reaches 100 times on DIMACS instances.
4 - On the Complexity of the Hamiltonian Cycle Problem
in Locally Connected Graphs
Pavel Irzhavski
Chartrand and Pippert (1974) proved that a locally connected graph of
maximum degree at most 4 and nonisomorphic to K(1,1,3) is Hamiltonian. Gordon et al. (2011) showed that a connected locally connected
graph of maximum degree 5 and minimum degree at least 3 is Hamiltonian. They also showed that the Hamiltonian cycle problem is NPcomplete in locally connected graphs of maximum degree 7 and conjectured that bounding the maximum degree to 6 makes the problem
polynomially solvable. We proved that the problem is NP-complete
even for planar locally connected graphs of maximum degree 5.
TA-13
Tuesday, 8:30-10:00 - Room 123
Project Scheduling 2
Stream: Scheduling
Invited session
Chair: Servet Hasgul
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1 - Project Scheduling with Rework: An Application in
the Animation and Videogame Industry
Gonzalo Enrique Mejia Delgadillo, Karen Niño, Maria
Angélica Sánchez Olaya
This research presents a Petri Net-based approach for project scheduling with rework. The modeling of the project activities and the associated resources is accomplished via a Timed Place Petri Net. The static
schedule is generated with a Beam Search algorithm which explores
the Petri Net state space. The same algorithm is adapted to handle
reworks. In this way we are able to calculate a more realistic schedule and simulate its execution. We test our approach on a real project
from the Animation and Videogame (A&V) industry and compare the
results versus the current practice.
2 - Multimode TCSP with Generalized Temporal Constraints: A MILP Formulation
Tamara Borreguero, Miguel Ortega-Mier, Álvaro
García-Sánchez
In this work, we present an Event Based MILP formulation for a Multimode Time Constraint Scheduling Problem of direct application for
some industries, such as aeronautical assembly lines. Taking as a starting point a RCSP Event Based MILP formulation, our contribution is
threefold: we include the allowance of multiple modes per task as well
as the use of more general temporal constraints. Also it has been dealt
as a TCSP rather than a RCSP. This alternative approach is more suitable for some industries where the total makespan is usually fixed by
the production rate or the client demand.
3 - A Project Scheduling Algorithm Considering Resource Constraints and Seasonal Effects
Servet Hasgul, Cem Atasever
A resource-constrained project scheduling problem aims at scheduling a set of activities at minimal duration subject to precedence and
limited resource availabilities. Resource costs and resource capacities
may change seasonally. In this situation, resource scheduling has to
be done by considering the seasonal variations. While the resource
costs are under seasonal variations, the total cost is aimed to be minimized. In this study, an algorithm is designed for resource constrained
project scheduling with seasonal variation, and some experiments are
conducted on the test problems.
TA-14
Tuesday, 8:30-10:00 - Room 124
DEA in Transportation and Logistics
Stream: DEA Applications
Contributed session
Chair: Carlos Ernani Fries
1 - Evaluating the Operational Efficiencies of Bus Transit Systems Considering Air Pollution
Chao-Chung Kang
This paper employed slack-based measure models with and without
undesirable outputs to assess the technical efficiency for bus transit
firms because air pollution factors were seldom incorporated in analysis efficiency before. A case study with 12 bus transit firms for
years 2007-2010 is conducted. The results indicate that the efficiency
scores obtained from the SBM without undesirable outputs are estimated more than those with the undesirable outputs. In addition, the
technical efficiency with air pollution emissions has significantly differed from that without considering them.
2 - Taking Fleet Commonality Beyond Aircraft Types —
Applying DEA Models to Evaluate the Impact of Engine Heterogeneity on Airline Cost Efficiency
Rico Merkert
This paper applies bootstrapped two-stage DEA models to fleets of 44
airlines to establish whether, among other factors, engine commonality impacts on airline cost efficiency. Previous research has shown that
strategic fleet management can significantly improve technical, allocative and cost efficiency of airlines. At the airline company rather than
group level, fleet commonality is a key variable in reducing operating
cost. We aim to take the focus beyond aircraft types as we argue that
engines, in addition to frames, are substantial components in terms of
both capital and operating cost.
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3 - Efficiency Analysis of Seaport Container Terminals
in Brazil
Cristiano Morini, Matheus Mauricio, Anibal Azevedo,
Rodolfo Cunha, Edmundo Ignacio Junior, Antônio Moretti
The increase of flow of goods through Brazilian seaports has revealed
inefficiencies in operations. This study aims to identify relative efficiencies in main seaport container terminals in Brazil. The method
considers the Data Envelopment Analysis (DEA). Berth extension and
stowage available area are input variables. Outputs are container movements, mooring services, and tons of cargo stowed in containers. A
sensibility analysis was included. The biggest port in number of container movements in Brazil, Port of Santos, does not achieve upper
levels in the variables observed.
4 - Scale Efficiency Analysis of Brazilian Logistic Service Providers (LSP) that Operate in Cold Supply
Chains
Carlos Ernani Fries, Ismael Peruzzo Zamoner, Fernanda
Christmann
LSP operating in cold supply chains have significantly expanded operations in Brazil since this country became a major producer and exporter of meat and its products. A scale efficiency analysis for these
LSP using Data Envelopment Analysis is here presented. A classification into groups of LSP that make use or not of third fleet suggests
that outsourcing transportation activities tend to project operations on
a more appropriate scale. An analysis of the scale efficiency over time
shows that the sector still supports LSP expansion, either by acquiring
companies or by increasing own capacity.
TA-15
Tuesday, 8:30-10:00 - Room 125
Behavioral Research in Pricing and
Revenue Management
Stream: Revenue Management II
Invited session
Chair: Ioana Popescu
1 - Dynamic Pricing in the Presence of Social Learning
and Strategic Consumers
Nicos Savva, Yiangos Papanastasiou
When a product of uncertain quality is first introduced, consumers may
be enticed to strategically delay their purchasing decisions in anticipation of the product reviews of their peers. This paper investigates how
the presence of social learning interacts with the adoption decisions of
strategic consumers and the dynamic-pricing decisions of a monopolist firm, within a simple two-period model. We examine two cases:
pre-announced and responsive pricing.
2 - Pricing with Anticipation
Javad Nasiry, Ioana Popescu
We study a market where customers derive emotional utility from anticipating pleasurable purchase outcomes, but experience disappointment if outcomes fall short of what they anticipated. In this context,
we show that firms can profit by adopting randomized pricing policies.
3 - Impact of Price Recommendation Tools by Salespeople
Wedad Elmaghraby
We investigate how salespeople use the information provided to them
to set the prices; of particular interest to us is how salespeople use price
recommendations coming from a decision support tool. We do this by
building reduced-form models and testing those on a data set obtained
by a grocery products distributor. We identify customer-specific and
salesperson-specific market factors that moderate the influence of the
price recommendations.
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4 - Social Influence and Customer Spending in Online
Games
Ioana Popescu, Yue Wu, Paddy Padmanabhan
1 - A DC Programming Approach for Sparse Linear Discriminant Analysis (LDA)
Duy Nhat Phan, Hoai An Le Thi
Monetization is a major challenge for companies offering free-to-play
online games. Using a unique and very rich industry data set, we investigate the determinants of customer spending in an online multi-player
computer game. In particular, our empirical analysis quantifies the effect of social influence on customer spending.
LDA is a standard tool for classification and dimension reduction in
many applications. However, the problems of high dimension is still a
great challenge for the classical LDA. We present a novel approach to
the sparse LDA and develop a sparse version of mixture discriminant
analysis. Our work is based on the optimal scoring and the zero-norm.
The difficulty in treating the zero-norm is overcome by using an appropriate continuous approximation such that the resulting problem can
be formulated as a DC (Difference of Convex functions) program to
which DCA (DC Algorithms) is investigated.
TA-16
Tuesday, 8:30-10:00 - Room 127
Copositive and Polynomial Optimization V
Stream: Copositive and Polynomial Optimization
Invited session
Chair: Immanuel Bomze
1 - Towards Absolute Delivery Schedule Reliability in
Container Liner Shipping Using Copositive Cones
Zhichao Zheng, Abraham Zhang, Siu Lee Lam, Chung Piaw
Teo
Container liner shipping is crucial to global supply chain performance
as it is the primary mode of moving goods across continents. Partly
due to inherent uncertainties at sea and ports, the liner shipping industry has long had a notorious reputation of schedule unreliability.
We exploit the connection between distributionally robust optimization
and conic programming to formulate a copositive programming model
for the liner scheduling problem. Comprehensive analysis of copositive schedules with real data and a detailed simulation model reveals
interesting insights on liner schedule design.
2 - Copositive Optimization Based Bounds on Box Constrained Quadratic Optimization
Gizem Sağol, E. Alper Yildirim
Box constrained quadratic optimization problems (BoxQPs) can be
formulated as a linear optimization problem over the cone of completely positive matrices in several different ways. We consider two
alternative formulations. We study the sequences of upper and lower
bounds on the optimal value of a BoxQP arising from two hierarchies
of inner and outer polyhedral approximations for both of these formulations.
2 - DC Programming and DCA for Solving Binary
Quadratic over a Special Polytope
Hoai An Le Thi, Tao Pham Dinh, Hoai Minh Le
The problem is first equivalently reformulated as quadratic minimizations over a polytope with the help of exact penalty whose penalty
parameter is known. Appropriate DC decompositions and their resulting DCA are investigated for solving the corresponding DC programs.
Some choice strategies of initial points for DCA via DC/SDP relaxation are developed. Finally computational experiments are conducted
on some real-world problems.
3 - Feature Selection for Ranking based on DC Programming and DCA
Hoai Minh Le, Hoai An Le Thi, Tao Pham Dinh
Ranking is a very important topic and has recently emerged as a crucial issue. Given a set of objects, ranking methods compute a score for
each of them and then the objects are sorted according to the scores.
We deal with the problem of feature selection in Ranking. The problem can be formulated as a mixed integer quadratic program. We first
reformulate the original problem as a continuous one then develop an
efficient algorithm based on DC programming and DCA for solving
the resulting problem. Numerical experiments on real world datasets
show the efficiency of the proposed method.
4 - The Performance of the Flying Elephants Approach
for Solving Traditional Non-Differentiable Problems
Adilson Elias Xavier, Vinicius Layter Xavier
Flying Elephants is a generalization and a new interpretation of the Hyperbolic Smoothing approach. The name is definitely not associated to
any analogy with the biology area. It is only a metaphor. The Flying
feature is directly derived from its differentiability property, which permits intergalactic trips of the Elephant into spaces with large number of
dimensions, differently of the short local searches associated to traditional heuristics. Computational results for solving distance geometry,
covering, clustering, Fermat-Weber and hub location problems show
the performance of the approach.
3 - Completely Positive Reformulations for Polynomial
Optimization
Luis Zuluaga
There is a well-established body of research on quadratic PO problems
based on reformulations of the original problem as a conic program
over the cone of completely positive (CP) matrices. We consider PO
problems that are not necessarily quadratic and provide a general characterization of the class of PO problems that can be formulated as a
conic program over the cone of CP tensors. As a consequence, it follows that recent results for quadratic problems can be further strengthened and generalized to higher order PO problems.
TA-17
Tuesday, 8:30-10:00 - Room 005
Nonconvex Programming: Local and
Global Approaches I
Stream: Global Optimization
Invited session
Chair: Hoai An Le Thi
Chair: Tao Pham Dinh
TA-18
Tuesday, 8:30-10:00 - Room 112
Robustness in Multiobjective
Optimization I
Stream: Multiobjective Optimization - Theory, Methods
and Applications
Invited session
Chair: Christiane Tammer
Chair: Alexander Engau
1 - A Unified Approach for Different Concepts of Robustness and Stochastic Programming via Nonlinear
Scalarizing Functionals
Christiane Tammer, Kathrin Klamroth, Elisabeth Köbis, Anita
Schöbel
We show that many different concepts of robustness and of stochastic
programming can be described as special cases of a general nonlinear scalarization method by choosing the involved parameters and sets
appropriately. This leads to a unifying concept which can be used to
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handle robust and stochastic optimization problems. Furthermore, we
introduce multiple objective (deterministic) counterparts for uncertain
optimization problems and discuss their relations to well-known scalar
robust optimization problems by using the nonlinear scalarization concept.
2 - The Relationship Between Multicriteria Robustness
Concepts and Set-Valued Optimization
Elisabeth Köbis, Christiane Tammer, Anita Schöbel, Daishi
Kuroiwa, Jonas Ide
We present connections between concepts of robustness for uncertain multi-objective optimization problems and set-valued optimization. We extend some of the existing concepts to general spaces and
cones. Furthermore, we derive new concepts of robustness for multiobjective optimization problems using different set relations. We point
out that robust multi-objective optimization can be interpreted as an
application of set-valued optimization. Finally, we provide algorithms
for solving uncertain multi-objective optimization problems.
3 - Pareto Efficiency in Robust Optimization
Nikos Trichakis, Dan Iancu
We formalize the concept of Pareto efficiency in the context of the robust optimization (RO) methodology. We characterize Pareto robustly
optimal (PRO) solutions, and extend the RO framework by proposing
methods to verify Pareto optimality and generate PRO solutions. Our
approach requires solving problems that are of the same complexity as
the nominal RO problems, and numerical experiments demonstrate the
significant potential upside of PRO solutions compared with classical
RO solutions.
4 - Trade-Offs - A Lost Dimension in Robust Optimization?
Alexander Engau
This presentation explores a question similar to the one posed by Ignacy Kaliszewski in his paper "Trade-Offs - A Lost Dimension in Multiple Criteria Decision Making" in 2002. We will investigate the role
of tradeoffs in robust compared to stochastic optimization and subsequently offer several new approaches to compromise between advantages and drawbacks of these two different paradigms. Our discussion
will both address relationships to scalarization functions in multiobjective programming and provide several new results about the existence
and characterization of properly efficient solutions.
TA-19
Tuesday, 8:30-10:00 - Room 128
Retail Forecasting
Stream: Demand and Supply Planning in Consumer
Goods and Retailing
Invited session
Chair: Kai Hoberg
1 - Weather Effect on Apparel Sales in France
Jean-Louis Bertrand, Xavier Brusset
In 2012, French apparel industry suffered weak sales for the fifth consecutive year. Trade professionals feel that the weather played a significant role. Its impact on retail sales in general has not been formally
quantified. This is an urgent issue for managers in climate-sensitive
sectors as climate change is aggravating naturally occurring climate
variability. In this paper we provide managers with tools to evaluate
the impact of temperature anomalies on sales volumes. We present a
statistical method to separate out the weather effect from the underlying real performance of apparel sales.
3 - Collaborative Forecasting and Channel Coordination
in a Perishable Goods Chain
Jan van Dalen, Clint Pennings
We examine the collaborative forecasting process in a perishable goods
chain with one supplier and many different retailers. The supplier has
access to the point-of-sales data of its retailers and recommends an
order quantity per SKU for each store (this recommendation also includes an assortment proposition). The retailer can accept this offer
or propose a different quantity, after which they jointly decide on a final number. We analyze how this channel coordination process was set
up, how it is affected by the forecast performance, and how the process
changes over time.
4 - Public Forecast Information Sharing in a Market with
Competing Supply Chains
Noam Shamir, Hyoduk Shin
Studying the operational motivation of a retailer to publicly announce
his forecast information, this paper shows that by making forecast information publicly available to both his manufacturer and to the competitor, a retailer is able to credibly share his forecast information - an
outcome that cannot be achieved by merely exchanging information
within the supply chain. We show that just by announcing his forecast
publicly a retailer can induce the manufacturer to invest in the proper
capacity level.
TA-20
Tuesday, 8:30-10:00 - Room 129
From the Old to the New: Managing the
Transformation of our Energy System
Stream: Stochastic Optimization in Energy
Invited session
Chair: Valerie Thomas
1 - Learning in Optimization: Integrated Assessment
Modeling of Climate Change under Uncertainty
Soheil Shayegh, Valerie Thomas
We develop a method for finding optimal greenhouse gas reduction
rates under uncertainty from climate parameters. Uncertainty about
climate change includes both overall climate sensitivity and the risk of
extreme tipping point events. We introduce a two-step-ahead approximate dynamic programming algorithm to solve the finite time horizon
stochastic problem. The uncertainty in climate sensitivity may narrow
in the future as the behavior of the climate continues to be observed
and as climate science progresses. We use a Bayesian framework to
update the two correlated uncertainties over time.
2 - Grid Integration Costs and the Optimal Climate
Change R&D Portfolio
Robert Barron, Noubara Djimadoumbaye, Erin Baker
Many low carbon energy technologies incur integration costs when
connected to the grid. This paper examines the impact of grid integration costs on the optimal energy technology R&D portfolio for minimizing the cost of climate change. This paper’s goal is to place bounds
on the size of the problem, and to determine under what circumstances
integration costs are relevant to policy design. This research finds the
importance of getting grid integration costs right depends on the specific question that is being asked: how to allocate a given budget, or
what the size of the budget should be.
2 - The Influence of Weather in Online Retailing - An Empirical Analysis
Kai Hoberg, Sebastian Steinker
3 - Optimisation of Intelligent Oil Wells using Stochastic
Algorithms
Morteza Haghighat Sefat, Khafiz Muradov, Ahmed ElSheikh,
David Davies
In this paper, we incorporate weather information into the sales forecast of a European online fashion retailer. Based on actual weather
information we find a highly significant impact of sunshine, temperature and rain, in particular in the summer, on weekends and on days
with extreme weather. Our analysis highlights that daily fluctuations of
online sales, that are attributable to the weather effect, can be as much
as 18.8%. Using weather forecasts we are able to improve the forecasting accuracy by an incremental 62.4% on weekends that require
special attention from a logistics perspective.
Oil production enhancement in intelligent fields is a nonlinear, highdimension, conditional optimisation problem with a computationally
expensive objective function. Stochastic estimated-gradient-based optimisation algorithms have proved to be an effective tool to solve
this class of problems. Solutions to this challenging problem using
the Simultaneous Perturbation Stochastic Approximation (SPSA) and
Ensemble-based Optimisation (EnOpt) algorithms are evaluated and
their performance compared for multiple case studies. Optimisation
guidelines will also be provided.
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4 - Understanding the Diffusion of Residential Solar
Panels using a Hazard Rate Model
Sebastian Souyris, Varun Rai
In this talk we will discuss the diffusion of residential solar panels in
the US. What types of households are keener to install solar PV? What
factors enter into account in the decision process? What types of marketing campaigns are more efficient to incentivize adoption? Is word
of mouth playing a role in the diffusion? In what degree the historic
and forecasted electricity prices do affect the adoption decision? To
answer these questions, we collect a detail adopters data set and we
cross it with other data streams. We analyze these data using a Hazard
Rate Model.
TA-21
Tuesday, 8:30-10:00 - Room 006
Optimization Modeling Applications in
Manufacturing 1
Stream: Optimization Modeling in OR/MS
Invited session
Chair: Tugba Saraç
1 - Minimisation of Production Costs and Chemical Pollutants in a Tin Foundry Plant
Janis Martinez, Juan Cabrejos
The investigation consisted in the design of a mathematical model,
adapted from Kim and Lewis (1987), which allows the reduction of
production costs in a tin foundry operation and the reduction of pollutants. This investigation was motivated by the insufficient quantitative
techniques in the production programming around foundry operations,
where the effect a batch has over others is not considered. After testing the model, the results indicated estimated savings of $1’192,433
per year, an estimated saving of 23% in the use of the melting furnace
and a decrease in the content of pollutants.
2 - Advanced Optimization and Simulation-based Tool
for Complex Automated Manufacturing Systems
Natalia Basán, A. Carlos Mendez-Aguirre
A unified computational decision-making tool based on mixed integer
programming, discrete-event simulation and improvement-based approaches for the efficient operation of complex industrial processes
will be presented. The principal aim of this work is to provide a
computer-aided tool for solving industrial-scale automated flow-shop
scheduling problems in a computationally efficient way. We will centre
our attention in a real-world problem arising in the automated wet-etch
station during the fabrication of wafer’s lots in the semiconductor manufacturing industry.
3 - A Multi-Objective Optimization Approach for Plastic
Injection Molding Machine Scheduling Problem
Tugba Saraç, Aydin Sipahioglu
In this study, the multi-objective plastic injection molding machine
scheduling problem is considered. Since this problem is a very complicated one, a two stepped solution approach is proposed. In the first
step, a goal-programming model is used for assigning jobs to the machines. In the second step, schedules of each machines are obtained
using another mathematical model. In order to show the performance
of the proposed solution approach, randomly generated instances are
solved using the GAMS Cplex solver and obtained results are presented.
4 - Project Selection with Uncertain Lifetime and Initial
Outlay
Xiaoxia Huang, Qun Zhang
In traditional project selection, lifetimes of candidate projects are all
treated as deterministic numbers, which is usually not suitable in real
life. In this paper, we treat the projects lifetimes as uncertain variables.
In addition, considering the complex of real world, we also regard the
initial outlays of the candidate projects as uncertain variables. Using
uncertainty theory, a new optimization project selection model is developed. In addition, to help investors use the existing tools to solve the
problem, the deterministic equivalents of the model is also provided.
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TA-22
Tuesday, 8:30-10:00 - Room 007
Cooperation in Operations Management
Stream: Game Theory and Operations Management
Invited session
Chair: Ana Meca
Chair: Ignacio García-Jurado
1 - Cost Allocation in Inventory Pools with ServiceDifferentiated Demand Classes
Mario Guajardo, Mikael Rönnqvist
We consider an inventory pool subject to a service level constraint,
where the members of the pool may have different target service levels. This occurs, for example, in inventory of spare parts for oil and
gas operations. We show examples where a cost allocation method results in core-stable allocations when the members have the same target
service levels, but not when these targets differ. In order to deal with
this problem, we propose the novel Minimum Deviation from the Service Level Referential Cost Method (MIND). The resulting allocation
is core guaranteed, if the core is not empty.
2 - Cooperation in Service Systems: The 3-D Assignment M/G/c/c Game
Shoshana Anily
We consider a cooperative game that consists of a number of M/G/c/c
queuing systems (players), each is associated with a Poisson arrival
rate, mean service rate, and a room size. The cost of a system is the average number of lost (blocked) customers. When a coalition of systems
is formed, the service rates and room sizes are reassigned to the arrival
rates in order to minimize the average number of lost customers. This
3-D assignment (bi-permutation) problem is NP-complete. Interesting
results on the balance and on the core of this cooperative game will be
presented.
3 - Centralized Inventory in a Farming Community
Manuel Alfredo Mosquera Rodríguez, Ma Gloria
Fiestras-Janeiro, Ignacio García-Jurado, Ana Meca
A centralized inventory problem is a situation in which several agents
face individual inventory problems and make an agreement to coordinate their orders with the objective of reducing costs. In this paper we
identify a centralized inventory problem arising in a farming community in northwestern Spain, model the problem using two alternative
approaches, find the optimal inventory policies for both models, and
propose allocation rules for sharing the optimal costs in this context.
4 - Cooperation in Capacitated Inventory Situations with
Fixed Holding Costs when Shortages are Allowed
Ignacio García-Jurado, Ma Gloria Fiestras-Janeiro, Ana Meca,
Manuel Alfredo Mosquera Rodríguez
We analyze a situation in which several firms deal with inventory problems concerning the same type of product. Each firm uses its limited
capacity warehouse for storing purposes and faces an economic order
quantity problem where storage costs are irrelevant and shortages are
allowed. We show that firms can save costs by placing joint orders and
we obtain an optimal order policy for the firms. Besides, we identify
an associated class of cost games which we show to be concave. Finally, we introduce and study a rule to share the costs among the firms
which provide core allocations.
TA-23
Tuesday, 8:30-10:00 - Room 008
Behavioural Issues in Problem
Structuring
Stream: Behavioural Operational Research
Invited session
Chair: Leroy White
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1 - Exploring Novice Facilitated Modelling Supported by
Scripts
Elena Tavella, Thanos Papadopoulos
There is limited research on how novice facilitators use scripts to successfully manage Facilitated Modelling (FM) and achieve workshop
outcomes. We explore this gap by presenting a micro-level analysis of
a transcript from a FM workshop held in a food cooperative in Denmark. We identify two distinct script-supported FM behaviours and related facilitation practices that enable novices to (a) acquire skills and
technical competencies; and (b) switch between and combine skills and
technical competencies to successfully manage workshops and achieve
outcomes.
2 - Coat-Tailing Behaviour in Decision
Isabella Lami, Leroy White
Most of the practice-based studies of the process of OR does not explicitly consider the issues relating to visualisation and boundary objects. By building on the concepts drawn from activity theory, we identify several patterns of behaviour and enactments in practice. Empirical evidence is based on a post- analysis of two infrastructure projects.
Our findings show that successful collaboration is based on coat-tailing
systems. Coat-tailing means to inextricably bind together individual
action and collective activity through careful design of technological,
mental and cultural artefacts.
3 - Behavioural Issues in PSMs
Leroy White
Problem structuring settings functions most obviously as a vehicle for
knowledge exchange and mobilisation. However, they also play a valuable socio-psychological role, enabling the participants both to pass on
important facets of their understanding of the problem at hand while
continuing to want to make an impact on the organisational world they
are in. This paper will provide some thoughts on the behavioural aspects of PSM interventions, drawing on insights from situated social
cognition, social networks and systems thinking theories.
4 - Integrating TRIZ with DEMATEL to tackle a systematic problems on evaluating the cloud system for
long-term healthcare
Sam Liu, Dong Shang Chang, Yi-chun Chen
The methodology of TRIZ has been widely employed on technology
innovation and extended to resolve managerial decision issues. Although there are some useful approach being proposed to deal with
the misuse of mental models in TRIZ for identifying conflict among
resolutions, the generated alternatives might be little applicable in real
setting due to lacking of systematic analysis aspect. With newly development on DEMATEL approach, it strengthens the quality of decision
making by incorporate systematic viewpoint on risk. This study aims
to integrate the TRIZ with the DEMATEL for tackling systema
TA-24
Tuesday, 8:30-10:00 - Room 212
Ethics and OR I
Stream: OR and Ethics
Invited session
Chair: Cristobal Miralles
Chair: Fred Wenstøp
1 - Implications of Nomology for Ethics
Cathal Brugha
This paper uses nomology to develop a three-level model for ethics. At
the top level ethics focuses on commitment to values. At the middle
level ethics in company practice usually is about serving the interests
of the company, employees and the environment. At the lowest level
it is about implementing the above levels by making adjustments to
ensure that there is a balance between sets of issues such as responsibility, transparency, authority and accountability. The paper gives
examples of ethics’ codes of practice used by companies to show how
they illustrate the three-level model.
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2 - Operational Research Virtues in the Face of Climate
Change
Fred Wenstøp, Søren Wenstøp
To expect operational researchers to be virtuous has an honorable tradition, and virtues are even more important now in the context of climate
change. We identify scientists’ virtues that we believe are conducive
for work with mitigation, adaption, restoration, etc. This includes a
humble, accurate, and truthful understanding of the complex dynamic
processes, which are changing the world we live in. We present a simple dynamic model of the global energy balance, which demonstrates
the processes involved in global warming.
3 - Strengthening Decision-Making for Emergency Planning using Participatory Problem Structuring: A
Case of Operational Research in the New Zealand
Volunteer Sector
Robyn Moore
This is an account of collaborative decision-making for emergency
planning in the volunteer sector, using the problem structuring methodology Theory of Constraints in a facilitated World café-style workshop.
An emergency plan is ethically acceptable depending on its substantive content (what it tells people to do and the consequences of doing
it) and on the deliberative process used to approve it (Jennings, 2014).
The World café setting was used to gather rich data from 35 managers
of volunteers, while TOC was used to examine and represent their perspectives in a structured way.
4 - Ethical Rationality: Enriching Economic Rationality
with Values and Dreams
Marc Le Menestrel
Ethical Rationality articulates economic rationality with values that are
excluded from it. Taking the point of view of decision sciences, I summarize some key limitations of the economic paradigm of rationality
at the descriptive, normative and formal levels. I then show how extending this paradigm leads to a more open form of rationality, where
actors face dilemmas which can be objectively studied but do not necessarily have a normative solution. Descriptive observation of actual
behaviour reveals how these actors have chosen to give weight, or not,
to values beyond economic values.
TA-25
Tuesday, 8:30-10:00 - Room 009
Applications of Game Theory
Stream: Mathematical Economics
Invited session
Chair: Adriana Kroenke
1 - Multi-Criteria Games: Ranking of Companies using
Financial Indicators
Adriana Kroenke, Nelson Hein, Volmir Wilhelm
This research aimed to evaluate the accounting placement of the iron
and steel companies listed on the BM&Fbovespa (Brazil) in 2012 by
means of multi-criteria games, using four lots of financial indicators.
Reading is done using business strategies as player I and financial indicators as the strategies of player II. The first ranking was defined
through the methods suggested by Fernández, Monroy and Puerto
(1998). The second is an adaptation of the first, with the inclusion
of goals. The third ranking was inspired by the work of Sakawa and
Nishizaki (2001), using diffuse goals.
2 - Transboundary Environmental Problems: A Multicriteria Games Approach
Naouel Yousfi, Mohammed Said Radjef, Fazia
Aoudia-Rahmoune, Aichouche Oubraham
The present paper deals with transboundary environmental problems.
In order to incite the countries to join an international environmental agreement, we propose to link environmental negotiations to trade
negotiations. Several works are based on this idea, but considering
distinctly the two aspects. To avoid this limit, we used the multicriteria games. The constructed game is solved using the Pareto-Nash
equilibrium concept and an aggregation method. Thus, we determine
following the weights used in the aggregation method, the most favorable situation to the emergence of linked agreements.
IFORS 2014 - Barcelona
3 - Asymmetric Shapley-Shubik and Banzhaf Power Indices Applied on Real Voting Data
Elena Mielcová
The main aim of this paper is to compare the results of classical
Shapley-Shubik and Banzhaf power indices with results of the respective asymmetric power indices extended to the cooperative games with
real coalitions applied on the real data of the cooperative simple game
— in this case the data from the voting in the Lower House of the
Czech Parliament 2006-2013. Results indicate the improvement in predictability of the real power of existing political coalitions comparing
to the values based on the classical Shapley-Shubik and Banzhaf power
indices.
TA-26
Tuesday, 8:30-10:00 - Room 010
Fuzzy Decision Making 2
Stream: Fuzzy Decision Support Systems, Soft Computing, Neural Network
Invited session
Chair: Martin Gavalec
Chair: Jaroslav Ramik
1 - X-Simplicity of a (Strong) Tolerance Eigenvector and
an Interval Fuzzy Matrix
Ján Plavka, Martin Gavalec
Fuzzy matrices can be used in a range of practical problems related
to scheduling and fuzzy optimization. A fuzzy matrix is said to have
an X-simple image eigenspace if any eigenvector belonging to interval
vector X is the unique solution of the corresponding system fuzzy linear equalities in the interval vector. We present equivalent condition
for interval matrix and (strong) tolerance eigenvector to have an interval version of X-simple image eigenspace and polynomial algorithms
for checking of interval X-simplicity are introduced. Supported by the
grants APVV-04-04-12 and GACR-14-02-424S.
2 - Eigenspace Structure of a Max-Lukasiewicz Matrix
Zuzana Nemcova, Martin Gavalec
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TA-27
Tuesday, 8:30-10:00 - Room 213
Advances in Operations/Marketing
Interface
Stream: Operations/Marketing Interface
Invited session
Chair: Sirong Luo
Chair: Saravanan Kesavan
1 - A New Approach for Dynamic Inventory-Pricing Control
Sirong Luo
We study a single product, periodic review, finite horizon dynamic
inventory-pricing problem. Demand in each period is stochastic, nonstationary and nonlinear in price. We use a two parameter demand
model, which outperforms one parameter demand models and introduces analytical challenges in analyzing the dynamic program. Using
a variable transformation approach, we identify a new set of technical conditions under which the base stock list price policy is optimal.
These conditions are easy to verify because they depend only on the
location and scale parameters of demand as functions of price.
2 - The Impact of Treatment Technology Advancement
on the Operational Performance of Healthcare Systems
Chunyang Tong
Service quality is an important assessment criterion for a healthcare
service system. The capacity constraint of the healthcare system creates tension between the quality of service delivered and the number of
patients served, and the perception of service quality hinges upon the
service content provided and the system’s responsiveness. In this paper, we attempt to characterise the inherent relationship between different phases of service and investigate the impact of technology advance
in one phase on the overall service delivery.
3 - Considering the Effective Ad Promotion Tool by Palmore’s Cohort Analysis
Qin Nuo, Satoshi Takeuchi, Cong Tingting, Hong Seung Ko
Max-Lukasiewicz algebra belongs to the family of max-T fuzzy algebras. The multiplication of vectors and matrices in these algebras
uses the binary maximum operation and a triangular norm T (T is the
Lukasiewicz triangular norm in this contribution). Classification of
the eigenspace structure of a matrix over the max-Lukasiewicz algebra
will be presented. Computation of the basic characteristics of matrices will be illustrated by examples, and Illustrative graphs and spatial
representation of the eigenspace will be given.
Picking up an effective promotion tool for getting customers is a very
important issue connected with the company’s sales and profits. But,
we cannot say that in the changing business environment, the current
promotion tool with high effects is certainly useful in the future. Thus,
it is needed to prospect which promotion tool will produce a high effect in the future. We quantify the effect of promotion tools and then
analyze it with using data related to the current main promotion tool.
Consequently, we suggest the efficient promotion tool in the future by
Palmore’s cohort analysis.
3 - Topologies and Uniformities of Rough Set Approximations
Milan Vlach
4 - Coordination by Contracts in Distributed Product Development Processes with Complete Substitution
Kerstin Schmidt, Thomas Volling, Thomas Spengler
To extend the range of applicability, the original rough set theory has
been generalized from various viewpoints. We deal with two generalizations. One is based on replacing the equivalence relations by more
general binary relations, the second relaxes the partitions to more general coverings. First, we discuss relationships between set approximations in the relation-based and covering-based rough set models.
Then we draw attention to the important (and often overlooked) fact
that some approximation operators induce not only topologies but also
uniformities.
In distributed product development processes system integrators collaborate with suppliers to provide marketable products. Considering a
converging supply chain with two suppliers and one system integrator,
we apply a Stackelberg game to model the contract-based coordination
of such processes under uncertain development results, complete substitution and maximum price clause. Assuming uniformly distributed
development results, we analyze the coordination ability of a wholesale
price contract and a penalty contract and present numerical illustrations
of centralized and decentralized solutions.
4 - Tolerance Eigenproblem in Fuzzy Algebra
Martin Gavalec, Ján Plavka
The tolerance eigenproblem in fuzzy algebra concerns several important classification types of the interval eigenvectors which are motivated by the fact that most of the practical applications work with imprecise input data. The following types of tolerated eigenvectors will
be investigated: the strongly tolerated, the tolerated and the weakly
tolerated eigenvector. The existence and the description of such eigenvectors will be presented. The relations between the considered eigenvectors are also studied and illustrated by examples. Supported by the
grants APVV-04-04-12 and GACR-14-02-424S.
TA-28
Tuesday, 8:30-10:00 - Room 130
Challenge ROADEF/EURO 3
Stream: Challenge ROADEF/EURO
Award Competition session
Chair: Eric Bourreau
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TA-29
IFORS 2014 - Barcelona
1 - Two Phase Approach Combining Heuristic and Integer Programming for SNCF Rolling Stock Problem
Mirsad Buljubasic, Michel Vasquez, Haris Gavranovic, Saïd
Hanafi
We propose a two phase approach combining mathematical programming and heuristics for the ROADEF/EURO challenge 2014, dedicated
to the rolling stock management on railway sites problem proposed by
SNCF. In the first phase, a train assignment problem is solved with a
combination of a greedy heuristic and integer programming. The objective is to maximize the number of assigned departures while respecting technical constraints. The second phase consists of scheduling all
the trains in the station’s infrastructure while minimizing the number
of canceled departures, using a constructive heuristic.
3 - Selection of Investment Alternatives in Power Generation Expansion using Multiobjective and Multicriteria Optimization Methods
Mariantonieta Molina, Jose Ceciliano Meza, Néstor Raúl
Ortiz Pimiento
This research proposes a framework based on a linear programming
model to solve the multiobjective generation expansion planning problem in two phases. A Multiobjective method is used to decide the new
capacity to install. Then, a multicriteria method is used to select the
best alternative. Quantitative (economical, environmental) and qualitative (social, sustainability) criteria are considered. The projected
demand is satisfied considering renewable and conventional sources,
especially in places where there is not interconnection to the electrical
system, focusing in a Colombian case.
2 - Solving the ROADEF/EURO 2014 Challenge by a Double Column Generation Based Heuristic
Lucas Létocart, Marco Casazza, Antoine Rozenknop,
Emiliano Traversi, Roberto Wolfler-Calvo
4 - Educational Marketing Decision System Based on
Multicriteria Analysis: The e-Marketing Online Platform
Nikolaos Matsatsinis, Evangelos Grigoroudis
We present an exact formulation for the ROADEF/EURO 2014 Challenge based on an exponential number of variables and constraints. We
solve it heuristically using an exact separation algorithm for the incompatibility constraints and a double column generation for the scheduling and routing variables. The pricing problem for the train scheduling
consists of solving a matching problem that couples trains with departures and adding maintenance when needed. The pricing problem
for the train routing consists of solving a shortest path problem with
resource constraints on a discrete time horizon.
e-Marketing Online is a modern web application that aims to familiarize students or potential entrepreneurs with modern marketing techniques and product development decisions. Offering a virtual market environment of products that simulates real-world situations, eMarketing Online adopts the MARKEX methodology in order to enable users (or user teams) following modern marketing strategies.
Through this approach, users gradually learn how to effectively implement MCDA methods in order to take essential decisions about product
marketing or new product development.
TA-29
Tuesday, 8:30-10:00 - Room 011
Multiple Criteria Decision Making and
Optimization 2
Stream: Multiple Criteria Decision Making and Optimization
Contributed session
Chair: Nikolaos Matsatsinis
1 - Performance Evaluation of European Insurance
Companies: A Comparison of Robust MCDA Approaches
Constantin Zopounidis, Giacomo Nocera, Michael Doumpos,
Emilios Galariotis
In this study we apply and compare multicriteria models based on multiattribute value theory and outranking relations for the evaluation of
the financial performance of insurance companies. Emphasis is given
on the robustness of the results with respect to the specification of the
models’ parameters. The analysis is based on a large European sample over the period 2000-2012. At a second stage the multicriteria
results are analyzed to identify differences between countries as well
as to examine the role of non-financial attributes on the performance
of insurance companies.
2 - A Multicriteria Approach to Sort Time Series Models
Applied to Stochastic Scenarios Generation
Hugo Ribeiro Baldioti, Bruno Ribeiro, Fernando Luiz Cyrino
Oliveira, Reinaldo Souza
In the context of the Brazilian energy planning, some stochastic models are proposed for generating energy scenarios, whose adherence to
the historical data is measured by statistical criteria, applied independently. This paper proposes the development of a methodology able
to sort the models using a multicriteria approach, through the Analytic
Hierarchy Process. Aiding the decision maker, the proposed method
has been efficient and indicates, through sensitivity analysis of the attributes, the volatility of the alternatives, pointing at different options
from the current model.
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TA-30
Tuesday, 8:30-10:00 - Room 012
Financial Mathematics 3
Stream: Financial Mathematics and OR
Invited session
Chair: Teruyoshi Suzuki
1 - Optimal Capital Injection Problem under Financial
Crisis
Teruyoshi Suzuki
We will introduce an optimal capital injection problem and propose an
algorithm to solve it. The problem can be represented by a linear programming formulation under Eisenberg and Noe’s model. We present
a sequential method to solve both the firm’s payoff to debt holders and
the government’s capital injection to the firms. We will show that the
priority rule of capital injection does not depend on the amount of the
budget by the government.
2 - Multilevel Monte Carlo Simulation for Game Option
Hitoshi Inui, Katsunori Ano
In this talk, we present the valuation method of Game option (Kifer
(2000)) by multilevel Monte Carlo (MLMC) method that was originally developed by M.B. Giles (2008). From the view point of variance decaying, it has been reported that MLMC performance is superior to the performance of the standard Monte Carlo (SMC) method.
We use MLMC and SMC to price the Game options based on Ano’s
dynamic programming backward search algorithm (Suzuki, Seko and
Ano, RIMS Kokyuroku (2001)) . We compare the difference between
SMC and MLMC.
3 - Optimal Impulse Control for Cash Management with
Double Exponential Jump Diffusion Processes
Kimitoshi Sato, Atsuo Suzuki
We consider a cash management problem where the cash demand is
assumed to be double exponential jump-diffusion processes. We formulate the model minimizing the sum of the transaction and holdingpenalty costs as an impulse control model. The model reduces to the
problem of solving a Quasi-variational Inequality (QVI), and the function satisfying QVI is derived. We show that there is an optimal policy
of the two-band type. Moreover, we discuss the effect of jumps on the
optimal policy through some numerical examples.
IFORS 2014 - Barcelona
4 - American Double Exercise Put Option on Geometric
Random Walk
Yuki Usui, Jun Oishi, Katsunori Ano
We study a discrete optimal double stopping problem for the American
put type reward on geometric random walk, that is, on CRR market. It
is shown that there exists double stopping boundaries and the optimal
first and second stopping times are respectively the first hitting time to
the corresponding boundary.
TA-31
Tuesday, 8:30-10:00 - Room 013
Processes of Applying MCDA
Stream: Decision Processes
Invited session
Chair: Theodor Stewart
1 - Problem Structuring for MCDA: Incorporating External Expertise
Valerie Belton
Facilitated workshops, in which a group of key stakeholders are helped
to structure, build and use a multicriteria model, are a common and effective approach to MCDA. However, often it is not possible to bring
together all those with relevant expertise and ownership. This talk will
describe and reflect on the lessons learned from two case studies which
have used different ways of sourcing expert input to inform the building of multicriteria models to be used by others, one associated with
the UNEP MCA4Climate Project and the other the EPSRC Highly Distributed Energy Futures Project.
2 - Explanations for MCDA models
K. Nadia Papamichail, Theodor Stewart
This paper presents an explanation system that helps individuals and
groups to build and interpret MCDA models. A library of text plans
has been developed using natural language generation techniques. The
system establishes what makes an alternative most favourable, highlights the pros and cons of choices and identifies those factors that differentiate between two options. Such explanations increase confidence
and reduce overall cognitive effort.
3 - Decision Processes for MCDA in a Developing Countries Context
Theodor Stewart
In this paper we extract lessons learnt from using MCDA to facilitate
policy analysis in a development context. Areas of application have
included water resource management, fisheries rights allocation and
operation of foodbanks. The challenges include the wide diversity of
criteria that have to be elicited, including highly qualitative issues, and
the diversity of stakeholders from PhD scientists to effectively illiterate fishermen. Simple post it sessions, summarized as causal maps,
together with simple assessment methods have been found effective.
4 - A Multi-Criteria Multi-Period Decision-Making Approach for Sustainable Project Selection
Anissa Frini
This work is concerned with project selection in sustainable development context. This decision-making problem must guarantee a longterm balance between maintaining the integrity of the environment,
the social equality and the economic efficiency. In addition, the consequences of projects have to be evaluated under uncertainty in the short,
medium and long term horizons. This work will: i) provide a state-ofthe-art survey on sustainable project selection and ii) propose a multicriteria multi-period approach, which considers the requirements of
sustainable development under uncertainty.
TA-33
TA-32
Tuesday, 8:30-10:00 - Room 014
Disaster Management
Stream: Humanitarian Operations Research
Invited session
Chair: Silja Meyer-Nieberg
Chair: Erik Kropat
Chair: Dusan Starcevic
1 - The Adaptive Orienteering Problem with Stochastic
Travel Times
Irina Dolinskaya, Zhenyu (Edwin) Shi, Karen Smilowitz
In this work, we analyze an adaptive routing problem that arises in humanitarian relief settings. We focus on a specific variation of the Adaptive Orienteering Problem with Stochastic Travel Times (AOPST) that
integrates path finding between the reward nodes. At the beginning of
the time horizon, one commits to the set of reward nodes visited and
the sequence of visits. During the planning horizon, as information on
stochastic travel times is updated, the path between nodes to be visited can be adapted. We present the model, algorithms and analysis of
results.
2 - Applying Multicommodity Transshipment Network
Flow Optimization Technique under Uncertainty to
Measure the Robustness of the Transportation Network for Emergent Situation
Novia Budi Parwanto, Hozumi Morohoshi, Tatsuo Oyama
Given a seriously emergent situation occurring, e.g., just after largescale natural disasters, how to deal with victims, survivors, and damaged areas is a very critical and important problem. To obtain an optimal strategy for this problem we try to make necessary and desirable
response strategies for managing emergent cases by solving multicommodity transshipment network flow optimization problems under various types of uncertain situations. Assuming uncertainty related with
each road segment’s robustness, obtained from applying Monte Carlo
simulation technique and supply-demand situations.
3 - Modeling and Optimizing Disaster Relief Inventories
Degang Liu
As disasters happen at increasing frequency, disaster relief inventories
become a very important social system for government and NGOs.
Compared with commercial logistics systems, disaster relief inventories are less investigated. It also difficult to model because of its characteristics of social and political factors, great uncertainty in demand
and supply, and uncertain distribution and transportation infrastructures during severe disasters. In this talk, we will present problems
in modeling disaster relief inventory procurement, location, and distribution problems in china’s situation.
4 - Software Platform for Managing UAV Operations
Dusan Starcevic, Mlad̄an Jovanović
Due to technological advances, interest in UAVs as a practical, deployable technological component in many civil applications is rapidly
increasing and becoming a reality, as are their capabilities and availability UAV performs various kinds of missions such as mobile tactical
reconnaissance, surveillance, law enforcement, search and rescue, land
management, environmental monitoring, disaster management. UAV
is a complex and challenging system to develop. In this paper we
present software platform for visualizing, controlling and simulating
UAV’s data acquisition operations.
TA-33
Tuesday, 8:30-10:00 - Room 015
Defence and Security Applicatons
Stream: Defence and Security Applications
Invited session
Chair: Ana Isabel Barros
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TA-34
IFORS 2014 - Barcelona
1 - Network Enabled Capabilities (NEC): From LongTerm Visions to Short-Term Operational Effects
Havard Fridheim, Stein Malerud, Frode Rutledal
2 - Extracting from the Classical for Large-Scale SemiContinuous Variable Efficient Frontiers
Ralph E. Steuer
Given the many visions on how Network Enabled Capabilities can increase future military operational effect, it is often surprisingly hard
to identify relevant short-term NEC measures. Challenges include
an insufficient description of current NEC maturity status, cultural
differences, security concerns and limited funding of cross-service
measures. Based on Norwegian experiences, we will discuss how a
multi-methodological approach comprising problem structuring, scenario analysis and studies of military exercises can help measure current NEC maturity and identify relevant short-term measures.
Computing the efficient frontier of a large-scale (up to 3000 securities) mean-variance portfolio selection problem with semi-continuous
variables has been an out-of-reach task. Given the speed at which the
efficient frontier of a classical portfolio problem can now be computed
and the likelihood of overlaps between the frontier of a realistic semicontinuous variable problem with that of its corresponding classical
problem, the paper shows how large amounts of the efficient frontiers
of large-scale portfolio problems with semi-continuous variables can
be obtained in very little time.
2 - A New Approach to Deterrence: Planning to Achieve
Deterrence Effects
Nicholas Taylor
3 - Multi-Period Mean-Variance Portfolio Selection with
Risk Control over Bankruptcy and Uncertain Exit
Time
Wu Xianping
Thinking regarding deterrence remains stuck in the Cold War. This
presentation describes a new deterrence planning process that is being
researched by the UK. The presentation provides an overview of deterrence theory and some of the shortcomings of the approaches taken
by most nations. The steps of the new planning process are described,
with proposals for its application. The presentation will finish with
identification of challenges and issues posed by deterrence planning,
activities and assessment. We will describe the current state of the UK
research programme as well as the next stages.
3 - Assessment of a Conflict Intervention
Elin Marthinussen, Baard Eggereide
There is no easy solution to assess the situation in a conflict area.
Nonetheless, this is an important task both during an international intervention, but also after such an intervention in order to evaluate the
intervention and to identify lessons for future operations. Based on
Norwegian operational research lessons from Afghanistan, we will discuss the challenges and best practices regarding such analysis and how
the analysis of multiple data sets can be applied in support to the planning of future operations.
4 - Dealing with Complexity and Chaos: The Military Experience
Jan Frelin
Military doctrine stresses that defence forces have to handle complexity. In that situation, a mechanism for feed-back from the environment
is necessary. The current methods for feedback have fallen short of
requirements, creating a gap between military practice and doctrine.
This failure is explained using theory from cognitive research, organizational learning and complexity research. Ways forward are suggested.
In this paper, we consider optimal multi-period mean-variance portfolio selection with risk control over bankruptcy and uncertain exit time.
Instead of embedding scheme, we employ mean-field formulation to
deal with the nonseparable feature of this problem in dynamic optimization problems. We derive the analytical optimal strategies and
efficient frontier and the whole process is simple and direct compared
to the embedding technique.
4 - Efficient Simulations for a Bernoulli Mixture Model of
Portfolio Credit Risk
İsmail Başoğlu, Wolfgang Hörmann, Halis Sak
We consider the problem of calculating tail loss probability and conditional excess for the general Bernoulli mixture model of credit risk.
We propose an efficient simulation algorithm for this model in contrast to previous works that focus on specific credit risk models. The
algorithm we propose is a combination of stratification, importance
sampling based on cross-entropy, and the geometric shortcut method.
Numerical results suggest that the proposed general algorithm is more
efficient than the benchmark methods for the specific models.
TA-35
Tuesday, 8:30-10:00 - Room 131
Game Theory with Applications I
Stream: Stochastic Modeling and Simulation in Engineering, Management and Science
Invited session
Chair: Takahiro Watanabe
TA-34
Tuesday, 8:30-10:00 - Room 016
Portfolio Optimization 1
Stream: Decision Making Modeling and Risk Assessment in the Financial Sector
Invited session
Chair: Ralph E. Steuer
1 - Asset Allocation Powered by Information Flow Correlation
Jose Faias
We propose an alternative approach to optimizing portfolios that reduces sampling error. The complete opportunity set holds the risk-free
and two possible risky assets that are negatively correlated. The traditional approach is to maximize the expected utility of wealth based on
the entire opportunity set. Instead, we use a timing switch between the
two risky assets in the opportunity set which depends on the Information Flow Correlation computed from a stochastic variance model. At
each rebalancing time, our outcome is to allocate between a risky and
a risk free asset.
90
1 - Harmonic Analysis of the Slutsky Effect
Toru Maruyama
Certain moving average process of white noises exhibits a periodic
behavior. This well-known phenomenon was found out in 1930’s by
E.Slutsky in the course of his research into business cycles. The aim of
the present paper is to give a solid mathematical foundations for Slutsky’s insight from the viewpoint of modern Fourier analysis. Slutsky’s
process is a kind of weakly stationary stochastic process and the periodicity of its path can be characterized by the properties of the spectral
measure (the Fourier transform of which is equal to the covariance of
the process).
2 - Game Theoretic Approaches to Weight Assignments
in DEA Problems
Jing Fu, Shigeo Muto
This paper deals with the problem of fairly allocating a certain amount
of divisible goods or burdens among individuals or organizations in
the multi-criteria environment. It is analyzed within the framework
of DEA. We improve the game proposed by Nakabayashi and Tone
(2006) and develop an alternative scheme by re-assigning the total
weight or power for the coalition members. Under our new proposition, we analyze the solutions for both TU and NTU game, as well as
the equilibria of the strategic form game in the DEA problems.
IFORS 2014 - Barcelona
3 - Animal Spirits, Competitive Markets, and Endogenous Growth
Kenji Miyazaki
I use a simple model with an endogenous discount rate and linear technology to investigate whether a competitive equilibrium has a higher
balanced growth path (BGP) than the social planning solution and
whether the BGP is determinate or indeterminate. The implications are
as follows. To start with, people with an instinct to compare themselves
with others possess an endogenous discount rate. In turn, this instinct
affects the economic growth rate in a competitive market economy.
The competitive market economy also sometimes achieves higher economic growth than a social planning economy.
4 - Existence of Pure Strategy Equilibrium in Finite
Games and Direction Preservingness of Best Reply
Functions
Takahiro Watanabe
This paper investigates a new approach for the existence of pure strategy equilibrium in finite games. Our approach is based on discrete
fixed point theorem established by Iimura Murota and Tamura (2005)
and Yang (2009). We first show that a pure strategy equilibrium exists if the best reply direction functions of all players are simplicially
direction preserving for a common triangulation. We also show that
some sufficient conditions for the direction preservingness of the best
reply functions.
TA-36
Tuesday, 8:30-10:00 - Room 132
Forest Management to Reduce Fire Risk
Stream: OR in Agriculture, Forestry and Fisheries
Invited session
Chair: Andrés Weintraub
1 - Flexible Planning of the Investment Mix in a Wildland
Fire Management System: Spatially-Explicit IntraAnnual Optimization, Considering Preparedness and
Escape Costs
Abílio Pacheco, João Claro
We model intra-annual forest fire management as a multistage capacity investment problem, with a portfolio of resources for fuel treatment and suppression, and fires as demand. We consider two flexibility
types: commitment postponement (prevention, suppression) and spatial flexibility (ground crews, helicopters). The analysis confirms that
higher weather volatility leads to postponement and shows qualitative
changes in the prevention/suppression mix with the burnt area cost.
The changes match observed behavior and challenge several myths.
Fuel treatments are always needed above a certain cost.
2 - A Three-Step Approach to Forest Optimization Modelling for Assessing Trade-Offs in Spatial Fuel Management Strategies
Brigite Botequim, Alan Ager, Abílio Pacheco, Tiago Oliveira,
João Claro, Ana Barros, Jose Borges
The research contains spatial and temporal dimensions to integrate
landscape-scale properties required to meet fire management goals in
eucalyptus farms distributed over Portugal, without encroaching budget constraints. Specifically: Developing a Forest System Dynamic
Model in order to identify temporal stand-scale and fuel dynamics;
Characterizing for each fuel arrangements the spread rate curve trends,
thereby allowing the calculation of changes in the annual expected
wood loss; Simulating in the Landscape Treatment Designer tool the
optimal levels of fuel landscape treatment configurations.
3 - A Heuristic for Satisfying Adjacency Constraints
when Scheduling Timber Harvests on Flammable
Forest Landscapes
Andrés Weintraub, David Martell, Juan José Troncoso
TA-37
We develop a heuristic solution to the problem of scheduling harvests
on forest landscapes subject to adjacency constraints. Our heuristic
is based on a threat index incorporated in a mixed integer programming spatial harvest scheduling model whose solutions accelerate the
harvesting of high risk stands while satisfying adjacency constraints.
We illustrate and evaluate our heuristic in a simulated planning environment for a hypothetical forest to determine how well the simulated
forest would be managed were our heuristic used to determine when
and where harvesting activities should occur.
TA-37
Tuesday, 8:30-10:00 - Room 017
Multiobjective Optimization in Asia (II)
Stream: Multiobjective Optimization
Invited session
Chair: Tetsuzo Tanino
Chair: Tamaki Tanaka
1 - LP Well-Posedness for Bilevel Vector Equilibrium
and Optimization Problems with Equilibrium Constraints
Somyot Plubtieng, Phan Quoc Khanh
The purpose of this paper is introduce several types of Levitin-Polyak
well-posedness for bilevel vector equilibrium and optimization problems with equilibrium constraints. Criteria and characterizations for
these types of Levitin-Polyak well-posedness we argue on diameters
and Kuratowski’s, Hausdorff’s, or Istràtescu’s measures of noncompactness of approximate solution sets under suitable conditions, we
prove that the Levitin-Polyak well-posedness for bilevel vector equilibrium and optimization problems with equilibrium constraints.
2 - Well-Posedness for the Bilevel New Generalized
Mixed Equilibrium Problems in Banach Spaces
Rabian Wangkeeree
In this talk, the well-posedness and generalized well-posedness for the
problem (BNGMEP) are introduced by an epsilon-bilevel mixed equilibrium problem. Also, we explore the sufficient and necessary conditions for (generalized) well-posedness of the problem (BNGMEP) and
show that, under some suitable conditions, the well-posedness and generalized well-posedness of (BNGMEP) are equivalent to the uniqueness and existence of its solutions, respectively. These results are new
and improve some recent results in this field.
3 - Existence and Convergence of Common Fixed Points
via an Iterative Projection Technique for Two Strict
Pseudo-Contractions in Hilbert Spaces
Kasamsuk Ungchittrakool
In this paper, the existence and convergence theorems of common fixed
points for two strict pseudo-contractions are obtained by using an iterative shrinking projection technique with some suitable conditions. The
method permits us to obtain a strong convergence iteration for finding some common fixed points of two strict pseudo-contractions in the
framework of real Hilbert spaces. Further, some related applications
are discussed to inverse strongly monotone operators in real Hilbert
spaces.
4 - Hybrid extragradient method for finding a common
solution of the split feasibility and system of equilibrium problems
Wiyada Kumam, Jitsupa Deepho, Poom Kumam
The purpose of this paper is to introduce a new hybrid extragradient
iterative algorithm for finding a common element of the set of fixed
points of quasi-nonexpansive mappings and satisfying solutions of the
split feasibility problem (SFP) and systems of equilibrium problem
(SEP) in Hilbert spaces. We prove that the sequence generated by
the proposed algorithm converge strongly to a common element of the
fixed points set of quasi-nonexpansive mappings and the solution of
split feasibility problems and systems of equilibrium problems under
mild condition.
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Tuesday, 8:30-10:00 - Room 214
Optimality Conditions and Algorithms:
From Convex to Nonconvex Optimization
Stream: Convex Optimization Methods and Applications
Invited session
Chair: Russell Luke
Chair: Shoham Sabach
1 - A Simple Algorithm for Nonconvex and Nonsmooth
Minimization Problems
Shoham Sabach, Jérôme Bolte, Marc Teboulle
We introduce a new algorithm for a broad class of nonconvex and nonsmooth problems. It relies on an elementary mixture of first order
methods and data information. We outline a self contained convergence analysis framework describing the main tools and methodology
to prove that the sequence generated by the proposed scheme globally
converge to a critical point. The resulting scheme involves elementary
iterations and is particularly adequate for solving many problems arising in fundamental applicaions. This is a joint work with Jerome Bolte
and Marc Teboulle.
2 - Sparse Optimization over Symmetric Sets
Nadav Hallak, Amir Beck
We consider the problem of minimizing a general continuously differentiable function over symmetric sets under a sparsity constraint.
We investigate both stationarity-based optimality conditions as well as
conditions of a coordinate-wise type, and show, by exploiting various
symmetry properties, how to verify and attain points which satisfy the
derived optimality conditions. For that purpose, we also develop algorithms or expressions for the orthogonal projection operator onto
sparse symmetric sets.The algorithms and optimality conditions are illustrated by examples. Joint work with Amir Beck.
3 - An O(1/k) First Order Algorithm for a Class of Nonsmooth Convex-Concave Saddle-Point Problems
Marc Teboulle, Yoel Drori, Shoham Sabach
We introduce a novel algorithm for solving a class of structured nonsmooth convex-concave saddle-point problems involving a smooth
function and the sum of finitely many bilinear terms and nonsmooth
functions. The proposed method involves elementary computations
and is proven to globally converges to a saddle-point with a rate of
O(1/k). We illustrate its relevance for tackling a broad class of composite minimization problems, and its performance through numerical
examples in some imaging and machine learning problems.
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Tuesday, 8:30-10:00 - Room 018
ORAHS VI - Treatment Optimization
Stream: Health Care Applications
Invited session
Chair: Sally Brailsford
Chair: Joana Matos Dias
2 - Tactical Planning at a Breast Cancer Outpatient
Clinic
Maartje van de Vrugt, Richard Boucherie
Patients suspected of breast cancer must rapidly get access to diagnostic tests. In some cases additional unscheduled same-day tests are
required. All patients should be diagnosed within a week after the first
visit to the outpatient clinic. Therefore, we analyze appointment planning on two time scales: the access process and the day process. Invoking two discrete-time queueing concepts, we obtain a new blueprint
schedule that satisfies the access norms and minimizes same-day waiting times. The methods are applied to a Dutch hospital.
3 - A Simulated Annealing Approach Using a DDS-based
Neighborhood for IMRT Beam Angle Optimization
Joana Matos Dias, Humberto Rocha, Brígida da Costa
Ferreira, Maria do Carmo Lopes
Intensity Modulated Radiation Therapy planning requires several decisions to be taken beginning by which radiation angles to use: Beam
Angle Optimization problem. The angles can be determined by a
lengthy and planner dependent trial-and-error approach (forward planning). Another possibility is to consider inverse planning where optimization models and algorithms are used to automatically determine
the angles. We consider Simulated Annealing using a Dynamically
Dimensioned Search based neighborhood structure to tackle this large,
non-linear, multi-modal and computationally demanding problem.
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Tuesday, 8:30-10:00 - Room 019
Production Planning
Stream: Production and the Link with Supply Chain
Invited session
Chair: Yuan Huang
Chair: Julie Rubaszewski
1 - Managing an Assemble-To-Order System with After
Sales Market for Components
Mohsen Elhafsi, Essia Hamouda
We study an ATO system subject to demand not only for the assembled
product but also for individual components. Demand inter-arrival and
component production times are exponentially distributed. We formulate the problem using a Markov Decision process framework and characterize the optimal production and inventory allocation policy that
minimizes the expected total holding and backorder costs. We propose
three simple heuristic policies and show that two of these heuristics
are not only very effective in mimicking the optimal policy but also
are simpler to implement in practice compared.
2 - Applying Lean Management in Complex Manufacturing Lines: The Case of Flash Chip Production
Elad Harison, Ofer Barkai
The paper evaluates the possibilities of implementing the principles of
Lean manufacturing and illustrates their potential contribution to the
operations of firms by defining metrics for the different dimensions of
their activities. The case brought up here illustrates the use of the major
principles of Lean in a relatively small scale enterprise — a manufacturer of flash memory chips. The benefits and improvements achieved
by the implementation of Lean are presented in a set of key Lean metrics. Finally, conclusions are made about the applicability of the Lean
methods.
1 - Development and Evaluation of a Continuous-Time
Semi-Markov Model for the Disease Progression of
Acute Heart Failure
Qi Cao, Douwe Postmus, Hans Hillege, Erik Buskens
3 - A Comparison of Two Priority Rules in KanbanControlled Job Shop
Ali Ardalan, Rafael Diaz
The care provided to heart failure (HF) patients is organized around
multidisciplinary management programs (MPs) in which health care
professionals collaborate to improve outcomes. However, it is currently still uncertain how intensive these programs should be to produce the associated clinical benefits in an affordable manner. To
address this issue, we used data from a clinical trial to develop a
continuous-time semi-Markov model for the disease progression of
HF patients. We subsequently used this model to evaluate the costeffectiveness of the 3 MPs considered in the clinical study.
We have shown that 2 modifications in JIT by including MRP Customer demand significantly improve performance of Job shops in customer wait time and WIP. The modifications were made to adapt JIT
to Job shops. This study uses simulation to compare the effect of the
2 modifications at levels of number of kanbans, length of withdrawal
cycle, FCFS and SPT on customer wait time and inventory. Results
show that there is a statistically significant difference in both customer
wait-time and inventory in the 2 modification approaches, with the first
being superior to the second.
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4 - A Decision Support System to Facilitate the Implementation of Workload Control in Make-to-Order
Companies
Yuan Huang
Workload Control (WLC) is a production planning and control method
uniquely designed for make-to-order companies. However, implementation of WLC has encountered significant difficulties due to the gap
between theory and practice. This paper describes a state-of-the-art
WLC decision support system which is considered an effective enabler of WLC application. To address the practical challenges (e.g.,
lack of quotation support, unexpected incoming of workloads) noted
in the literature, the system has been developed through a user interactive action learning and reflection approach.
TA-41
Tuesday, 8:30-10:00 - Room 216
Green Logistics in Rich Vehicle Routing
Problems
Stream: Simulation-Optimization in Logistics & Production
Invited session
Chair: Javier Faulin
1 - Evaluating the Willingness to Pay using an Econometric Model for Road Transportation in the Spanish
Pyrenees
Adrian Serrano, Javier Faulin, Fernando Lera-Lopez,
Mercedes Sanchez
All logistic activities generate environment costs because of externalities such as noise and air pollution. One well-known method to study
those costs is the use of surveys about the willingness to pay (WTP) of
the interviewee to compensate the damage caused. Here, we propose
an econometric model in which we analyze the WTP in road transportation crossing the Pyrenees in the Basque Country and Catalonia.
In this study, we consider some factors such as road distance, personal
income, style of life, and other socioeconomic features of people living
in the affected area by externalities.
2 - A Biased-Randomized Algorithm for the Vehicle
Routing Problem with Backhauls
Javier Belloso, Angel A. Juan, Javier Faulin, Elena
Perez-Bernabeu
We consider the Vehicle Routing Problem with Backhauls (VRPB)
where the group or cluster of delivery customers has to be served before the first pickup customer can be visited. We propose an algorithm based on an adaptation of the algorithm SR-GWCS-CS introduced by Juan et al. (2011). Promising solutions have been obtained
from the application of our method to classical benchmark instances
for the VRPB. We also consider the environmental implications associated with the resolution of this problem.
3 - Teaching Logistics and Routing Online: Experiences
and Challenges using Virtual Campuses
Francisco Faulin, Javier Faulin, Angel A. Juan
We describe here some benefits and challenges related to teaching Logistics and Routing (L&T) in online environments related to virtual
campuses. Information technologies (IT) offer new ways to teach and
learn Operations Research models, because they facilitate the shifting to an emergent educational paradigm which considers students as
active and central actors in their learning process. In this sense, we describe some real experiences, developed during the last years at three
different universities in Spain.
4 - Optimal Routing of Ambulances on Service with
Queues and Demand Uncertainties. A Case Study of
Zomba Central Hospital.
Javier Faulin, Elias Mwakilama, Levis Eneya
TA-42
We aim at improving the pick-up and delivery of patients while minimizing both unmet stochastic demand and waiting times. An optimal
schedule algorithm for routing a few available ambulances to meet the
desired stochastic demand is designed. Such goals are met through
efforts of combining the vehicle routing problem and queuing theory
disciplines.
TA-42
Tuesday, 8:30-10:00 - Room 215
Big Data Analytics for Quality
Improvement
Stream: Big Data Analytics
Invited session
Chair: Mustafa Baydoğan
1 - A New Procedure for Fault Variable Identification in
Multistage Processes
Myong K Jeong, Jinho Kim, Khalifa Nasser Khalifa, Wook
Yeon Hwang, Abdelmagid S. Hamouda, Elsayed Elsayed
In modern manufacturing systems with a large number of process variables, it is challenging to identify the variables that cause an out-ofcontrol signal. In this talk, we present a new procedure for fault variable identification. We compare the diagnostic performance of the proposed procedure with existing methods using simulations. The computational experimental results show that the proposed procedure is an
efficient diagnostic tool for the real time fault variable identification in
high-dimensional processes such as multistage manufacturing systems.
2 - Ensemble Learning Strategies for Large-Scale Time
Series Analysis and Data Mining
Mustafa Baydoğan, George Runger, Didem Yamak
We introduce a novel time series (TS) representation based on a treebased ensemble learning strategy. Earlier, many high-level representations have been proposed for TS data mining but these representations
require many parameters and have problems with generalizability. Our
proposed approach is scalable, imposes no constraints on the data and
has only one parameter. We illustrate the benefits of our approach on
45 TS classification problems. The proposed approach has promising
extensions to forecasting, clustering, anomaly detection etc.
3 - A Model-based Prognosis of the Gas Pipeline with
Corrosion Defects
Seong-Jun Kim, Byunghak Choe, Hyo-Tae Jeong, Woo-Sik
Kim
Corrosion is one of the major causes of failure in the gas pipeline.
This paper deals with assessing the pipeline reliability in the presence
of corrosion defects. In order to consider uncertainty involved with
pipeline parameters, statistical approaches such as First Order Second Moment (FOSM) and First Order Reliability Method (FORM) are
incorporated with fuzzy clustering technique. The simulation result
based upon a field dataset indicates that our method provides more advisory estimation of the pipeline reliability. Additional issues on its
maintenance planning will be discussed as well.
4 - Learning a Bayesian Network Having One Latent
Variable
Chi-Hyuck Jun, Jun-Seong Kim
This paper proposes a new probabilistic graphical model which contains one unobservable latent variable that affects all other observable
variables. Linear Gaussian models are used to express the causal relationship among variables. The proposed iterative method uses a combined causal discovery algorithm of score-based and constraint-based
methods to find the network structure, while Gibbs sampling and regression analysis are conducted to estimate the parameters. The proposed model is applied to ranking evaluation of institutions using a set
of performance indicators.
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IFORS 2014 - Barcelona
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Tuesday, 8:30-10:00 - Room 217
Accounting and Financial Crisis
Stream: Operational Research in Financial and Management Accounting
Invited session
Chair: Jonathan Crook
1 - Classification Algorithms for Imbalanced Business
Financial Data
Georgios Marinakos, Sophia Daskalaki
Classification algorithms such as Linear Discriminant, k-Nearest
Neighbor, Decision Trees and Neural Networks are evaluated as for
their performance on an imbalanced financial dataset from the Greek
private sector. Our focus is on the ability of the algorithms to predict
the minority class of businesses that declared financial distress in a
sample where the vast majority is solvent businesses. The imbalance
affects the classifiers’ prediction performance and rebalancing techniques as random undersampling and synthetic minority oversampling
are used to improve it.
2 - The Stability of Survival Model Parameter Estimates
for Predicting the Probability of Default: Empirical
Evidence over the Credit Crisis
Jonathan Crook, Mindy Leow
We investigate the stability of parameter estimates of discrete survival
models by developing two survival models for accounts that were accepted before and since the credit crisis. We find that the two sets
of parameter estimates are statistically different, with different predictions of probabilities of default when applied onto a common test set.
We investigate whether changes in predicted probability distributions
are due to the quality of the cohort accepted under different economic
conditions, or due to the drastically different economic conditions, or
a combination of both.
3 - Intensity Modelling with Macroeconomic Effects and
Simulated Transitions
Mindy Leow, Jonathan Crook
Using application, behavioural and macroeconomic variables, we estimate intensity models to predict probabilities of delinquency and default for individual accounts over the duration time of loans. We find
different trends for different groups of accounts and over time. Using
Fleishman’s power method transformation, random distributions based
on properties of observed transition rates are generated and compared
against predicted probabilities to get predicted transitions for accounts
over time. From the results of this simulation, we calculate distributions for the transitions and losses.
TA-44
Tuesday, 8:30-10:00 - Room 218
OR in Regular Study Programs
Stream: Initiatives for OR Education
Invited session
Chair: Elise del Rosario
Chair: Ariela Sofer
Chair: Liudmyla Pavlenko
1 - Integrating OR and Systems Engineering in Masters
Capstone Projects
Ariela Sofer, Karla Hoffman
We discuss how we combine MS in OR students and Masters in Systems Engineering (SE) students in joint capstone teams. The students’
collaboration fosters a productive synergy that provides OR students
with a broader systems perspective and provides SE students with a
better understanding of the benefit and potential of OR models and
methods. Examples of applied capstone projects from various industrial and government sponsors will be discussed
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2 - Object-oriented Coordinate Design of Course and
Teaching Mode in OR
Gang Du
In this paper, the concept of three-dimension design space and objectoriented coordinate design method of course and teaching mode are
proposed. The idea is the design based on three dimensions including
knowledge dimension, object dimension and mode dimension. The
design procedure consists of dimension division, courses design and
teaching mode design is described. As an implement assistance, a
teaching design handbook is suggested. A real example, the OR course
and teaching design, including a handbook design, in Tianjin University in China is given in this paper.
3 - Operational Research Education in Taiwan
Yu-Lin Wang
This study investigates differences between business schools and engineering schools in operational research in Taiwan. To assess the divergent educational approaches, this study investigates the (1) number
of operational research-related courses per school, (2) design and arrangement of operational research-related course curricula, (3) content
of operational research-related courses, and (4) teaching methods in
operational research-related courses, across differing institutional settings in these two schools.
4 - Academic planning for OR education
Erwin Reizes
A report of 52 years of engineering and teaching and learning with experience applied to OR academic planning is presented. In this paper,
the methodology and taxonomy presented at EURO conference 2012
Vilnius (TD41/TD11.3) will be used. We end with a conclusion and an
outlook.
TA-45
Tuesday, 8:30-10:00 - Room 219
International Aspects of OR History and
Education
Stream: International Aspects of OR: Cooperation —
Coordination — Communication
Invited session
Chair: Ulrike Reisach
1 - Acquisition of Relative Clauses in Brazilian Portuguese Studied by Categorical Data Analyses
Gastão Gomes, Sergio Camiz, Christina Gomes, Ana Abreu
In this work we study the interdependence among five categorical variables related to the accuracy of the repetition of stimulus. For this purpose we use techniques like Correspondence Analysis and Loglinear
Analysis.
2 - Relationship between Architectural Education and
Graph Theory
Mehmet Inceoglu
The basic design course, Architectural education in the first year,
teaching and the effectiveness of the implementation of the meets the
expectations of the design does not satisfy the targeted, it is a matter of
debate. At this stage, the designer interprets the information acquired
in the problem solution-oriented thoughts in advance to improve the
effort. In this study, we examined the concept of Basic design education in architecture texture. The basic design has been in the Studio
with the texture work "graph theory" is scrutinized.
3 - Consideration of Intercultural Challenges and Different Thinking Patterns in Teaching German Understanding of Academic Research to Foreign Students
Mitja Stefan Weilemann, Kristina Weilemann
Foreign students need to apply the host/target country’s understanding
of academic research and integrity. This holds true for international
students in Germany as well as for Non-Germans studying German
language mediation in their home country. Lecturers deal with intercultural challenges and different thinking patterns. The authors compare two approaches from different perspectives: 1) research assistants
teaching academic methods to international students at the University
of Applied Sciences Neu-Ulm/Germany and 2) German language assistants at the Università degli Studi di Sassari/Italy.
IFORS 2014 - Barcelona
4 - Applying Grey Relation Analysis to Explore the
College Students Studying Motivation, Learning
Stress and Academic Achievement under Declining
Birthrate Phenomenon
Hua-Kai Chiou, Mei-Chun Mao
With unemployment soaring in Taiwan society, shrinking wages and
other factors, the formation pressure and an economic and psychological burden on a family and raise children. Here we apply grey relational analysis to explore the studying motivation of students, learning
stress and academic achievement, and through our surveys as a mutual
view schools and departments as in curriculum planning and teaching, and thus motivate students the pursuit of learning motivation and
achievement, improve the content and quality of education, strengthen
students’ employability and competitiveness.
TB-02
Tuesday, 10:30-12:00
TB-01
Tuesday, 10:30-12:00 - Room 118
Railway Timetabling
Stream: Railway and Metro Transportation
Invited session
Chair: Karl Nachtigall
1 - New Heuristic Solution Techniques for the Periodic
Event Scheduling Problem (PESP)
Jacint Szabo, Sabrina Herrigel-Wiedersheim, Marco
Laumanns, Ulrich Weidmann
The increasing capacity usage in railway networks and the demand
for more frequent and reliable offers to passengers make railway
timetabling progressively challenging. In this research we concentrate
on the Periodic Event Scheduling Problem (PESP), a method to construct periodic timetables. We introduce new heuristic solution methods based on iterations over several mixed integer linear programs to
accelerate the computation of timetables close to optimality. Computational studies on real world timetabling instances show promising
results.
2 - Combining Cyclic Timetable Optimization and Traffic
Assignment
Michael Kümmling, Jens Opitz, Peter Großmann
Usually, timetable optimization follows a simple route-wise traffic assignment, neglecting the feedback of the optimized timetable on the
traffic assignment. We use constraint programming to incorporate the
timetable’s constraints into a new multi path traffic assignment. A set
of rules especially fitted to railway journeys reduces the search space
further. Using the determined multiple paths, a cyclic timetable optimization is conducted, based on the periodic event scheduling problem.
3 - Solving the Train Path Assignment Optimzation
Problem by Column Generation
Karl Nachtigall
Given a fixed set of train paths along side its’ schedule, train path assignment in railway timetabling is an NP-complete problem. In this
work, we introduce several objective functions to highlight important and corner cases in train path assignment. A method for optimal assignment of train paths by a branch-cut-and-price algorithm will
be shown, which implies a research foundation for further investigations. Computational results and evaluation of real-world scenarios
show promising results for the presented approaches.
4 - Approaches to Solving Single Track Timetabling
Jonas Harbering, Marie Schmidt, Abhiram Ranade
Timetabling has been intensively studied in many different versions.
In this work, we present a very simple timetabling problem which has
not been investigated so far. Consider a single track with uncapacitated
stations at irregular but known positions on the track and fixed numbers
of trains traversing the track from both sides. The task is to minimize
the time from the start of the first train until the arrival of the last train
under the additional condition that trains are only allowed to pass each
other at stations. In this talk, we present different approaches to solve
this problem.
TB-02
Tuesday, 10:30-12:00 - Room 111
Inventory-Routing Problems
Stream: Vehicle Routing
Invited session
Chair: Okan Ozener
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IFORS 2014 - Barcelona
1 - Inventory-Routing Scheme for an ATM Network Replenishment Problem
Pablo A. Rey, Alejandro Cataldo, Cristián Cortés, Juan Perez,
Homero Larrain
We present an inventory-routing scheme for a real ATM network replenishment problem. This application includes time windows constraints together with strong penalizations for stock-outs of specific
machines. We propose a mixed-integer linear programming formulation solved through a decomposition approach for decoupling the routing from the lot-sizing problem. The model is tested with real data
of 500 machines distributed over Santiago-Chile, all of them operated
by a single company; results are promising compared with the performance observed from current operation.
2 - An Inventory-Routing Problem with Pickups and Deliveries Arising in the Replenishment of Automated
Teller Machines
Roel G. van Anholt, Leandro Coelho, Gilbert Laporte, Iris
F.A. Vis
This paper introduces, models and solves a multi-period inventoryrouting problem with simultaneous pickups and deliveries. Commodities can be brought from and to the depot, as well as being exchanged
among customers to manage their inventories. This problem arises,
e.g., in the replenishment operations of recirculation ATMs. We formulate the problem as a MILP model and propose an exact branch-andcut algorithm for its resolution. We assess the performance through
extensive computational experiments using real data. Good lower and
upper bounds for this new practical problem are obtained.
3 - Cyclic Distribution Strategies for an Inventory Routing Problem
Okan Ozener, Ali Ekici, Gultekin Kuyzu
We study a variant of inventory routing problem where a set of customers with deterministic and continuous demand is replenished from
a central depot by routing a fleet of capacitated delivery vehicles. Assuming a cyclic distribution policy where the proposed delivery schedule is repeated with a given frequency, we propose a solution approach
and test it on a set of randomly generated instances in terms of solution
quality and solution time.
4 - City-Courier Quick Service Network Topological Design
Tsung-Sheng Chang, Yu-Hsuan Hsu
This research tackles the problem of topological optimization of citycouriers’ service networks to effectively reduce the couriers’ service
time. This research first mathematically models the problem, which
involves multiple objectives and time periods. Then, this research applies hierarchical optimization and rolling horizon techniques to deal
with the multi-objective and multi-period issues, respectively. Finally,
this research further decomposes the problem into topological network
design problem and m-TSP with balance and familiarity constraints
that are solved by proposed heuristics.
TB-03
Tuesday, 10:30-12:00 - Room 001
Airline and Airport Operations
Stream: Aviation
Invited session
Chair: Mourad Boudia
Chair: Valentin Weber
1 - Reducing Airport Gate Holdouts in Passenger Aviation
Brian Lemay, Jeremy Castaing, Amy Cohn
Commercial flights are routinely assigned a gate at their destination
airport prior to departing their origin airport. However, events such
as an early incoming flight and/or a late outgoing flight can cause an
arrival to wait for its assigned gate to become available. This "gate
holdout’ can result in missed passenger connections, delayed crews,
and increased fuel costs. We formulate an optimization model for the
gate assignment problem that incorporates the system variability in order to minimize the expected impact of gate holdouts. We test our
model with data from a major U.S. Carrier.
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2 - Aircraft Line Maintenance Planning Optimisation
Syed Shaukat, Cheng-Lung Wu
This paper aims to develop algorithms for scheduling tasks in multiple maintenance windows available at multiple locations to optimise
aircraft line maintenance cost. A heuristic of a hybrid combination
of classic job scheduling methods was developed with a lexicographic
formulation of hierarchical constraint propagation and a soft objective function. The algorithm produced near optimal solutions with significant gains in execution speed and task yield compared to manual
scheduling. The knowledge will contribute to operations research and
scheduling automation in airline maintenance operation.
3 - Adaptive Process of Schedule Recovery for Airline
Operations
Valentin Weber, Gregoire Spiers, Mourad Boudia, Rodrigo
Acuna Agost
Airline schedule recovery consists in minimizing the impact of disruptions for the schedule and in returning as quickly as possible to the
planned operations. The available tools for repairing depend on the
closeness to the operations. Few days before, we only consider equipment changes or cancellations; the day before, we can also delay legs,
change the aircraft type or create ferry flights. Our solution is based
on a sequence of algorithms that is adaptable to the context. We illustrate its behavior on real life data sets including maintenances and
passengers from a major European airline.
TB-04
Tuesday, 10:30-12:00 - Room 119
Warehousing
Stream: Supply Chain Management
Invited session
Chair: René de Koster
1 - A Flexible Routing Strategy for Improving the Performance of a Sequential Zone-Picking Line
Ying-Chin Ho, Jian-Wei Lin
Because of the fixed-sequence restriction in a sequential zone-picking
line, totes or cartons of orders may waste time on waiting in zones’
input queues and time on zones they do not need to visit. To overcome
this disadvantage, a flexible routing strategy is proposed. We propose
not only a new design to convert a sequential zone-picking line into a
system that allows flexible routing of totes or cartons, but also rules to
dispatch totes or cartons to their next destinations. Simulation experiments are conducted to understand the performance of the proposed
strategy and dispatching rules.
2 - Lean Six Sigma: An Application in a Warehouse Operation
Haluk Hekimoğlu, Sabri Erdem
In today’s evolving world, companies from all around the world choose
cost reduction solutions for maximizing their profitability. Lean
six sigma is an innovative management discipline focusing on loss
elimination and continuous improvement for the companies trying to
achieve high profitability and low cost rates.This paper presents an application from logistics sector, how losses detected and reduced by using lean six sigma tools in a warehouse operation. As a result of the
study achievements and improvements are clearly expressed.
3 - Evaluation of Satellite Information Tasks Processing
Capacity
Gang Liu, Peide Xu
The capacity of satellite information processing node need to be assessed, to solve the capacity allocation problem. We first analyze the
basic process of satellite information processing, and build a network
model of it. Then we present a queuing network model for the entire
processing network, and the nodes is regarded as servers. After that we
build a priority queuing system with reneging, to deal with the priority
and time deadlines of tasks. We use block matrix solution method to
solve the model. At last, a case study is provided.
IFORS 2014 - Barcelona
4 - The Impact or Order Picker Skills on Warehouse Performance
René de Koster, Marek Matusiak
We study batching orders and routing order pickers in a picker-to-parts
warehouse and additionally take differences in picking skills of the
workers into account. We first apply multilevel modeling to forecast
batch execution times for individual pickers. Next, these forecasts are
used to minimize total batch execution time, by assigning the right
picker to the right order batch. We solve the problem with an ALNS
algorithm and show that state-of-the-art batching and routing methods
can be improved by almost 10% by additionally taking skill differences
among pickers into account.
TB-05
Tuesday, 10:30-12:00 - Room 002
Sustainability in Maritime Transportation
Stream: Maritime Transportation
Invited session
Chair: Harilaos N. Psaraftis
1 - Impact study of the new sulphur regulations on a
North Sea short sea route
Oriol Algaba Birba
The aim of the current study is to analyze the impact of the IMO and
EU sulphur regulations for a specific short sea route in the North Sea.
These regulations may have significant impact on the profitability of
such routes because of higher costs and may also induce reverse modal
shifts and more CO2 overall. The study first analyzes the impact of
the new regulations on costs and prices for the specific route. Then
an analysis regarding the different available measures to comply with
the requirements is carried out and relevant recommendations are provided.
2 - The Economic Speed of an Oceangoing Vessel in a
Dynamic Setting
Evangelos F. Mageirou, Theodore Bouritas, Harilaos N.
Psaraftis
Environmental and economic considerations have led to dramatic decreases in speed of all types of oceangoing vessels esp. since 2008. In
the authors’ previous work, a tramp vessel’s optimal speed was analyzed in a dynamic setting given probabilities for future freight rates.
The approach involved a unified setting for voyage and speed selection
and was solved by dynamic programming. We extend this approach by
introducing a Markov chain model for the fuel prices / environmental
cost and b. a continuous state model for the charter market. Computational experiments are presented.
3 - Combining Speed and Routing Decisions in Maritime
Transportation
Christos Kontovas, Harilaos N. Psaraftis, Min Wen
We present recent results on the problem of combining ship speed and
routing decisions. Speed is a key determinant of the economic and
the environmental performance affecting variables such as trip duration, fuel costs, and air emissions, among others. It is seen that inputs
such as fuel cost, ship charter costs and cargo inventory costs may
impact both speed and routing decisions. We develop models that optimize speed for a spectrum of routing scenarios and we use a heuristic
method to solve them. Some examples are presented so as to illustrate
the various trade-offs that are involved.
4 - Maritime Fleet Deployment with Speed Optimization:
Case Study from RoRo Shipping
Kjetil Fagerholt, Henrik Andersson, Kirsti Hobbesland
We propose a new modeling approach for integrating speed optimization in the planning of shipping routes, as well as a rolling horizon
heuristic for solving the combined problem. As a case study we consider a real deployment and routing problem in RoRo-shipping. Computational results show that the rolling horizon heuristic yields good
solutions to the integrated problem within reasonable time. It is also
shown that significantly better solutions are obtained when speed optimization is integrated with the planning of shipping routes.
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TB-06
Tuesday, 10:30-12:00 - Room 211
Translation of Health Systems
Engineering Research into Clinical
Practice
Stream: Logistics in Health Care
Invited session
Chair: Tarun Mohan Lal
1 - Implementing a Residency Scheduling Program at
the University of Michigan Pediatric Emergency Department
Amy Cohn, Young-Chae Hong, Jennifer Zank, Elizabeth
Perelstein, Zachary VerSchure, William Pozehl
Residency schedules are often created manually by the Chief Residents, despite tremendous complexity, lack of decision-support tools,
and the need for quality schedules. A key challenge is the fact that
there is no one clearly defined objective function. In close collaboration between the Industrial and Operations Engineering Department
and the Pediatric Emergency Department, we have developed a MIPbased tool to facilitate scheduling. The results are both a significant
reduction in the time required to generate the schedules and a significant improvement in the quality of the schedules.
2 - Spine Surgery Surgical Schedule Optimization
Jeanne Huddleston, Tarun Mohan Lal
Spine surgeries are complex, difficult to schedule due to the length
and variability of the surgery thereby making surgical scheduling challenging. This presentation will cover the methodology used to optimize the surgical schedule, implementation challenges and results till
date achieved at Mayo Clinic by implementation of a decision support
tool that predicts the surgical duration and uses an optimization model
that improving patient access and financial performance for the spine
surgery practice.
3 - Priority Scheduling of Jobs with Unknown Types
Serhan Ziya
In some healthcare applications where priority decisions need to be
made, the information that is crucial to determine the importance or
urgency level of a job may not be available immediately, but can be
revealed through some preliminary investigation. While investigation
provides useful information, it also delays the provision of services.
Therefore, it is not clear if and when such an investigation should be
carried out. In this talk, we develop and analyze a simple mathematical
model to provide insight into how this decision should be made.
4 - Stochastic Optimization to Reduce Wait Times in an
Outpatient Infusion Center
Jeremy Castaing, Amy Cohn, Brian Denton
The University of Michigan Infusion Center is faced with common
complaints of excess patient wait times. In an effort to improve the
quality of cancer care delivery and infusion center operations, we formulate a large scale integer programming optimization model that creates a patient appointment schedule aiming to reduce waiting times
and total hours of operation. An algorithm returning a good approximation to the optimal solution is proposed. We then develop a simulation model to evaluate performance of schedules provided by the
optimization model and others heuristics.
TB-07
Tuesday, 10:30-12:00 - Room 003
Convex and Complementarity Models for
Electricity Market Analysis
Stream: Equilibrium Problems in Energy
Invited session
Chair: Mohammad Reza Hesamzadeh
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IFORS 2014 - Barcelona
1 - Optimal Network Operations using a SOCP-OPF
model
Mohamadreza Baradar, Mohammad Reza Hesamzadeh
This research derives the second-order cone programming (SOCP)
formulations for improving network operations. The transmission
network constraints with VSC-type DC grid systems are convexified
through linear approximations and convex relaxations. The accuracy of
linear approximations and exactness of the convex relaxations are studied. Transmission loss minimisation, transfer capability enhancement,
and system loadability maximisation are modeled as SOCP problems.
2 - An EPEC Approach for Modelling Exercise of Market
Power on Ramp Rate
Ekaterina Moiseeva, Mohammad Reza Hesamzadeh
With increasing penetration of wind power, there is a need for securityconstrained short-run dispatch as a welfare-maximizing way of procuring fast-ramping generation. However, it is observed, that on the occasion of contingency some generators bid low ramp rates, which enforces the dispatch of fast-ramping generators, so the prices spike up.
Such ramp-rate withholding is a new type of strategic behavior. Using game-theoretic framework, we model the problem as an EPEC and
recast it as a single-stage MILP. We demonstrate the computational
performance and discuss the scaling of such problems.
3 - Multi-regional Transmission Planning as a Noncooperative Decision-making
Yaser Tohidi, Mohammad Reza Hesamzadeh
There are few literatures on multi-regional transmission planning problem and its cooperative and non-cooperative solutions. This paper contributes to the literature by bridging this gap. The paper derives the
mathematical model for non-cooperative transmission planning based
on the game theory concepts in applied mathematics. The solution
concept of the worst-Nash equilibrium is introduced to solve the setup game. Different mathematical techniques are employed to formulate the worst-Nash equilibrium solution as a mixed-integer linear programming problem.
4 - The Optimal Coordinated Bidding of Risk Averse Hydropower Producer in Sequential Markets
Yelena Vardanyan, Mohammad Reza Hesamzadeh
The electricity prices in different market places are unknown when the
bidding takes place. Thus, to develop a statistical planning model for
price-taker hydropower producer in sequential markets is a challenging, meanwhile an important task. This paper develops stochastic Second Order Cone Program (SOCP) to generate optimal bidding strategy
for three sequential markets for a profit maximizer hydropower producer. The model considers not only expected profit but also profit
variance modeling objective function as a linear combination of expected value and a variance of the profit.
TB-08
Tuesday, 10:30-12:00 - Room 120
Power Management and Decision
Analysis in Sustainable Development
Stream: Energy Economics, Environmental Management and Multicriteria Decision Making
Invited session
Chair: Carlos Enrique Escobar-Toledo
2 - A Pareto Analysis for Evaluating Energy Trade-Off in
Part Supplying
Victoria Rodriguez, Juan Bermeo, Masood Fathi, María Jesús
Alvarez
Energy savings at present is one of the main concerns of the industries and companies in the world because most of them for their bad
practices in their production processes are contributing directly to the
greenhouse gases emission.In the present study a realistic mathematical model for the JIT part-supplying problem at mixed model assembly
line is presented. The model considers two typical objectives which are
the reduction of the inventory level and the reduction of the transport
cost with consequent reduction of emissions. The aim is to find a representative set of Pareto optimal solution.
3 - Deciding Between Carbon Trading and CCS: An
Optimisation-based Case Study for Methanol Synthesis from Syngas
Semra Agrali, Gorkem Uctug, Yildiz Arikan, Eray Avcioglu
We consider the problem of installing a carbon capture and sequestration (CCS) unit for a production plant in order to ensure that the
amount of CO2 emissions is within its allowable limits. We formulate
this problem as a non-linear optimisation problem where the objective is to maximise the net returns from pursuing an optimal mix of
the two options: to invest in CCS or buy carbon credits for the excess
emissions above their limits. The results were found to be sensitive to
carbon credit prices and the discount rate. The model was applied to a
methanol synthesis plant.
TB-09
Tuesday, 10:30-12:00 - Room 121
Control Theory & System Dynamics
Stream: Dynamical Systems and Mathematical Modelling in OR
Contributed session
Chair: Mona Soufivand
1 - Optimal Control of One Economical Problem Using a
Principle of Maximum
Phridon Dvalishvili, Aleksandre Mosidze, Liana Karalashvili
It is clear that overproduction and the necessity to store commodities
lead to obvious losses for the company. Losses will be even bigger in
the case of shortage, taking into consideration the unmet demand and
a smaller profit. It is obvious that the fact that shortage impairs the
company’s reputation should also be taken into account. One model
of optimal control for a problem of commodity production and supply is given. Using a principle of maximum it is constructed production volume change dynamics (optimal control) and commodity supply
functions, so that the overall loss is minimal.
2 - System Dynamics Model for Firm level R&D Investment Decision Making
Jiyoon Son, Hongsuk Yang, Soo Wook Kim
This study develop an system dynamics model for Firm level R&D investment decision making while considering the impact of market dynamics and new product diffusion on market maturity perspective system dynamics methodology is adopted to describe the dynamic system
of market condition.
1 - Monitoring Electricity Power Grids using Chernoff
Faces
Valter Senna, Carlos Carneiro
3 - Stabilizable Switched Systems by Partial State Reset
Isabel Brás, Ana Carapito, Paula Rocha
Chernoff faces are used to obtain a multivariate representation of quality indexes in power grids. Using the R language, we capture five
important electrical parameters and continuously show properly configured faces that depict their values on the grid substations. Looking at
the faces, one can follow the magnitudes of the parameters and the differences between substations. In developing countries, such as Brazil,
where the power grid needs constant attention and skilled manpower is
scarce, it provides clear identification of spots or regions that require
attention by the system operator.
A switched linear system is considered to be a family of continuous
linear time invariant systems governed by a switching law. For each
time instant, the switching law defines which of the linear systems is
active. Usually, the state trajectory is considered to be continuous. In
this talk, we analyze switched systems where state jumps are allowed
in some components of the state, during the switching instants. More
concretely, we identify some classes of switched systems where it is
possible to perform suitable jumps in those state components in order
to obtain a stable dynamics.
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IFORS 2014 - Barcelona
4 - Towards Fostering the Improvement of Public-Private
Partnership in Social Services using System Dynamics Approach
Mona Soufivand, Enzo Bivona, Roberto Strazzeri, Marco
Alessi
Considering the significant role of interaction between private and public charity centers in current social welfare systems, this paper aims to
support such a partnership in order to foster the quality of service delivery system. To do so, a specific case study in Lecce, South Italy, is analyzed using System Dynamics approach. The analysis intends to improve the public-private partnership and fostering co-creating the value
among the key partners of a ”food donation” service supply chain.
TB-10
Tuesday, 10:30-12:00 - Room 122
Decision Support Models for the Energy
Industry II
Stream: Optimization Models and Algorithms in Energy
Industry
Invited session
Chair: Andres Ramos
1 - An Iterative Method for Coupling Computationally
Heavy Profit-Maximizing Electricity and Gas Market
Models
Pablo Dueñas
Energy companies support their decision-making process with detailed
market models. Decisions include budget elaboration, assets management or contracts exercise. Depending on the level of detail, a simulation may take from minutes to hours to be solved. Due to last years
electricity and gas markets integration, companies have found new
business opportunities in joint operations. A single integrated market model may become intractable or require excessive simplification.
An iterative method for coupling two large market models is proposed.
Robust profit-maximizing decisions are achieved.
2 - Robust Transmission Expansion Planning (TEP) Applying Shrinkage
Sara Lumbreras, Victor DeMiguel, Andres Ramos
Stochastic optimization finds the best solution in terms of expected cost
for a given scenario tree, but the definition of this tree is often incomplete or subjective. In these cases, it is desirable to make the solution
robust with respect to small changes in the definition of scenarios. We
propose to shrink the stochastic solution towards a robust benchmark,
this is, modify it to make it is more similar to another TEP solution
which is calculated independently from the scenario tree. A case study
illustrates the method
3 - Including Short-Term Operation Details in Strategic
Generation Expansion Models
Adelaida Nogales, Sonja Wogrin, Efraim Centeno Hernáez
Renewable generation technologies are expected to reach large penetration levels in a number of electric power systems. These technologies are changing the plant scheduling of the rest of the generating facilities and as a result, operation-related issues become more
important for an adequate analysis of generation expansion problems.
A generation expansion equilibrium model which introduces start-ups
and shut-downs under an oligopolistic market representation has been
developed. A new approach to solve the equilibrium problem via an
equivalent optimization problem has been used.
4 - Strategic Forward Trading and Technology
Heikki Peura, Derek Bunn
Forward trading in electricity markets is often driven by hedging motives, but with market power may also result from strategic considerations. In increasingly technologically diverse markets, the flexibility
and reliability of production technologies may influence not only spot
prices but also the nature of forward trading. We develop a theoretical model to study the impact of these factors and their interactions
on spot and forward market equilibria, with important implications on
both firm strategy and market design.
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TB-11
Tuesday, 10:30-12:00 - Room 113
Network Routing
Stream: Combinatorial Optimization
Invited session
Chair: Michael Juenger
1 - The Cut Property under Demand Uncertainty
Sara Mattia
Given a graph and a set of uncertain traffic demands, we investigate
when capacities satisfying the robust version of the cut inequalities
are sufficient to guarantee a feasible routing for the demands independently of the realization of the uncertainty (robust cut property). We
provide conditions for a problem to have the robust cut property and
show how to use such conditions to generalize to the problem with
uncertain demands the results that are known for the problem without uncertainty, when possible. Both static and dynamic routing are
considered.
2 - Single-Commodity Robust Network Design Problem:
Complexity, Instances and Heuristic Solutions
Valentina Cacchiani, Eduardo Álvarez-Miranda, Andrea Lodi,
Tiziano Parriani, Daniel Schmidt
We study a single-commodity Robust Network Design problem in
which an undirected graph with edge costs is given together with a
discrete set of balance matrices, representing different supply/demand
scenarios. The goal is to determine the minimum cost installation of
capacities on the edges such that the flow exchange is feasible for every
scenario. We present complexity results and define computationally
hard instances, which are solved by means of a new heuristic algorithm. The comparison with solutions obtained by Cplex on a natural
flow formulation shows the effectiveness of our method.
3 - Designing Robust Client-Server Networks under
Simple Polyhedral Demand Uncertainties
Daniel Schmidt, Valentina Cacchiani, Michael Juenger,
Frauke Liers, Andrea Lodi
We design optimal robust client-server networks: A single commodity
(e.g., data) is to be transfered among the nodes of a network. Each
node has a minimum/maximum supply or demand of that commodity.
Our aim is to find minimum cost integer capacities such that all possible realizations of supplies and demands can be routed. Applications
for the model lie in networks with identical servers.
We build on previous work by Buchheim, Liers and Sanità (INOC
2011) and a previous joint work by the authors (ISCO 2012) with Álvarez, Dorneth and Parriani to develop a branch-and-cut-algorithm.
4 - Approximate Earliest Arrival Flows
Melanie Schmidt, Martin Groß, Jan-Philipp Kappmeier,
Daniel Schmidt
We consider the Earliest Arrival Flow Problem: Given a set of factories and a set of clients with prescribed supplies and demands, we ask
for a network flow over time that satisfies as much demand as possible
in each point in time. Because of the enforced pointwise optimality,
earliest arrival flows do not necessarily exist in arbitrary networks. In
this talk, we report how to bypass this problem by defining and finding
suitably relaxed definitions of earliest arrival flows.
TB-12
Tuesday, 10:30-12:00 - Room 004
Nonstandard Numerical Methods for
Differential Equations
Stream: Continuous and Discontinuous Dynamical
Systems
Invited session
Chair: Mevlüde Yakıt Ongun
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IFORS 2014 - Barcelona
1 - A Crack Problem for a Nonhomogeneous Strip
İlkem Turhan, Elçin Yusufoğlu
In this study, a linear elasticity problem is considered. It is assumed
that the strip consists of two materials. While material 1 is homogenous, material 2 is nonhomogeneous coating in y-direction. To solve
the considered linear elasticity problem, a system of singular integral
equation is derived under the boundary and continuity conditions. The
system of singular integral equations is solved and numerical computations are presented to interpret the effect of stress intensity factors
(SIFs).
2 - Efficiency of Differential Transform and Variational Iteration Methods for the Solutions of Some Differential Equations
Onur Karaoğlu
There are many methods to find the approximate or exact solutions of
differential equations. In this study, differential transform method and
variational iteration method that are from these solution methods in literature have been discussed. Differential transform method is based on
Taylor series expansion, while variational iteration method is a method
producing successive approximations by using iteration of the correction functional. Numerical solutions of some differential equations
through methods mentioned in study were searched and affects for the
solution of methods were assessed.
3 - Numerical Solution of Time-Fractional ZakharovKuznetsov Equation via Generalized Differential
Transform Method
Ozan Özkan, Ummugulsum Cansu, Serkan Sönmezer
In this paper, a new application of generalized differential transform
method (GDTM) has been used for solving time-fractional ZakharovKuznetsov equation.The presented method is a numerical method
based on the generalized Taylor series formula which constructs an
analytical solution in the form of a polynomial. The fractional derivatives are described in the Caputo sense.The results obtained are in good
agreement with the ones in the open literature and it is shown that the
technique introduced here is robust, effcient and easy to implement.
4 - Nonlinear Fuzzy IVPs Using by Nonstandard Finite
Difference Schemes
Mevlüde Yakıt Ongun, Damla Arslan
In this talk, a nonstandard numerical method is presented for Fuzzy
initial value problems. The scheme based on the nonstandard finite
difference scheme is discussed. Some examples and figures are given
including nonlinear Fuzzy firs order differential equations.
TB-13
Tuesday, 10:30-12:00 - Room 123
Advances in Scheduling
Stream: Scheduling
Invited session
Chair: Alexandre Dolgui
1 - A New Algorithm for Multi-Agent Scheduling to Minimize Makespan on Two Machines
Xiwen Lu
In this paper, we study a multi-agent scheduling problem on two identical machines. Each agent aims at minimizing the makespan. We
present a (1+1/6, 2+1/6,..., g+1/6)-approximation algorithm which produces a schedule such that the makespan of the ith completed agent is
no more than (i+1/6) times its minimum makespan, i=1,2,...,g. This
ratio vector is tight.
2 - Non-Identical Parallel Machine Scheduling with
Sequence-Dependent Setup Times
Shiegheun Koh
100
This research deals with a problem that minimizes makespan in a nonidentical parallel machine system with sequence and machine dependent setup times and machine dependent processing times. We first
present a new mixed integer programming formulation for the problem, and using this formulation, one can easily find optimal solutions
for small problems. However, since the problem is NP hard and the
size of a real problem is large, we propose four heuristic algorithms
including genetic algorithm based heuristics to solve the practical bigsize problems in a reasonable computational time.
3 - Multi-Attribute Scheduling on Unrelated Machines
Pierpaolo Caricato, Antonio Grieco, Sandro Zacchino
We address a loading and scheduling problem on multiple machines,
in which setup time depends on the values of one or more jobs features. This is very common in manufacturing environments, where
setup times descend from the need to tune production machines in order to respond to variations in jobs physical characteristics such as size
or weight. We propose a heuristic approach that exploits this specific
nature of setup, extending and improving a former approach limited to
the single machine case. Experimental tests based on actual industrial
data prove the validity of the proposed approach.
4 - Lot-Sizing and Lot Sequencing on a Single Imperfect
Machine with Breakdowns and Product Rejects
Alexandre Dolgui, Ksenyia Schemeleva, Xavier Delorme,
Frédéric Grimaud
A multi-product sequencing and lot-sizing problem for a line that produces items in lots is studied. There are two types of uncertainties:
random lead time induced by machine breakdowns and random yield
because part rejects. Sequence dependent setup times are also present.
The goal is to maximize the probability of producing a required quantity of items of each type by the end of a planning horizon. Decomposition can be used to separate sequencing and lot-sizing. A genetic
algorithm (GA) is proposed. Computational results comparing GA
performance with and without decomposition are reported.
TB-14
Tuesday, 10:30-12:00 - Room 124
DEA in Services
Stream: DEA Applications
Contributed session
Chair: Sérgio Santos
Chair: Yu Chao
1 - Network DEA Model to Evaluate Post-Graduate Engineering Courses in Brazil
Silvio Gomes Júnior, Placido Moreno, João Carlos Soares de
Mello
Brazilian post-graduate courses are evaluated every three years. This
evaluation is unclear. It tries to measure the academic productivity,
among other factors. Therefore, the aim of this work is to evaluate
the ability of post-graduate Engineering III programs of CAPES areas
to produce scientific papers from masters’ degrees and doctoral theses in a proper way. We have implemented a two-stage Network DEA
(NDEA) model using the number of theses as an intermediate variable. The model allows us to compute the efficiencies from both the
academic and research aspects of the post-graduate courses.
2 - Market Orientation, Innovation Capability, Marketing
Proficiency, and New Product Market Success
Yu Chao, Chun-Mei Lai
The role of marketing orientation as an antecedent of new product performance has been extensively documented in the literature. Marketing
Orientation has attracted ever-increasing interest because of the publication of seminal works and is a strategically valuable resource for successful new product development (NPD). This article focuses on NPD
projects in the Taiwanese bio-tech industry and examines the mediate
relationship between market orientation and new product market success through innovation capability and marketing proficiency.
IFORS 2014 - Barcelona
3 - Determining Mobile Communication Operators’ Efficiency by using DEA
Ahmet Aktas, İzzettin Temiz
Mobile communication technologies have shown great improvements
in the last 20 years. Operators are making new investments to compete
against their rivals and to increase the number of their customers. As a
result of these investments, a positive change of efficiency is expected.
In this study, an application of Data Envelopment Analysis (DEA) has
been done in order to determine efficiency of mobile communication
operators in Turkey. Efficiency of each operator is calculated for 6 periods of three-months between January 2012 and July 2013. Efficiency
change of operators has also been analysed.
4 - Efficiency and Seasonality in the Portuguese Post
Offices and Postal Distribution Centers
Sérgio Santos, Carla Amado, Ana Fadísta
This study uses Data Envelopment Analysis (DEA) to assess the efficiency of Portuguese post offices and Postal Distribution Centers
(PDCs) and to explore the extent to which seasonality impacts on their
performance. To this effect, we use data from 85 post offices and 44
PDCs. The results indicate that whilst there is a remarkable variation
in the performance of the units assessed, seasonality seems to play an
important role in explaining this variation, indicating that, in order to
remain efficient, some units may need to adjust their capacity according to the season.
TB-16
4 - Behavioral Anomalies in Consumer Wait-or-Buy Decisions and Their Implications for Markdown Management
Nikolay Osadchiy, Anton Ovchinnikov, Manel Baucells
Deciding whether to buy an item at a regular price or wait for a markdown a consumer trades-off the delay in getting an item, the likelihood
of getting it and the magnitude of savings — all of which are prone to
behavioral anomalies/regularities. We propose a model that incorporates such anomalies and analytically solve the consumer wait-or-buy
problem. Through a behavioral study estimate the model parameters
and numerically show that accounting for the behavioral anomalies a
firm would offer larger markdowns yet generate higher revenue compared to the current literature’s predictions.
TB-16
Tuesday, 10:30-12:00 - Room 127
Structure Learning and Applications
Stream: Intelligent Optimization in Machine Learning
and Data Analysis
Invited session
Chair: Ivan Reyer
TB-15
Tuesday, 10:30-12:00 - Room 125
Pricing and Consumer Behavior:
Modeling and Estimation
Stream: Revenue Management II
Invited session
Chair: Ozalp Ozer
1 - Mixing Hopfield Neural Network and Probabilistic
Model Method
Diana Vasilieva, Yuri Mikhailov
We introduce our modification of Hopfield neural network (HNN) architecture. While using original Hopfield network we found some
cases where resulting values can be ambigious. To solve that problem we added probabilistic model (PM) and developed mixing method
of these two approaches. As a result we got better results than original
Hopfield network.
1 - Markdown or Everyday-Low-Prices? The Role of
Consumer Regret and Availability Misperception
Ozalp Ozer, Karen Zheng
2 - Bayesian Sample Size Estimation for Patient Classification Survey
Anastasia Motrenko
We study a seller’s optimal pricing and inventory strategies when consumers’ purchase decisions are affected by anticipated regret and misperception of product availability. We show that these behavioral factors reinstate the profitability of markdown over everyday-low-price, in
sharp contrast to prior studies. We quantify that ignoring these behavioral factors can lead to excessive profit losses. We determine that pricing offers the seller additional means to leverage consumers’ behavioral issues, while mitigating potential consequences of mis-calibrating
behavioral issue.
We seek to increase the quality of classification of Cardio-Vascular
Disease patients. As a part of research, arises the problem of determining the minimum sample size necessary for statistical significance
of classification. Previously, we proposed a method of sample size determination that involved comparing empirical distributions, evaluated
on different subsets of a sample. To measure similarity, the KullbackLeibler distance was used. We now investigate further the features of
this distance and provide some theoretical background for the method.
2 - Optimal Reference Pricing for Healthcare Procedure
Payments
Victoire Denoyel, Laurent Alfandari, Aurelie Thiele
3 - A Machine-Learning Paradigm that Includes Pointwise Constraints
Giorgio Gnecco, Marco Gori, Stefano Melacci, Marcello
Sanguineti
In reference pricing (RP), a payer determines a maximum amount for
a procedure; patients who select a provider charging more pay the difference. This has strong potential in costs reduction for payers, quality
increase for patients and visibility for high-value providers. Inspired
by a CalPERS program, we use robust optimization to set reference
price and providers subject to it. We develop a MIP payer decision
model to fill the gap of quantitative insights on RP due to price, quality
and geographic coverage. Preliminary results give promising leads on
pitfalls and benefits of this policy.
3 - Customer Behavior Modeling in Revenue Management Systems using a Global Optimization Approach
Shadi Sharif Azadeh, Gilles Savard
In revenue management systems it is necessary to precisely predict demand of each product at a given time. This could be a challenging
task, as registered bookings are censored to booking limits. In order
to have a precise forecasting model, uncensoring methods are applied
to unconstrain the registered data. We propose an optimization model
to estimate the demand of each product at a given time as well as the
product utilities for customers arriving from different segments. We
introduce an algorithm that takes availability constraints into account.
The classical framework of learning from examples is enhanced by the
introduction of hard point-wise constraints, i.e., constraints, on a finite
set of examples, that cannot be violated. They arise, e.g., when imposing coherent decisions of classifiers acting on different views of the
same pattern. Constrained variational calculus is exploited to derive a
representer theorem that provides a description of the functional structure of the solution. The general theory is applied to learning from hard
linear point-wise constraints combined with classical supervised pairs
and loss functions.
4 - Structure Learning and Forecasting Model Generation
Vadim Strijov, Mikhail Kuznetsov, Anastasia Motrenko
The aim of the study is to suggest a method to forecast a structure of a
regression model superposition, which approximates a data set in terms
of some quality function. The problem: algorithms of model selection
are computationally complex due to the large number of models. The
solution: we developed a model structure forecasting algorithm based
on previously selected models.
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TB-17
Tuesday, 10:30-12:00 - Room 005
Nonconvex Programming: Local and
Global Approaches II
Stream: Global Optimization
Invited session
Chair: Hoai An Le Thi
Chair: Tao Pham Dinh
1 - DC Programming and DCA for Dictionary Learning
Xuan Thanh Vo, Hoai An Le Thi, Bich Thuy Nguyen Thi, Tao
Pham Dinh
Sparse representations of signals based on learned dictionaries have
drawn considerable interest in recent years. However, the design of
dictionaries adapting well to a set of training signals is still a challenging problem. For this task, we propose a novel algorithm based on DC
(Difference of convex functions) programming and DCA (DC Algorithm). The efficiency of proposed algorithm will be demonstrated in
image denoising application.
2 - Internet Routing by DC Programming and DCA
Thi Thuy Tran, Hoai An Le Thi, Tao Pham Dinh
We consider an Internet Routing problem (Open Shortest Path First),
where select paths are based on link weights. The problem is formulated as minimizing the sum of some increasing and convex link
cost functions with some nonconvex constraints. We present two approaches based on DC programming and DCA for solving this problem which is in fact a DC program with DC constraints. They consist
in reformulating those programs as standard DC programs in order to
use standard DCAs for their solutions. Computational exepriments are
conducted on some real-world problems.
3 - DC Programming and DCA for Minimizing L1/L2 —
Norms of Polyhedral Convex Function Vector over a
Polyhedral Convex Set
Tao Pham Dinh, Hoai An Le Thi, Hoai Minh Le
Minimizing a sum of absolute (resp. square) values of polyhedral convex functions over a polyhedral convex set, being important by their
applications, are (NP hard) nonsmooth nonconvex programs. We investigate DC programming and DCA to reformulate them as appropriate DC programs (the polyhedral DC1 and DC2) and to devise customized DCAs for their solutions. It turns out that DCA consists in
solving at each iteration a linear (resp. convex quadratic) program.
Moreover the resulting DCA1 applied to DC1 has finite convergence.
4 - Tracking of Potentially Threatening Target Evolution
in a Network
Frédéric Dambreville
The issue is to track the target being given limited and scarce information, where classical filtering approaches provide irrelevant tracking of
the target. The grounding idea is to use a threat cost criterion, to be optimized, as a complement of the prior, and deal the threat tracking as a
goal-oriented filtering. This leads to a dynamic zero-sum game where
the strategy of the intruder is characterized by a constrained flow along
the network, and where the cost is multiplicative along the trajectory.
We show that the whole problem is solved as a Linear Program.
1 - Robust Multi-Criteria Location Problems
Christian Günther
We consider continous multi-criteria location problems with uncertainties in the data. The uncertainties are given in the objective function of
the location problem. In our models we use currently developed concepts of robustness for multi-objective optimization problems. Particularly, we focus on the concept of minmax robust efficiency introduced
by Ehrgott, Ide and Schöbel (2013). Furthermore, we use algorithms
based on decomposition approaches like presented by Alzorba, Günther and Popovici (Optimization 2013) to solve a special class of robust
multi-criteria location problems.
2 - The Robustness Space Framework for Pareto Set Reduction
Jorge Leon, Daniel Jornada
This presentation deals with identifying a reduced subset of robust
solutions from a given Pareto Front. The framework maps the kdimensional Pareto set onto a 2-dimensional space called the robustness space (RS). Given a set of uncertainties related to the values of
the decision variables, the dimensions in RS represent the robustness
of a solution with respect to its objective values and infeasibility. We
present structural properties and a solution approach for the case of
multi-objective linear programs. Examples illustrate how the RS may
be useful in multi-criteria decision making.
3 - Assessing the Robustness of Pareto Sets in MultiObjective Integer Programming Problems
George Mavrotas, José Rui Figueira, Eleftherios Siskos, Haris
Doukas
We provide measures of robustness for Pareto sets in Multi-Objective
Integer Programming (MOIP) problems. The robustness of each one
Pareto Optimal Solution (POS), as well as the robustness of the Pareto
set as a whole is assessed, providing appropriate indices. The method
is based on a combination of Monte Carlo simulation with MultiObjective Programming (using method AUGMECON2) and is illustrated using a multi-objective knapsack problem. The method provides
an illustrative way of presenting the robustness of Pareto front in two
and three dimensions.
4 - Pareto-based Definitions of the Optimal Value and
Optimal Solutions of a Fuzzy Program
Benoît Pauwels, Serge Gratton, Frédéric Delbos
The values of a function to be optimized may be subject to imprecision
of non-stochastic nature. Such uncertainty can be modeled with fuzzy
sets theory. However fuzzy optimization literature lacks coherent definitions for the optimal value and optimal solutions. We propose such
definitions based on the Pareto-efficient sets of bi-objective programs
associated with the cuts of the fuzzy objective function. The case when
the fuzziness of the objective function results from the presence of
fuzzy parameters - which includes the linear and quadratic cases - is
investigated further.
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Tuesday, 10:30-12:00 - Room 128
Inventory Planning I
Stream: Demand and Supply Planning in Consumer
Goods and Retailing
Contributed session
Chair: Piotr Staliński
TB-18
Tuesday, 10:30-12:00 - Room 112
Robustness in Multiobjective
Optimization II
Stream: Multiobjective Optimization - Theory, Methods
and Applications
Invited session
Chair: Alexander Engau
Chair: Christiane Tammer
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1 - A Hybrid Optimization Approach for Inventory Space
Allocation with Assembly Line Balancing
Tugbanur Sezen, Rifat Gürcan Özdemir
This study aims to develop a hybrid approach in which a mathematical
model is fed back by a simulation model to solve component inventory
area allocation and assembly line balancing problems. The mathematical model assumes that all parameters regarding to the assembly line
are deterministic and solves space allocation and line balancing problems simultaneously. However, the parameters related to the inventory
replenishment are random. Thus, some constraints are updated by a
simulation model based on the results of fill rate. The developed approach is implemented in automotive industry.
IFORS 2014 - Barcelona
2 - Some New Findings About the Newsboy Problem
Jing-An Li
The newsboy problem has been studied for a long time and is being
studied till now. Most researchers are good at using the classical Newsboy model to solve all kinds of related problems. Considering the expected objective function generated by the stochastic demand, we have
some new findings about the newsboy problem. And these findings are
also illustrated at http://www.scmgame.org for your reference.
3 - Determining Strategic Inventory Ratio in Leagile Supply Chain Considering Desirable Decoupling Point
Mahsa Ghandehari, Arash Shahin, Azam Khalili
Performance of a leagile supply chain strongly depends on the location of the decoupling point. The aim of this paper is to determine
optimum ratio of strategic inventory and desirable decoupling point in
leagile supply chain. Speed and variety factors have been considered as
agility criteria evaluated by stockout and lost sales costs and order and
inventory holding costs have been considered as leanness variables.
Finally, considering each chain as a decoupling point, the desirable
decoupling point is selected so that the total cost is minimized.
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4 - Robust Portfolio Planning of Offshore Wind Farms
Alexana Cranmer, Erin Baker
Applying a spatial version of robust portfolio analysis to wind siting
will help us better understand the value of each project in the context
of the full portfolio of projects. Wind farm sites are generally considered one at a time and current approaches do not account for any
interactions between the qualities of the sites. Sites may interact with
each other through wake effects, profit potential, and wildlife impacts.
TB-21
Tuesday, 10:30-12:00 - Room 006
Optimization Modeling Applications in
Manufacturing 2
Stream: Optimization Modeling in OR/MS
Invited session
Chair: Lena Altherr
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Tuesday, 10:30-12:00 - Room 129
Managing Smart Energy Grids under
Uncertainty - I
Stream: Stochastic Optimization in Energy
Invited session
Chair: Samira Safaei Farahani
Chair: Zofia Lukszo
1 - Optimal Bidding Strategy of a Plug-in Electric Vehicle
Aggregator in Day-ahead Electricity Mmarkets under
Uncertainty
Marina González Vayá, Göran Andersson
We approach the problem of a plug-in hybrid vehicle (PEV) aggregator bidding into the day-ahead electricity market with the objective to
minimize charging costs while satisfying PEV’s flexible demand. The
problem is formulated a bi-level problem, where the upper level problem is the aggregator’s cost minimization, and the lower level problem
is the market clearing. Since driving behavior is uncertain, chance
constraints are introduced and solved using a scenario-based approach
providing probabilistic guarantees.
2 - Distributed Model Predictive Control for an Uncertain
Smart Thermal Grid
Samira Safaei Farahani, Zofia Lukszo, Bart De Schutter,
Tamas Keviczky
Smart Thermal Grids (STG) are one type of smart energy systems that,
if controlled efficiently, can contribute to maintain the supply-demand
balance in the energy distribution and to reduce the energy costs for
producers and consumers. This paper focuses on modeling and control
of STGs in which the uncertainties in the demand and production are
included. The control approach we propose is stochastic distributed
model predictive control and its implementation relies on the real-time
solution of an optimization problem. Our aim is to increase the computational efficiency of this control approach
3 - Multi-Stage Reserve Policies for Large-Scale Power
Systems
Joseph Warrington, Paul Goulart, Manfred Morari
Multi-stage reserve policies are planned, time-coupled responses to errors in the prediction of uncertain renewable infeeds or loads in power
systems. Affine functions represent an attractive, tractable parameterization of such policies, which in our earlier work were shown to have
the potential to reduce expected operating costs under inaccurate predictions. This talk describes our latest work in extending the approach
to practical large-scale power systems using distributed optimization
principles.
1 - Buffer Allocation and Preventive Maintenance Optimization in Unreliable Production Lines
Nabil Nahas
In this paper, we consider a serial production line consisting of n unreliable machines with n-1 buffers. The problem under study consists
of developing an integrated model for the joint determination of buffer
sizes and preventive maintenance intervals. The objective is to determine the optimal preventive maintenance policy and the optimal buffer
allocation that will minimize the total system cost subject to a given
system throughput level. The extended great deluge algorithm (EGD)
is proposed to solve the problem. Numerical examples showed that
PM has a major impact on the throughput.
2 - Optimization of Pick-and-Place in Die Attach Process
You-Jin Park, Rong Pan, Douglas Montgomery, Connie
Borror
In semiconductor manufacturing process, the wafers are moved to an
assembly facility and sawed into individual chips after front-end process. Only good chips are picked up by a robot arm and attached to a
lead frame on strips. This sub-process is known as the die attach process. To improve the production efficiency, it is necessary to evaluate
the performance of the robot arm operation in the die attach process.
In this research, a pick-and-place problem of the die attach process
is mathematically formulated and efficient methods that can minimize
the total transfer distance are obtained.
3 - Maximising over Time the Profit of a Renewable Tool
Aureli Alabert, Mercè Farré
Assume we have a tool or machine from which we obtain a profit, but
whose performance degrades in time, it is random to some extent, and
has downtimes, maintenance costs, a finite lifetime, and that at some
time to be decided by the owner, it must be replaced by a new one.
A situation of this kind arises in the dairy industry, where the "tools"
to manufacture the milk are the cows in a farm, that must be replaced
when the expected (discounted) revenue of a given animal is less that
the expected revenue of a new younger one, taking into account the
fixed costs of the replacement.
4 - Efficient Dynamic Flow Models with Technical Restrictions
Lena Altherr, Thorsten Ederer, Ulf Lorenz, Peter Pelz, Philipp
Pöttgen
We apply Operations Research methods to design energy- and costoptimal fluid systems. For a given time-varying flow and pressure demand, finding an optimal combination of available components such as
pumps, valves, pipes or accumulators and optimal settings for the employed components presents itself as a multi-stage optimization problem. This problem can be solved efficiently by using a hybrid approach
which integrates a quasi-static formulation into a time-expanded network. In this work, we present the model formulation and comparative
benchmarks for the example of a given fluid system.
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Tuesday, 10:30-12:00 - Room 007
Cooperation in Manufacturing and
Service Systems
Stream: Game Theory and Operations Management
Invited session
Chair: Ulas Ozen
Chair: Greys Sosic
1 - Asymptotic Invariance Results for Assembly Systems
Mahesh Nagarajan, Greys Sosic, Chunyang Tong
We show a set of useful properties for large assembly systems that allow us to extend known results for assembly systems with monopoly
suppliers to those with commodity ones.
2 - Competitive Allocation Rules for Cooperating Logistics Providers
Behzad Hezarkhani, Marco Slikker, Tom Van Woensel
This talk addresses allocation rules for gain sharing in consortia of logistic providers where joint planning of truckload deliveries reduces
the cost of empty kilometers. The competitive nature of freight transport markets requires allocation rules that distinguish among the players based on characteristics of the situation which are not represented
by the associated cooperative game. We introduce desirable properties
in these situations and argue that none of the existing allocation rules
in the literature satisfy these properties. We propose an allocation rule
that accomplishes the latter.
3 - Manufacturers’ Competition and Sustainable Cooperation: Cost Structure and Stability Analysis
Greys Sosic, Fang Tian, Laurens Debo
We study a market with two substitutable and one independent product,
in which recycling can be either manufacturers’ responsibility or undertaken by the government. Each product can be made by a different
firm, or one firm makes two independent products. We analyze conditions under which different products are recycled together. We also
extend our analysis by considering the case with two pairs of substitutable (but mutually independent) products in which each firm makes
two independent products.
4 - Strategic Lateral Transshipment with Communication Constraints
Michal Tzur, Eran Hanany, Shulamit Lederman
We focus on transshipment problems with communication constraints,
and aim to find the resulting transshipment configuration. A LP is
formulated in order to calculate the system optimum and the problem
is analyzed as a Potential Game. Finally, an algorithm is presented,
which establishes optimal decisions for each retailer based on imperfect information about retailers’ inventory realization. The results indicate that, in most of the cases, the transshipment of units between
retailers through a cyclic configuration is optimal. In addition, in the
optimal configuration, no split is applied.
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Tuesday, 10:30-12:00 - Room 008
Behavioural Economics and Games
Stream: Behavioural Operational Research
Invited session
Chair: Gregory Kersten
1 - Inequity aversion in screening contracts: experimental evidence and model analysis
Guido Voigt
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Screening contracts (or "menu of contracts") align the incentives in
supply chains with private information. In screening contracts it is
assumed that all parties are strictly expected) profit maximizing. We
present an experimental study that highlights that the profit maximization assumption is critical. We argue that inequity aversion explains
the observed behavior and show how contract design can account for
this behavioral phenomenon.
2 - Strategic Customer Behavior in Newsvendor System: Analysis and Experimental Study
Yanan Song, Xiaobo Zhao
We deal with a newsvendor system facing strategic customers. The
newsvendor determines the quantity and price, and then each customer
chooses buying or waiting for a discount. Although the rational expectations (RE) equilibrium with customer behavior "all-buy" is popularly
used in the literature, we show that under the retailer’s optimal price
and quantity of the RE equilibrium, the customers’ game also has "allwait" Nash equilibrium. A laboratory experiment was conducted, from
which the customer behavior exhibited a tendency of "all-wait" in the
setting of the RE equilibrium.
3 - Application of the Long-Run Macroeconomic Growth
Model of Slovakia
Filip Ostrihon, Tomas Domonkos, Miroslava Dolinajcová
This paper presents a calibrated growth model of Slovakia, which is
intended to analyze the effects of various policy scenarios on the Slovak labor market. Furthermore, the analysis covers the impact of these
policy decisions considering the social security systems. We also keep
in mind the revenue and expenditure side of the public finance and
their long-term neutrality. The model is composed of seven interrelated blocks. Special attention is dedicated to the block describing the
labor market, which distinguishes participants according to age, gender, education and inclination towards work.
4 - Auctions, Negotiations, and Reciprocity
Gregory Kersten, Tomasz Wachowicz
Experimental study of multi-attribute reverse auctions with
(non)verifiable multi-bilateral negotiations confirms that the buyers’
surplus is higher in auctions than in negotiations, the winning sellers’ surplus-lower, and there is no difference in social welfare. The
results show that verifiable negotiations produce worse results than
non-verifiable negotiations with negotiators leaving more value on the
table than bidders. This indicates that negotiations have potential to
yield better results than auctions. They are worse mechanisms because
of the buyers’ use of reciprocity rules.
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Tuesday, 10:30-12:00 - Room 212
Applications of Analytics to Strategy
Stream: Strategy and Analytics
Invited session
Chair: Frances O’Brien
1 - System Dynamics and Big Data: New Frontiers for
Strategy
Martin Kunc
System Dynamics is a simulation tool usually associated with the development and analysis of strategies. System Dynamics hasn’t been
considered a simulation that requires large amount of data. However,
there are new trends in the use of System Dynamics and Big Data for
the development and analysis of strategies. This paper discusses existing practices and proposes a new research agenda
2 - Soft Analytics and the Strategy Process
Frances O’Brien, Martin Kunc
Strategy is deciding where an organisation wants to be (direction) &
how it might get there. Strategy development is an organisational process that supports the collection of inter-related activities (setting direction & goals, assessing the internal & external environment, generating & evaluating initiatives, monitoring performance & progress). We
consider definitions of analytics and explore how different categories
of analytic tools can be used to support the activities within a strategy process. We pay particular attention to soft approaches & strategy
tools.
IFORS 2014 - Barcelona
3 - Dynamics in the Formation of Group Preferences
Clemens Hutzinger
Multi-stage decision problems, in which several dependent decisions
are to be taken, frequently occur. Many of these decisions are solved
by groups via group discussions. This piece of research analyses the
role of group members’ characteristics and verbal communication in
the formation of group preferences. We show that both group members’ characteristics and verbal communication have a great impact on
the way group preferences are formed. However, the way group preferences are formed does not match group members’ perceptions thereof.
4 - Optimal Strategy Planning Approach againts the Bad
Impacts of OTTs on GSM Operators
Neslihan Keskin, Cansu Bahadır, Rifat Gürcan Özdemir
This study focuses on strategy planning against the recently increasing usage of Internet-based applications for GSM operators. The
internet-based messaging applications such as WhatsApp, Line, Facebook Messengers are called as Over-The-Top (OTT) players. OTTs
are the applications for which GSM operators cannot charge directly.
Because of that, it may cause a significant decline in revenue from
text-messaging. A mathematical model is developed for determining
optimal strategy against decline in revenue due to the OTTs. The proposed approach is implemented for the GSM operators in Turkey.
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4 - Sparse Computation for Large-Scale Binary Classification
Philipp Baumann, Dorit Hochbaum
Well-known data mining algorithms rely on inputs in the form of pairwise similarities between objects. For large datasets it is computationally impossible to perform all pairwise comparisons. We therefore
propose a novel approach that uses approximate Principal Component
Analysis to efficiently identify groups of similar objects. The effectiveness of the approach is demonstrated in the context of binary classification using the supervised normalized cut as a classifier. For large
datasets from the UCI repository, the approach significantly improves
run times with minimal loss in accuracy.
TB-26
Tuesday, 10:30-12:00 - Room 010
Fuzzy Decision Making 3
Stream: Fuzzy Decision Support Systems, Soft Computing, Neural Network
Invited session
Chair: Jaroslav Ramik
Chair: Martin Gavalec
TB-25
Tuesday, 10:30-12:00 - Room 009
Numerical Methods in Data Mining
Stream: Data Mining
Invited session
Chair: Emilio Carrizosa
1 - SAS High Performance Procedures for Large-Scale
Dense SVM and Quantile Regression
Yan Xu, Joshua Griffin, Leo Lopes
SVM classifiers require solutions to large-scale quadratic optimization
problems. In special cases, such as linear or low-degree polynomial
kernels, a low-rank factorization of the Hessian is available. Such factorizations create equivalent problem formulations amenable to parallel computing environments via interior point methods. Further, this
formulation shares many similarities structurally with certain Quantile
Regression optimization problems. By exploiting the SAS High Performance computing infrastructure, dense problems with billions of
observations are efficiently solved.
2 - A Modified Frank-Wolfe Algorithm for Large Scale
Problems in Data Mining
Francesco Rinaldi, Luigi Grippo, Giovanni Fasano
In this work, we describe a modified version of a classical method in
mathematical programming, namely the Frank-Wolfe Algorithm. We
analyze its properties and test its efficiency on some large scale problems in Data Mining.
3 - Dimensionality Reduction of Categorical Data in Support Vector Machines
Dolores Romero Morales, Emilio Carrizosa, Amaya
Nogales-Gómez
Support Vector Machine (SVM) is the state-of-the-art in Supervised
Classification. We propose a methodology to reduce dimensionality in
SVM, by clustering the attributes of categorical variables. We present
three strategies based on solving: the original SVM, a Nonlinear Mixed
Integer Linear formulation and a Mixed Integer Linear formulation.
We compare empirically the performance of the SVM classifier derived using the original data against that using the clustered data. We
show a reduction in the dimensionality of the categorical data with accuracy comparable to that of the original SVM.
1 - Fuzzy Classification in HR Management — Evaluation and Decision Making based on Multiple Attributes
Jan Stoklasa, Pavel Holeček, Jana Talasova
In common practice we work with verbally specified classes of objects. In HR management assigning work, identifying the type of the
worker, promotion or outplacement decisions can be seen as classification problems. In this paper we discuss linguistic fuzzy rule base
classification models suitable for HR management. We show how they
can be used in the area of academic faculty management. When a
preference relation on the classes exists, the linguistic labels of the categories can be used to express evaluation of objects (e.g. membership
in the most preferred class implies the best evaluation).
2 - AHP Model for the Evaluation of Creative Work Outcomes of Art Colleges
Jana Talasova, Jan Stoklasa, Vera Jandova
In recent years a model for the evaluation of creative work outcomes
of art colleges has been created in the Czech Republic. Based on this
model a part of the subsidy from the state budget is distributed. The
model classifies artworks into 27 categories based on three criteria:
significance, extent and institutional reception. Scores of the categories
are computed by a modified AHP method. This paper describes the
progressive development of the model. We focus on the transformation of an expertly defined evaluation strategy into a well-functioning
and yet relatively simple mathematical model.
3 - Logical Aggregation in Decision Making: Applications and Perspectives
Ana Poledica, Ana Horvat, Selena Totic
The aim of this paper is to reflect on existing applications of Logical Aggregation (LA), based on interpolative Boolean algebra, in decision making environment. LA has been applied in the areas such
as finance (e.g., company financial performance), management (e.g.,
portfolio matrix), IT (web services selection), education (candidates
ranking for master studies), etc.. In this paper, we give an overview
of LA applications with various examples using the existing software
tool. We also analyze the method with respect to key properties for its
application, and outline the future perspectives.
4 - Fuzzy Queuing Cost Model Optimization for Bus Passengers with Customers’ Perception of Service
Chie-bein Chen, Hsing Paul Luh, Yi-Chih Chen, Chia-Hung
Wang, Yang-Hua Fan
An optimization model whose queues prior to a service and costs depend on the perception of waiting will be proposed. The goal is to
minimize the total cost by selecting an optimal service level when the
arrival rate, service rate and waiting cost of customers all belong to
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the fuzzy sets. This research is devoted to an approach of fuzzy queue
optimization model and the applications of Markov chains with fuzzy
set theory in queue service. Finally, a real case of bus passengers is
used to evaluate the compromise solutions and make sure whether the
proposed optimization model is feasible or not?
TB-27
Tuesday, 10:30-12:00 - Room 213
Pricing, Bundling, and Strategic
Consumers in Supply Chain Management
Stream: Operations/Marketing Interface
Invited session
Chair: Kathryn E. Stecke
1 - Selling Opaque Goods with Mixed Bundles
Ashutosh Prasad
In addition to pure components selling, a multi-product seller has several available selling strategies. Two possibilities are to create a bundle
or to create an opaque good for filling out the product line. Heretofore
these have been studied as distinct strategies. The goal of this paper
is to examine whether a product line of four products — the original
components, the bundle and an opaque good — can be even more profitable, or whether the opaque good will be dominated.
2 - Impact of Sourcing and Pricing Power on Retailer’s
Optimal Store-Brand Quality under Competition
Candace Yano, Bo Liao
Store-brand products may be produced in-house by the retailer or by a
national-brand or third-party manufacturer. Pricing power within each
supply chain may also differ: the national brand manufacturer or the
retailer may be the Stackelberg leader, or there may be a Nash game
between them. We compare the retailer’s equilibrium store-brand quality decisions across the nine combinations of sourcing decisions and
pricing power relationships.
3 - Demand Shaping through Bundling: A Dynamic Multiproduct Inventory-Pricing Model
Jeannette Song
We study joint optimal inventory, pricing and bundling decisions
over a finite horizon. We show that component complementariness,
cost structure, initial inventory and demand uncertainty all drive the
bundling strategy. For vertically differentiated products, the desired
bundling composition depends on the ratio of cost gap to quality gap.
4 - Towards Closer Integration of Planning and Execution Processes in an Retail Environment
Mozafar Hajian
With emergence of Omni-Channel retailing, retailers need to adapt
their processes to face more technology-savvy, demanding customers
and sophisticated competitors.
Here, we describe how optimization technology is used in a sense and
respond system that enables retailers to track real-time changes in demand and prices of their merchandise in the market in order to evaluate
their market position, impact on their own profitability and to make appropriate decisions that minimize those impacts.
TB-28
Tuesday, 10:30-12:00 - Room 130
Turnkey Optimization on the Cloud (FICO)
Stream: Sponsored Sessions
Sponsored session
Chair: Oliver Bastert
Chair: Susanne Heipcke
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1 - Turnkey Optimization on the Cloud
Oliver Bastert, Susanne Heipcke
In this session we will demonstrate enhancements in the linear, mixed
integer and nonlinear solvers in the latest release of the FICO R
Xpress, including a ground breaking innovation for simplex algorithms. In addition, we will introduce robust modelling and optimization capabilities in Xpress and demonstrate the ease of modeling complex problems. We will discuss how to deploy optimization applications using FICO R Optimization Modeler on the FICO R Analytic
Cloud. Through the FICO R Decision Management Platform, FICO’s
new cloud-based tools platform, you can build,
TB-29
Tuesday, 10:30-12:00 - Room 011
Multiple Criteria Decision Making and
Optimization 3
Stream: Multiple Criteria Decision Making and Optimization
Contributed session
Chair: Douwe Postmus
1 - Accident Causation Analysis with Multiple Criteria
Decision Making Methods in Workplaces
Erdem Aksakal, Metin Dagdeviren
Nowadays, one of the issues that constitute major problems for businesses is the occupational accident. The number of factors that will
affect the size of businesses involved in the accident, area of activity,
working conditions, dynamic properties and etc. is directly proportional. In this study, taking on the basis of three main criteria and 12
sub-criteria with using multi-criteria decision-making methods of Entropy and DEMATEL in an integrated manner and aimed to present the
most important factor that caused the accident.
2 - Effectiveness Analysis of Ratios from Paired Comparison
William Wedley, Eng Choo, Diederik J.D. Wijnmalen
In MCDM, ratio priorities are often derived from paired comparison
matrices. With AHP/ANP, the principal right eigenvector of the matrix is used. Other worthwhile procedures are available. This study
analyzes and compares the effectiveness of various methods, where effectiveness is defined as the trajectory to zero as comparison matrix
converges to the true comparison matrix. To facilitate this analysis,
simulation is used to (1) derive a true comparison matrix and (2) perturb that matrix to different levels of error. Various measures of effectiveness are used to record the convergence.
3 - Prioritization of Collaborative Innovation Values
Irem Duzdar, Gulgun Kayakutlu, Bahar Sennaroglu
Innovation is the best competitive advantage for small and medium
enterprises (SMEs) that are trying to globalize.However,SMEs have
to construct alliances with the other companies, SMEs and organizations to innovate.Each type of alliance has a specific risk and success
factors.First aim of this study,the successful alliances based on Helix
relations will be analyzed and taxonomy on the effective criteria will
be constructed.The second is to prioritize them using Analytical Network Processing method.Achievements will support strategic alliance
decisions with the collaboration principles.
4 - Multi-criteria decision analysis in medical decision
making
Douwe Postmus
The assessment of benefits and risks is a central element in clinical decision making. It also plays an important role in the market authorization of new pharmaceutical treatments and in subsequent decisions to
reimburse these treatments. What these settings have in common is that
they all require the transformation of a large amount of clinical data on
multiple outcome measures into an overall balance to ultimately make
a yes/no decision. In this talk, we illustrate by means of a case study
how such decisions can be reached in a transparent way by applying
multi-criteria decision analysis.
IFORS 2014 - Barcelona
TB-30
Tuesday, 10:30-12:00 - Room 012
Advances in Financial Decisions and
Their Long-Term Horizon
Stream: Financial Mathematics and OR
Invited session
Chair: Thomas Burkhardt
Chair: Andreas Loeffler
Chair: Ursula Walther
1 - Survival Risks and Risk Averse Management in
Forestry
Thomas Burkhardt
Forest investments are subject to survival risks related to calamities.
Previous research, mostly based on simulation techniques, has demonstrated the economic relevance on both valuation and management.
Recent studies by Möhring et al. (2011) and Burkhardt et al. (2014) developed an analytic perspective on the incorporation of survival risks
into a Faustmann-type model, based on expectations. I extend this
approach to incorporate value volatility on a stand level, which is of
interest conceptually as well as for the management of small private
forests.
2 - Transaction Costs and Bid-Ask-Spreads
Andreas Loeffler
The authors investigated a complete order book data set from XETRA
2003, containing all order book snapshots of all DAX titles that were
traded during that year. It turned out that the average bid-ask spread
over that period, taken over all entries, is closely related to the average
number (but not value) of assets of every transaction recorded. This
relation is robust with respect to weekly, monthly and yearly averages;
daily averages show a different (but also related) pattern. It seems that
this relation is based on the fact that transaction costs are much greater
than information costs.
3 - Risk Quantification in PPP Projects
Ursula Walther
PPP projects combine a long lifetime with considerable technical and
market risks. The optimal allocation of risks to the project partners, especially public versus private parties, is a core challenge. Additionally,
an economic assessment of the project’s cost effectiveness is necessary.
Both tasks require the estimation of appropriate risk costs. We suggest
a new method for risk quantification in PPP projects based on a valueat-risk idea. Reconciling state-of-the art risk management methods
with practical data limitations we develop adequate risk premiums.
TB-31
Tuesday, 10:30-12:00 - Room 013
Portfolio Decision Processes
Stream: Decision Processes
Invited session
Chair: Juuso Liesiö
1 - Project Portfolio Selection for Group Decision Making using Multi-Criteria Analysis and Mathematical
Programming through an Iterative Approach
Olena Pechak, George Mavrotas, Eleftherios Siskos, John
Psarras
We propose an Iterative Trichotomic Approach (ITA) to deal with a
group of decision makers (DM) in project selection problems. The basic idea is a separation of projects into three sets: green - selected by
all DMs, red - rejected by all DMs and the grey projects - selected by
some of them. As iterative process moves from round to round (using a
weight convergence process), green and red sets are enriched whereas
the grey set shrinks until becomes empty. The final outcome is a consensus portfolio of projects, the degree of consensus on each project
and consensus index for the whole portfolio.
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2 - Adjustable Robustness for Multiobjective Project
Portfolio Selection
Thomas Fliedner, Juuso Liesiö
Robust Portfolio Modeling (RPM) supports project portfolio selection with multiple, uncertain project outcomes. By determining nondominated portfolios for all realizations of uncertain parameters, RPM
considers worst-case scenarios, which are impractical for some reallife decision problems. We reduce the set of outcome scenarios by limiting the number of parameters which may deviate from their expected
value. Adjusting this limit, decision makers can choose desired levels
of conservatism, in extreme cases considering only expected outcome
values or all possible scenarios.
3 - Baseline Value Specification and Sensitivity Analysis
in Multiattribute Project Portfolio Selection
Juuso Liesiö, Antti Punkka
A key issue in applying multiattribute project portfolio models is
choosing baselines that define the value of not doing a project. Yet,
specifying these baselines can be difficult as it may require, for instance, scoring the strategic fit of not doing a project. We develop
advanced techniques for specifying baselines which admit incomplete
preference statements. Furthermore, we develop integer programming
models to analyse the sensitivity of project and portfolio decision recommendations when only incomplete information about the baselines
is available.
4 - Multicriteria Decision Support for Planning Renewable Power Production at Moroccoan Airports
Risto Lahdelma, Abdellah Menou, Pekka Salminen
The Moroccan Airport Authority ONDA has introduced a "green airports’ program by which airports will be supplied by solar and wind
power in addition to conventional power from the national grid. The
problem is to select at which airports ONDA should build solar and
wind power parks, and how large they should be. The choice is made
subject to multiple criteria, including economy, technical feasibility,
and environmental concerns. In this paper we use Stochastic Multicriteria Acceptability Analysis (SMAA) to compare different alternatives
to produce renewable power at airports.
TB-32
Tuesday, 10:30-12:00 - Room 014
Crisis and Disaster Management
Stream: Humanitarian Operations Research
Invited session
Chair:
Chair:
Chair:
Chair:
Silja Meyer-Nieberg
Erik Kropat
Goran Mihelcic
Jose Holguin-Veras
1 - Routing for Post-Disaster Needs Assessment Operations
Burcu Balcik, Burak Guragac
After natural disasters, governmental and/or non-governmental organizations conduct rapid needs assessments to identify victims’ needs.
Due to limited time and resources, it may not be possible to visit all of
the affected locations, so an efficient assessment plan must be developed. In this study, we develop a mathematical model to support site
selection and routing decisions of the post-disaster needs assessment
teams. We develop a tabu search algorithm to solve the realistic problem instances efficiently and present computational results to illustrate
the performance of the algorithm.
2 - A Consistent Design Supporting Structure For Crisis
Management Integrating Personal Behaviours Case
analysis: The 2009 Australian Bushfire
Cerasela Tanasescu, Rudnianski Michel
In crisis management, the issue is to take appropriate decisions that will
enable to solve the crisis as satisfactorily as possible. The present paper
aims to give a first sketch of a consistent design supporting structure
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(i.e. a general model depicting the structure of a crisis, and positioning personal behavioural features with respect to the crisis dynamics)
applied to the concrete case of Australian bushfire — Victoria 2009.
In this respect, the paper proposes a general guideline for addressing
crisis management issues in which personal behavioural features play
a significant role.
3 - A Resource Distribution Network Model for Emergency Logistics Planning
Rojee Pradhananga, Shaligram Pokharel, Fatih Mutlu, Jose
Holguin-Veras, Dinesh Seth
We present a proactive resource distribution approach for emergency
response planning, in which actual demands at the post-disaster stage
are met through pre-positioned resources at Distribution Centers (DCs)
and/or through direct post-disaster shipments of resources from suppliers. A stochastic two stage model is presented to determine locations
of the suppliers and DCs along with pre-disaster and post-disaster resource allocations. Application on a case study and analysis of factors
affecting the resource allocations are discussed. (Acknowledgement:
Qatar/QNRF/NPRP Project: 5-200-5-027)
4 - Facility Location and Network Design for Intermodal
Transportation of Hazardous Materials
Ginger Ke, Ghazal Assadipour, Manish Verma
This research studies the network design problem of an intermodal
transportation network for hazardous materials, where the government
regulates the location of intermodal terminals, and the carrier determines the routing of shipments. We formulate a bilevel programming
model, which considers the dominant relationship between the government and carrier, and develop a meta-heuristic-based solution method
to solve this model. The proposed framework and methodology is
tested on realistic size problem instances. Computational experiments
provide detailed managerial insights for the shareholders.
Selecting the best maintenance method is one of the critical decisions
for weapon systems. In this study, we applied an integrated decision
making approach based on Delphi and Analytic Hierarchy Process
(AHP) methodologies to solve aircraft maintenance problem. First,
Delphi method is utilized to determine the evaluation criteria by a consensus of decision makers. Then, AHP is used to structure the problem,
weight the criteria and determine the final scores of the alternatives.
Finally, we conclude that integrated approach fits best for this kind of
problems in the strategic headquarters.
4 - Multi-Criteria Evaluation of Conceptual Aircraft Designs
Ahmet Kandakoglu, Y. Ilker Topcu, Cengiz Kahraman
This study presents a realistic decision making approach based on
Fuzzy Axiomatic Design (FAD) and Stochastic Multicriteria Acceptability Analysis (SMAA) methods for selecting the best conceptual
aircraft design during an aircraft development process. While FAD
method helps to select the design that meets the operational requirements the most under uncertainty, SMAA method handles different
kinds of imprecise and partially missing preference information in a
consistent way. This approach is a well suited tool for this kind of
decision making problems. Finally, an empirical example is given.
TB-34
Tuesday, 10:30-12:00 - Room 016
Portfolio Optimization 2
Stream: Decision Making Modeling and Risk Assessment in the Financial Sector
Invited session
Chair: Paulo Rotela Junior
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Tuesday, 10:30-12:00 - Room 015
Defence and Security Applications II
Stream: Defence and Security Applications
Invited session
Chair: Ana Isabel Barros
1 - Prioritization of Capability Gaps in Defence Planning
Petter Kristian Køber, Alf Christian Hennum
We propose a procedure for prioritization in long term force structure
planning, which is based on a well-established capability and scenario
based method for defence analysis. The purpose is to bridge the gap
between capability requirements and capability development. The procedure consists of a gap analysis of the structure, an impact assessment
of potential gaps, a setting of a level of ambition for the structure as a
whole and a risk calculation and analysis. It is flexible in the sense that
the ambition level is easily adjusted.
2 - Multi-Criteria Decision Support for Base Closure and
Realignment
Özkan Özcan, Ahmet Kandakoglu, Nurdinç Şenay
Base Closure and Realignment (BCOR) has become one of the crucial
strategic activities in the defense planning due to the recent budget limitations. This study presents a decision model based on the Stochastic Multicriteria Acceptability Analysis (SMAA) method to support
this activity. SMAA is a recent method that handles different kinds
of uncertain, imprecise and partially missing information in a consistent way. It assigns probability distributions to the criteria scores and
orders the criteria weights, and then applies Monte-Carlo simulation.
Finally, an empirical example is given.
3 - Multi Criteria Evaluation of Weapon System Maintenance Methods
Nurdinç Şenay, Ahmet Kandakoglu, Berna Cigdem Baz
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1 - Generalized Interval Multi-Objective Programming
Problem and its Application to Portfolio Selection
Pankaj kumar, Geetanjali Panda, Umesh Gupta
We consider a multi-objective decision making model, wherein all parameters and decision variables are intervals. The existence of an acceptable compromise feasible solution of this model is established,and
a methodology is proposed to derive such a solution in three major steps:assigning the degree of acceptability to every feasible solution;assigning goals to each objective function;and assigning a degree
of acceptability to each objective value corresponding to its goal. This
theoretical development is illustrated in the portfolio selection model
with data from Bombay Stock Exchange, India.
2 - Clustering Stocks for Portfolio Optimization
AnaSofia Ferreira, Fernando Bacao, Patricia Xufre
Portfolio optimization can be characterized has the decision-making
process involved in matching investments to objectives, usually balancing risk and return. Selecting the appropriate assets based on a risk
level criterion constitutes a complex procedure and represents one of
the most important decisions that investors make. This paper presents
experimental results of the use of cluster analysis for identifying different types of assets, which, in a subsequent step, might be selected into
a portfolio. The result is a visual SOM/k-means model for financial
analysis of FTSE and Nasdaq Index.
3 - Developing a Credit Rating model for Supreme Banking Portfolio at ZABG Bank
Fadzayi Ndlovu
This research focused on identifying the determinants of risk of default and then developing a relevant credit rating model for a bank in
Zimbabwe. The empirical results from logistic regression show that
there are six variables which increase the probability of default (PD)
of the clients. The PDs for each of the supreme banking clients were
grouped into ten clusters using the K-Nearest Neighbor (KNN) algorithm. These ten clusters were then adopted as the risk grades for the
490 supreme banking clients that were in the study population.
IFORS 2014 - Barcelona
TB-37
4 - Forecast and Fuzzy Data Envelopment Analysis: A
Portfolio Optimization
Paulo Rotela Junior, Edson Pamplona, Fernando Salomon
1 - Using GPS Data to Model Forest Fire Initial Attack
Airtanker Operations
David Martell, Nick Clark
This article aims to use forecasting techniques associated with Fuzzy
DEA - Data Envelopment Analysis to analyze the behavior of assets
portfolio. The research follows the Box-Jenkins methodology using
ARIMA model to forecast indicators such as return, variance, beta and
others. The prediction interval and the predicted value obtained will be
used like values of a triangular Fuzzy distribution of the variables used
as input and output of Fuzzy DEA model. Finally, the assets considered efficient in this model will be submitted to the Sharpe approach to
optimize the portfolio composition.
The airtankers that the Ontario Ministry of Nat. Resources uses for forest fire suppression are equipped with GPS units that track their realtime location, velocity and altitude but they do not indicate which fire
is being fought, the time each airtanker spends travelling to and from
each fire or the time each airtanker spends flying between each fire and
the lake from which it scoops water to drop on the fire. We developed a
methodology that we used to determine 1) what was happening at each
point along the airtanker’s track and 2) the time and location of every
water drop on each fire.
2 - Optimal Deployment During an Escaped Fire
John Hearne, James Minas, Melih Ozlen
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Tuesday, 10:30-12:00 - Room 131
Game Theory with Applications II
Stream: Stochastic Modeling and Simulation in Engineering, Management and Science
Invited session
Chair: Leon Petrosyan
Chair: Vladimir Mazalov
Chair: Katsunori Ano
1 - The Effect of Shock in Repeated Network Games
Artem Sedakov
The dynamic network formation game is considered. A player who has
the largest set of neighbors in the network may leave the game with a
positive probability. This effect is called "shock". The effect of shock
may appear only once, and the stage number, on which the shock is
occurred, is chosen at random. In the cooperative scenario of this repeated network game the characteristic function is constructed. Timeconsistency of the Shapley value is investigated. To prevent players
from breaking the cooperative agreement, a mechanism of stage payments is designed.
2 - Nash Bargaining Solutions in a Cooperative Fish War
Model
Vladimir Mazalov, Anna Rettieva
Discrete-time game-theoretic cooperative fish war models are investigated. The players differ in their time preferences and use different
discount factors. We propose to use Nash bargaining solution in order
to determine cooperative behavior and present two approaches. In the
first one the cooperative strategies are determined as Nash bargaining
solution for the whole planning horizon. In the second, we use recursive Nash bargaining procedure determining the cooperative strategies
on each time step. The results of numerical modelling and comparison
of the schemas are presented.
3 - Sharing Rules for Minimum Cost Arborescence Problems
Yoshifumi Kusunoki, Tetsuzo Tanino
In this talk, we address minimum cost arborescence problems (mcap),
which are extensions of minimum cost spanning tree problems (mcstp) with possibility of asymmetric costs of edges. Recently, Dutta
and Mishra have proposed a rational cost allocation rule for mcap. We
propose a class of cost allocation rules, called sharing rules. We investigate properties of the sharing rules. Moreover, we show that the
proposed sharing rules are generalizations of the Dutta-Mishra rule and
other allocation rules for mcstp.
TB-36
Tuesday, 10:30-12:00 - Room 132
Forest Fire Suppression
Stream: OR in Agriculture, Forestry and Fisheries
Invited session
Chair: John Hearne
Consider a fire sweeping across a landscape with identified assets.
Each asset has a value, resources required and a time-window for treatment to reduce risk of loss. Deployment decisions are complex and
time-critical. This problem is addressed by extending the concept of
the orienteering problem. Model formulation, illustration and performance will be presented.
TB-37
Tuesday, 10:30-12:00 - Room 017
Metaheuristics for Multiobjective
Optimization
Stream: Multiobjective Optimization
Invited session
Chair: Abraham Duarte
1 - Heuristics for the Bi-objective Path Dissimilarity
Problem
Jose Luis Gonzalez-Velarde, Rafael Marti, Abraham Duarte
The aim of this work is to formally introduce the path dissimilarity
problem as a bi-objective optimization problem, in which a single solution consists of a set of p different paths, and two conflicting objectives arise, on one hand the average length of the paths must be kept
low, and on the other hand the dissimilarity among the paths in the set
should be kept high. A new GRASP procedure is proposed and tested
against previous methods, which are reviewed, and we show that it is
able to create better approximations of efficient frontiers than existing
methods.
2 - An Adaptation of the Variable Neighbourhood Search
Methodology for Multi-Objective Optimization Problems
Eduardo G. Pardo, Juan J. Pantrigo, Borja Menéndez,
Abraham Duarte
Variable Neighbourhood Search is a general-purpose methodology
widely used to solve optimization problems when only one objective
is minimized / maximized at the same time. However, some of the key
ideas of the methodology might also be useful in the multi-objective
context. We propose an adaptation of some of the steps of the Variable Neighbourhood Search methodology to solve multi-objective optimization problems. In particular, we describe how to modify the classical design of the shaking, neighbourhood change and improvement
procedures of the methodology to address these kinds of problems.
3 - Multi-Objective Hybrid Algorithms for Solving Routing Problems
Ana Dolores López Sánchez, Alfredo G. Hernandez-Diaz,
Miguel A. Hinojosa, Francisco Gortázar, Abraham Duarte
The recent interest of some researches to address multi-objective routing problems is motivated by both its theoretical and its practical importance. We address a multi-objective routing problem which objectives are to minimize the number of vehicles, the total distance, and the
duration of the longest route (to balance the working day). To solve the
problem, we propose four multi-objective hybrid algorithms. Specifically, we combine Greedy Randomized Adaptive Search Procedures
to build high-quality feasible solutions and Variable Neighbourhood
Descent algorithms to improve them
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4 - A Multi-Objective Multi-start Algorithm for a Balanced Real-World Open Vehicle Routing Problem
Alfredo G. Hernandez-Diaz, Ana Dolores López Sánchez,
Julian Molina, Daniele Vigo, Rafael Caballero
The aim of this paper is to solve a real-world problem proposed by
an international company operating in Spain modeled as a variant of
the Open Vehicle Routing Problem in which three objectives are considered: minimize the number of routes used, balance the duration of
these routes and minimize the makespan, i.e., the maximum time spent
on the vehicle by one person. A competitive multi-start algorithm,
able to obtain a set of efficient solutions in reasonable computing time
is proposed. The effectiveness of the algorithm is examined through
computational testing on hard real-world problems.
TB-38
Tuesday, 10:30-12:00 - Room 214
Sparse Optimization Methods
Stream: Convex Optimization Methods and Applications
Invited session
Chair: Yaxiang Yuan
Chair: Xin Liu
1 - A Subspace Method for Minimizing a Convex
Quadratic Function with Sparsity Constraint
Yaxiang Yuan
This talk presents a subspace method for solving a special sparse optimization problem. The problem is to minimize a convex quadratic
function subject to a sparsity constraint. The method presented applies
subspace techniques, which generates the iteration points in subspaces
that have sparsity property. Theoretical properties of the method will
be given and numerical results will be reported as well.
2 - Lower Bound Theory for Schatten-p Quasi-Norm
Regularized Least Squares Problem
Qingna Li, Shiqian Ma
Consider the Schatten-p quasi-norm regularized least squares problem
with p between 0 and 1. In this talk, we develop a lower bound theory for the Schatten-p regularized least squares problem. Moreover,
we characterize the first and second order necessary conditions for the
problem. A smoothing gradient method is proposed, where the developed lower bound is employed to the final solution to get a lower rank
output. Numerical results are reported to confirm the efficiency of the
method.
3 - A Feasible Direction Method for Nonsmooth Convex
Constrained Optimization
Jose Herskovits, Mario Tanaka
The present algorithm combines ideas of bundle methods with an interior point algorithm for smooth constrained optimization. An equivalent formulation for the original problem is stated and a sequence
of auxiliary problems is built, approximating by planes the objective
function and the constraints. At each of the steps, a search direction for
the auxiliary problem is computed solving two linear systems. When
the step is serious, this direction is feasible with respect to the original
problem. We prove global convergence and show very good numerical
results for a set of test problems.
TB-39
Tuesday, 10:30-12:00 - Room 018
ORAHS VII - Healthcare Systems
Stream: Health Care Applications
Invited session
Chair: Sally Brailsford
Chair: Cigdem Gurgur
110
1 - The Doctor Staffing Model in Outpatient Department
Based on Queuing Theory and Integer Programming
Li Luo, Yong Lei
This study builds a doctor staffing model in outpatient department .This
model is designed based on queuing theory and integer programming;
the least number of doctors is calculated by using queuing theory based
on the waiting time that outpatients can tolerate from the survey reports. Then, its corresponding genetic algorithm is designed to solve
the model. Finally, the model is applied to the digestive system department in West China Hospital and the results show that the outpatient
doctor staffing model reduces the waiting time of patients and improves
the doctors’ job satisfaction.
2 - Operating Room Scheduling With Sequence Dependent Uncertain Surgery Times
Enis Kayis, Tagi Hanalioglu, Refik Gullu
Effective operating room (OR) planning requires right surgery duration estimates. Recent empirical findings suggest that as well as wellknown factors such as surgical team assigned to the case, time and
sequence within a day may also affect the duration of a surgery. In
this work, we study the optimal OR schedule under uncertain surgery
duration that depend on the assigned sequence of the case. Our results
show that scheduling the surgeries in increasing order of variability
could improve the schedule’s performance under multiple criteria such
as utilization, overtime and waiting time.
3 - Sustainable HealthCare Supply Chains — Bundling
Decisions for HealthCare Products
Cigdem Gurgur
With the profound interest in healthcare waste given its impact on costs
and the environment, our study considers supplier selection and quantity allocation decisions for a health care provider that may purchase
new products, as well as refurbished products in managing the endto-end supply chain. New products are more expensive than the used
ones, but can be delivered any time and in any quantity. Refurbished
products have the same quality, but they are sold in bundles. We use
data from a large healthcare provider to test the implications of our
study.
4 - Network Representation of Subproblem Solution
Spaces in Nurse Scheduling
Atsuko Ikegami, Yuma Tanaka
Nurse scheduling is known to be difficult to solve. Even evaluating
given solutions is hard because it is impossible to explicitly describe
all considerations. We construct a network that represents all feasible
schedules for a given nurse. In this network, any path from the source
to the sink represents a feasible schedule, and the network contains all
feasible schedules. If schedules are fixed for all other nurses, we can
efficiently obtain optimal and near-optimal schedules by finding the
shortest and k-shortest paths in the network. This can be helpful in
scheduling nurses efficiently.
TB-40
Tuesday, 10:30-12:00 - Room 019
Educational Planning and Development
Stream: Educational Planning and Development
Invited session
Chair: Laura Lotero
Chair: Milagros Baldemor
Chair: Subhash Datta
1 - Design of Balanced Diets for 1 to 3 Year-Old Children
from Government Day-care Centers in Ecuador
Sandra Gutierrez, Fernanda Salazar, Adrian Sarango
We study the case of government day-care centers in Ecuador, which
provide 70% of daily required nutrients to 1-3 year-old children. First,
we discuss a nutritional evaluation of current diets served at these centers. Afterwards, we formulate an integer linear version of the Stigler’s
diet problem in which we take into account not only the satisfaction
of lower or upper bounds of nutrients, but also their balanced intake.
Finally, we present computational results and conclusions for the problem.
IFORS 2014 - Barcelona
2 - Monte Carlo Simulation and Optimization for pollution reduction strategies at the Colegio Mayor de Antioquia University
Luis Alejandro Builes, Carlos Hoyos, Michelle Muñoz,
Alejandra Ramirez Muñoz, Daniela Valencia Arroyave
In order to estimate emissions due to commuting to the Institución
Universitaria Colegio Mayor de Antioquia, we simulate with a Monte
Carlo technique the emission factor assignment to different types of
bus technologies available in the city for commuting. We estimate
emissions for all transportation modes and then we seek alternatives to
pollution reduction using the Simplified Emissions Estimation Model
and the occupation factors to formulate the optimization model for the
assignment of available private car seats to bus commuters to minimize
pollutant emissions.
3 - School Efficiency in a Developing Country
Gerhard Kent, Hennie Kruger
To manage a school efficiently in a developing country is a challenge
which is often due to mismanagement of resources. In this study the
efficiency of secondary schools in the North-West Province of South
Africa is investigated. A DEA model without inputs and combined
with a layered pareto optimal principle is applied with main outputs
being pass rates of different subjects in different grades. Preliminary
results indicated that this output only layered model enables the ranking of schools and also provides intermediate goals for the inefficient
schools to become more efficient.
4 - Efficiency of Accounting Education in the Philippines
Arlyn Villanueva, Brian Canlas Gozun
The Certified Public Accountant licensure examination in the Philippines is one of the toughest in the country. This paper proposes a
method for modeling accounting education in the Philippines in order to improve the passing rates of accounting graduates. Out of the
more than 1,200 business schools in the country, there are around 300
schools that offer accountancy. Only 30 to 40% of the graduates pass
the licensure examination and this study will propose ways to improve
accounting education by benchmarking using data envelopment analysis.
TB-42
The Uncapacitated Facility Location Problem is a widely researched
problem already tackled by many proposals with outstanding results.
Our proposal is a new simple-but-effective Iterated Local Search algorithm that outperforms former proposals, both in computing time and
result quality. We proved the algorithm value with the well-established
benchmarks and then applied the algorithm to solve planning issues on
very different fields like logistics, transportation, distributed computing or network deployments.
3 - ReSATyrus: A Distributed Resource-Sharing Control
Compiler
Priscila Lima, Daniel Alves, Felipe França
Dealing with consistent, scalable behaviour control of high numbers of
entities is a challenge intrinsic to modern problems such as intelligent
transportation systems and collective robotics. This work presents a
distributed approach to the generation of asynchronous, yet coherent,
trajectories of multiple entities sharing common routes and intersections. Derived from a SAT-based constraint programming platform,
ReSATyrus translates resource-sharing specifications into constraint
graphs, upon which Scheduling by Edge Reversal dynamics is applied
to provide the desired distributed control.
4 - Modeling Approach to Simultaneous Scheduling Batteries and Vehicles in Optimization of Transportation
and Handling Tasks Realization
Milorad Vidovic
Battery operated vehicles are typical solution to performing material
handling and transportation tasks for several decades. Efficient and
economic use of transportation and handling equipment requires implementation of different operational and tactical decisions: fleet size
determination, optimal routes defining, etc.. For the case of battery
operated vehicles, additional decisions related to changing and charging batteries should be also made. However, in the literature and in
practical application this impact is not fully recognized.
TB-42
Tuesday, 10:30-12:00 - Room 215
TB-41
Tuesday, 10:30-12:00 - Room 216
Metaheuristics and Simheuristics in
Logistics and Production
Stream: Simulation-Optimization in Logistics & Production
Invited session
Chair: Angel A. Juan
Chair: Djamila Ouelhadj
1 - Simheuristics: Hybridizing Simulation with Metaheuristics for Decision-Making under Uncertainty
Angel A. Juan, Scott Grasman, Javier Faulin, Markus Rabe,
Tolga Bektas
Many real-world problems in the production and logistics business
are complex to solve even in their deterministic representation, in
part due to their large size and the rich (real-life) constraints they include. To complicate things even further these problems frequently
show stochastic behavior, thus making them difficult to solve by just
using exact methods. A suitable and natural approach to solve these
stochastic combinatorial optimization problems is to use ’simheuristics’, which combine heuristic optimization with simulation techniques.
2 - A Multi-Start based Algorithm with Iterated Local
Search for the Uncapacitate Facility Location Problem
Guillem Cabrera, Sergio Gonzalez, Angel A. Juan, Joan
Manuel Marques, Scott Grasman
Efficient Big Data Algorithms
Stream: Big Data Analytics
Invited session
Chair: Jonghun Park
Chair: Seoung Bum Kim
1 - Instant Planning with Case Based Reasoning
Jonghun Park, Beom-suk Chung, Yongsuk Yang, Junseok
Lim, Inbeom Park, Heewoong Park
A computational framework for instantly solving planning problems is
presented in this paper. The proposed framework is broadly based on
a case based reasoning approach, and aims to produce a solution very
quickly without compromising the solution quality too much through
approximating the decisions made by an optimal planner in the form
of state-based decisions. Experiment results show that the proposed
framework works satisfactorily for real-life planning and scheduling
problems and helps promoting a firm’s agility through enabling realtime (re)planning as well as what-if analysis.
2 - Non-Parametric Machine Learning Models for Predicting American Option Prices: Comparison Study
Hyunwoong Ji, Sangwoo Han, Jaewook Lee
In this paper, we investigate the performance of non-parametric machine learning models with respect to the in-sample pricing and outof-sample prediction performances of index American options. The
comparisons were performed on the 10 years S&P 100 Index American options from January 2004 to December 2013. We also verified
the statistical differences between the compared methods by testing
the null hypothesis that two series of forecasting errors have the same
mean-squared value.
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3 - U.S. Senate Network Analysis based on Roll Call
Votes
Young Joon Park, Seoung Bum Kim
Several quantitative analyses have been conducted to understand the
collective behavior of social groups. In this study, we propose a systematic approach to comprehend the political tendencies and voting
patterns of politicians resulted by their social positions and relationships. The proposed analytic methodology measured the voting similarities of senators by the results of roll-call vote from 1989 to 2013,
and is represented as a social network graph. Our results show that
each senate network has different topological properties according to
subjects of bills.
TB-43
Tuesday, 10:30-12:00 - Room 217
Accounting and Management Decisions
Stream: Operational Research in Financial and Management Accounting
Invited session
Chair: Markus Puetz
1 - Implementing Value Engineering based on a Multidimensional Quality-Oriented Management Control
Calculus within a Target Costing and Target Pricing
Approach
Markus Puetz, Stefan Bock
In order to meet customer needs and to achieve the business objectives,
value engineering (VE) has become a crucial part of target costing.
This presentation addresses a new VE-procedure which is based on a
multidimensional quality-oriented management control calculus. The
structure of the VE-procedure is illustrated at first. Subsequently, its
mathematical problem model and an according approach for effective
production planning are introduced. Moreover, specific aspects of the
proposed procedures for the analysis and control of occurred cost and
proceeds deviations are depicted.
2 - Robust Long Term Planning of Municipal Budgets
Christian Fritze, Matthias Amen
The German budget law requires municipalities to sustain their equity.
If future losses are expected to reduce the equity about a legally defined value, the municipality has to plan and describe measures to restore budget balancing within a period of at most ten years to prevent
debt overload. The questions arise on how municipalities create robust
plans over such long term periods considering the specific restrictions
of the public sector such as the commitment to satisfy the demand for
core services. We present an approach for robust long term planning
for municipalities.
3 - The relationship of Cost System Precision and Organizational and Procedural Structures
Jan-Gerrit Heidgen, Stephan Lengsfeld, Arndt Rüdlin
We extend the approach of Labro/Vanhoucke (2007) to analyze the
interacting effects of structural and procedural improvements on cost
system precision in ABC systems. Firstly, we show that interactions
differ when organizational structures are changed after procedural
structures are set compared to the inverse scenario. Secondly, improvements on stage II have a larger impact on cost accuracy -compared to
those on stage I- only as long as structural errors on the first stage aren’t
too severe. Thirdly, we provide design-recommendations depending
on different initial states of the cost system.
4 - Flexibility in Cost-based Transfer Pricing
Markus Brunner, Peter Schaefer
Cost-based transfer prices are frequently used to guide intra-firm trade
and also provide incentives for investment. We investigate whether
transfer prices should be fixed ex ante for the long run or adjusted each
period when future costs and revenues are uncertain. We find that more
flexible transfer prices improve trading decisions in the short run, but
cause underinvestment in the long run. Specifically, transfer prices
should be fixed if uncertainty about future costs is low, and adjustable
if uncertainty is intermediate; with high uncertainty, they should be
based on actual costs.
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TB-44
Tuesday, 10:30-12:00 - Room 218
Additional Educational Activities for OR
Stream: Initiatives for OR Education
Invited session
Chair: Gerhard-Wilhelm Weber
Chair: Elise del Rosario
Chair: Liudmyla Pavlenko
1 - Developing OR Application Skills with AIMMS: A
Bridge in OR Education
Ovidiu Listes
We share our experiences in training both academics and OR professionals for developing OR application skills using AIMMS. Whether
the users are students moving from theory to practice or professionals who need to acquire skills in a short time, AIMMS can contribute
to bridging the gap in the OR education. Fast and flexible modeling,
powerful solvers and integrated visualization are among the AIMMS
features which facilitate learning, create understanding and stimulate
further application refinements. While we illustrate these aspects based
on several examples, interaction is much appreciated.
2 - An Overview of the Intensive Programme in Optimization and DSS for Supply Chains (Odss.4SC)
Giuseppe Bruno, Ana Amaro, Miguel Casquilho, Albert
Corominas, Juan Manuel Garcia Lopez, Andrea Genovese,
Carla Henriques, Amaia Lusa, Johan Magnusson, Henrique
Matos, Joao Miranda, Ana Paula Barbósa-Póvoa, Susana
Relvas, Sergio Rubio
The third edition of the Odss.4SC Erasmus Intensive Programme is
taking place in Portalegre, Portugal (6-20 July-2014). Once again,
about 40 MSc and PhD students from Engineering and Logistics programmes from many countries are participating. Academics from 8
higher education institutions will be delivering classes; lab sessions
are kindly supported by IBM/ILOG. The talk will illustrate the summer school activities and the lessons learned in the former editions
(2012, 2013); also, a preliminary evaluation of the triennial project is
presented.
3 - Summer School AACIMP: Introducing Operational
Research to the Students with Various Backgrounds
Liudmyla Pavlenko, Oksana Dziuba, Alexis Pasichny,
Kateryna Pereverza, Dmytro Fishman, Olga Nazarenko,
Gerhard-Wilhelm Weber
Operational Research is a truly interdisciplinary field that provides
many applied researchers instruments needed for dealing with complexity of real-life problems. Yet for many educators the issue of integrating OR into regular curriculum remains challenging. We propose
advanced education and particularly summer schools as a conventional
form for testing and developing new approaches towards OR education. This talk aims to present our experience of developing international project Summer School AACIMP in the NTUU "KPI", pointing
out its benefits and pitfalls.
4 - Feedback from the field - ILOG in IBM for a smarter
planet
Alex Fleischer
(0) We will not deal here with theories and models but only deployed
applications. (1) Operations Research is a GPT (General Purpose
Technology). We will give here some examples of real-life applications. (2) OR as a way for Sustainable Development: Water, Energy,
Transport ... . (3) OR as a long-term practice with applications that
will run for decades, what can we learn from IBM Mainframes. (4)
What is ahead? - New problems to solve. - Moving from craft-work to
industrial practice. - Making the most out of more powerful machines
and architectures.
IFORS 2014 - Barcelona
TB-45
Tuesday, 12:15-13:45
Geometric Clustering
TC-50
Tuesday, 10:30-12:00 - Room 219
Stream: Geometric Clustering
Invited session
Chair: Steffen Borgwardt
Chair: Andreas Brieden
Chair: Peter Gritzmann
TC-50
Tuesday, 12:15-13:45 - Plenaries room
Plenary Session J. Barceló
Stream: Plenary Sessions
Keynote session
Chair: Nelson Maculan
1 - Partitioning in Polynomial Time via Edge-Complexity
Michal Melamed, Shmuel Onn
The shaped partition problem deals with partitioning n given items
among p players, so that player i gets b_i items. Each player has an
integer utility matrix with columns representing the items’ utility under d criteria, providing the player with a utility vector per partition.
The goal is to find a partition that maximizes a convex objective function on these vectors’ sum. It was shown that for fixed d and p this
problem has a polynomial time algorithm. We show that for small valued utilities, it can be solved in polynomial time even for variable p by
using its feasible set edge-complexity.
2 - A Balanced k-Means Algorithm for Weighted Point
Sets
Steffen Borgwardt, Andreas Brieden, Peter Gritzmann
We generalize the popular k-means method to handle weighted point
sets and prescribed lower and upper bounds on the cluster sizes. Our
algorithm replaces the assignment step of k-means by the computation
of a weight-balanced least-squares assignment, which we model as a
linear program over a special polytope. The optimal vertices correspond to clusterings that allow strongly feasible power diagrams. We
use this connection to devise a worst-case bound on the number of iterations of our algorithm, which is similar to the known upper bound
for k-means - despite our more powerful framework.
3 - Tabu Search and GRASP for the Capacitated Clustering Problem
Anna Martínez-Gavara, Vicente Campos, Micael Gallego,
Manuel Laguna, Rafael Marti
1 - Analytics and the Art of Modeling
Jaume Barceló
This lecture could have as subtitle "Was Johannes Kepler a precursor
of Analytics? Models constitute a key tool to achieve a deep understanding on how complex systems behave, models have been central
to building the body of knowledge that we understand as "Science’.
Since its origins Operations Research has claimed to be considered a
scientific discipline and, as such, rooted in the model building process.
A process that epistemologically is schematically represented by the
methodological chain: factslawstheories. Kepler’s quest for an interpretation of Brahe’s astronomical observations in terms of a model, his
laws of the orbital motion of planets, is a well known example of the
paradigm of modern science. Since then we have learned that reality
is more complex than we thought, it is uncertain and dynamic in both,
probabilistic and chaotic terms. The technological evolution is supplying quality data in unprecedented amounts, and this has forced us to
develop the appropriate methods to deal with them, but this only means
that the methodological chain of knowledge discovering is now richer
with respect to our capabilities of analyzing the facts, and therefore
opens the door to deeper chances of finding laws and formulating explanatory theories. The search for Higgs Boson, frequently presented
as an archetype of Analytics process, is essentially supported by the
same epistemological principles that Kepler’s work. I would like to
devote my lecture to make some remarks on these similarities and, in
doing this, highlight the relationships in the frameworks of the theme
of this conference: The Art of Modeling.
Our problem consists of forming a given number of clusters from a set
of elements in such a way that the sum of the weights of the elements
in each cluster is within some capacity limits, and the sum of the benefits between the pairs of elements in the same cluster is maximized.
A GRASP with VNS has been recently proposed by Deng and Bard
(2011). We propose a tabu search and several GRASP. They are based
on different neighborhoods, including a new one, not previously proposed for the CCP, in which we implement a one-for-two swapping.
We also hybridized both methodologies for improved outcomes.
4 - Three Distinctive Models for Multicriteria Clustering
Yves De Smet
In multicriteria decision aid, many authors have been interested in assigning objects to predefined groups. This is referred as the sorting
problematic. More recently, they have also investigated how clustering techniques could be extended to this specific context. The goal of
this presentation is to summarize three recent clustering techniques:
a method for partially ordered clustering based on binary matrices, an
exact method for ordered clustering based on ordinal properties of preferences and an extension of the PROMETHEE II method for ordered
clustering.
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TD-01
IFORS 2014 - Barcelona
Tuesday, 14:00-15:30
TD-01
Tuesday, 14:00-15:30 - Room 118
Railway Scheduling
Stream: Railway and Metro Transportation
Invited session
Chair: Marco Laumanns
Chair: Gabrio Curzio Caimi
1 - Generating Delivery Commitments from Train Operators’ Applications
Sara Gestrelius, Martin Aronsson, Malin Forsgren
Despite the traffic situation being unique for every day of operation,
a train should always run according to the train path finalised in the
yearly train plan in Sweden. We propose that only timings that are
important to the train operators, called delivery commitments, should
be finalised rather than entire train paths. Then the timetable could
be optimized for every unique day, while operators still get the information they need to provide their service. In this talk we present our
initial work on methods for generating delivery commitments from the
operators’ applications.
2 - Optimizing Railway System Performance by Kronecker Algebra
Mark Volcic
We present an optimization algorithm for railway systems in terms of
punctuality and energy consumption. By applying Kronecker Algebra,
a graph is created representing all train movements, where conflicts
can be easily found. The graph can be reduced to the relevant nodes
for train synchronization. The reduced graph is used to determine all
possible combinations of routes of all trains. The optimal driving strategy for each train is calculated and the best result will be taken as the
overall result. The algorithm is implemented in Ada and designed to
run on multi-core CPUs.
3 - Re-optimization of Rolling Stock Rotations
Thomas Schlechte, Ralf Borndörfer, Markus Reuther
The Rolling Stock Rotation Problem is to schedule rail vehicles in order to cover timetabled trips by a cost optimal set of vehicle rotations.
The problem integrates several facets of railway optimization, i.e., vehicle composition, maintenance constraints, and regularity aspects. In
industrial applications existing schedules often have to be re-optimized
to integrate timetable changes or construction sites. We present an integrated modeling and algorithmic approach for this task as well as computational results for industrial problem instances of DB Fernverkehr
AG.
4 - An Efficient Macroscopic Railway System Simulator
Jean Damay, Adrien Boillot
To assess the quality of an existing or hypothetic entire railway system,
we have devised and built a software tool that simulates at a macroscopic level the operational production of its trains over the network.
The main research contribution consists in taking into account several
types of railway resource constraints (rolling-stock / crew) and delays
(congestion, speed limitations, background noise. . . ) at specific and
relevant discrete events of the simulation. Service and production KPIs
are provided at the end of (and during) the simulation, and may be visualized over time and space.
TD-02
Tuesday, 14:00-15:30 - Room 111
Cross-docking and Warehouse
Operations Optimtization
Stream: Vehicle Routing
Invited session
Chair: Felix Brandt
114
1 - Lagrangean Relaxation for the Cross-dock Door Assignment Problem
Wael Nassief, Ivan Contreras, Rami Asad
In this talk we study a Cross-dock door assignment problem in which
the assignment of strip doors to incoming trucks and stack doors to
outgoing trucks is to be determined, with the objective of minimizing
the material handling cost. We present a strong mixed integer programming formulation that is embedded into a Lagrangean relaxation (LR)
that exploits the structure of the problem to obtain bounds on the optimal solution value. A primal heuristic is adopted at some iterations of
the LR to obtain high quality feasible solutions. Numerical results on
a set of benchmark instances are reported.
2 - A Comparison of Heuristics for the Order Batching
and the Picker Routing Problem in Manual Order
Picking Systems
André Scholz
Order picking is a warehouse function dealing with the retrieval of articles from their storage location in order to satisfy a given demand
specified by customer orders. When solving the order batching problem, a given set of customer orders has to be grouped into feasible
picking orders such that the total length of all picker tours is minimized. The length of each picker tour is determined by using a given
routing strategy. In this paper, it is investigated if the solution quality
can be improved by combining heuristics for the order batching problem with more complex routing strategies.
3 - A Multi-Temperature Truck Layout and Loading Problem
Felix Brandt, Anne Meyer
In this work we consider a vehicle layout and loading problem arising
in convenience product delivery to stores by using multi-temperature
vehicles with reconfigurable walls. We want to find a feasible wall
setup and loading pattern, which results in an unloading sequence with
a minimum number of reshuffles. We present a MIP model capturing
the layout constraints as well as the reshuffling aspects of the problem. We give an overview of our experiments using real world data
from our industrial partner PTV group. Our results show that there are
significant time savings achievable.
4 - A decision support system to optimize material handling at cross-docking terminals
Pierre Baptiste, Mohammad Yousef Maknoon, Miguel Anjos
The main challenge in cross-docking terminals is to reduce the material handling cost due to its intense operation on internal transshipment.
The material handling cost depends on products double handling and
traveling distance within doors. Previous scheduling models consider
a single factor as a measurement to optimize material handling decisions. In this study, we consider a holistic view and propose a mathematical programming framework to schedule cross-docking operations
with respect to its operational restrictions.
TD-03
Tuesday, 14:00-15:30 - Room 001
Airline Planning
Stream: Aviation
Invited session
Chair: Sakae Nagaoka
1 - Optimizing Time-Dependent Arrival Rates for Truck
Handling Operations at an Air Cargo Terminal
Axel Franz, Raik Stolletz
Truck arrivals at air cargo terminals are typically of time-dependent
and stochastic nature. Mechanisms such as terminal appointment systems aim at smoothing demand by shifting arrivals from peak to offpeak periods. Using a time-dependent queueing model, we provide
a methodology to evaluate and optimize truck arrival patterns at air
cargo terminals. Our optimization approach is based on the stationary backlog-carryover approach to analyze the system’s performance.
The model’s objective is to minimize total waiting times with the timedependent arrival rates as decision variables.
IFORS 2014 - Barcelona
2 - Effect of Pricing on Fleet Assignment with ItineraryBased Demands
Yasemin Kalafatoglu, Taner Bilgic
This research investigates the influence of itinerary pricing and network effects on fleeting decisions. It has been shown that itinerary
fares have a significant effect on choices of customers and thus on
itinerary demands. Using real data from a Turkish airline, the Itinerarybased Fleet Assignment Model (IFAM), an MIP model for fleet assignment that incorporates itinerary-level demands, is solved. Different
pricing scenarios based on the data are considered. Results show that
fleeting decisions and passenger spills are strongly related to itinerary
pricing.
3 - Pair-wise Resilience Index based on the Miss Distance and Time to the Closest Point of Approach
Sakae Nagaoka, Mark Brown
In airspace planning, safety indices which can be derived from aircraft
trajectory data are needed to assess airspace complexity. One such index, Resilience, reflects the air traffic management system capability to
respond to a safety significant event without increasing the likelihood
of more such events. The index does not use speed information, so ignores overtaking situations. Therefore we propose an index that takes
into account the miss distance and time to closest point of approach for
each pair of aircraft. This paper briefly gives the mathematical model
and some calculated examples.
TD-04
Tuesday, 14:00-15:30 - Room 119
Best Practices in Traffic Simulation
Stream: Traffic Flow Theory and Traffic Control
Invited session
Chair: Monica Menendez
TD-06
4 - Meaningful Quantification of Traffic and Pedestrian
Flow Model Accuracy
Femke van Wageningen-Kessels, Serge Hoogendoorn, Winnie
Daamen
Errors of road traffic or pedestrian flow models are quantified using
accuracy measures. Often used measures such as root mean square error or absolute percentage error of predicted velocities or densities are
not informative of the type of error. However, it is important to know,
for example, whether the overcrowding is predicted at the wrong time
or location or whether the actual traffic velocities show more discontinuities than the predicted ones. We propose accuracy measures that
quantify meaningful errors in (one-dimensional) road traffic and (twodimensional) pedestrian flows models.
TD-05
Tuesday, 14:00-15:30 - Room 002
Maritime Routing and Scheduling 1
Stream: Maritime Transportation
Invited session
Chair: Kjetil Fagerholt
1 - OR Applications in the Maritime Industry
Trond A. V. Johnsen
Over the last decades, the number of scientific publications addressing
use of OR to solve maritime planning problems has increased significantly. This again has in the recent years led to the development of
several decision support models and systems applied by the maritime
industry. In this paper, a set of OR applications in the maritime industry is presented. These examples cover different industry segments
and planning levels. Lessons learned from the industrial projects will
be presented, and critical factors for a successful industrial implementation discussed.
1 - Validation of Traffic Simulation Models: Are we Looking in the Right Direction?
Jordi Casas, Vincenzo Punzo, Marcello Montanino
2 - Development of Containership Services with Transshipments and Deadlines
Mico Kurilic
The process of checking to what extent the model replicates reality,
also referred as validation, is a remarkably challenging task in the traffic field, given the complexity and the highly stochastic nature of traffic. In this paper, statistical techniques applied in other fields are reviewed and compared to the current practice in traffic simulation. In
particular, the customary assumption of fixed demand in the designs of
experiment, usually adopted to run replications in traffic simulation, is
questioned. The paper analyses the implications of neglecting uncertainty in traffic demand.
Our model builds liner routes and schedules for cargo with deadlines
and transshipments. It tries to meet the deadlines and to minimize costs
of operating ships and cargo handling. It iteratively builds routes, deploys ships, and assigns cargo to the ships. Decisions about port calls
and cargo transshipments are based on sailing times, possible cargo
consolidations and deadlines. At every step, the model selects the
cargo with early deadline and with minimum incremental costs of assigning it to a scheduled ship. If needed, a new service is added to the
schedule until all cargo is assigned.
2 - HBS-compliant Capacity Analysis using VISSIM
Peter Vortisch
Simulation is often used as an alternative to the analytical methods of
highway capacity guidelines. But MOEs given in the guidelines and
produced by simulation are not always comparable. In our project,
we developed methods to use VISSIM in compliance with the HBS,
the German HCM. This includes parameter sets to calibrate VISSIM
to the capacities given in the HBS for standard network elements and
guidance how to extract MOEs from VISSIM that can be compared to
the MOEs the HBS is based on, especially how to measure capacity in
a HBS-compliant way.
3 - Sensitivity Analysis: A Valuable Tool in Traffic Model
Calibration
Monica Menendez, Qiao Ge, Biagio Ciuffo
Sensitivity Analysis (SA) can aid in finding the influential parameters
of a model. Here we develop an efficient SA method for traffic simulation models, especially those that are high dimensional and computationally expensive. Its application is illustrated with a case study.
Results show that the accuracy of this method is similar to that of the
variance-based SA in identifying the influential parameters and their
ranks, but the computation cost is much lower. Hence, it is recommended as a standard SA method for traffic simulation models and
other complex models in the scientific community.
3 - A Decision Support Tool for Liner Shipping Network
Design
Berit Dangaard Brouer, Guy Desaulniers
Liner shipping companies adapt to new market situations and fleet decisions by redesigning and adjusting existing services. We present a
decision support tool, which is able to incrementally adjust an existing network to new market situations. The underlying algorithm is
a matheuristic using an integer program to define insertions and removals of port calls from designated services to improve performance
and cost of the overall network. We present a case study of the decision support tool optimizing on a designated subset of services within
a global liner shipping network.
TD-06
Tuesday, 14:00-15:30 - Room 211
Health Care Operations Management
Stream: Logistics in Health Care
Invited session
Chair: Katja Schimmelpfeng
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IFORS 2014 - Barcelona
1 - A Hierarchical Facility Layout Planning Approach for
Large and Complex Hospitals
Stefan Helber
In large and complex hospitals with a high number of departments,
transportation processes for patients, personnel, and goods can consume substantial resources and hence induce substantial costs. The
allocation of the different departments and wards in the possibly multiple connected hospital buildings determines those costs. Based on the
analysis of a very large and complex University Hospital in Hannover,
Germany, we develop a hierarchical layout planning approach to propose locations for departments and wards. We describe the models and
report numerical results.
2 - A Flexible Approach for Strategic Master Surgery
Scheduling
Andreas Fügener, Jens Brunner
This study discusses a master surgery scheduling approach that maximizes hospital revenues under consideration of downstream resources,
such as intensive care units or general patient wards. Demand of these
resources is modelled by a stochastic patient path model. We discuss
models with both fixed and variable resources to determine efficient
allocation of capacity. Our approach is tested with real life data from a
German university hospital and manages to achieve significant revenue
increases.
3 - Clustering Clinical Departments for Wards
Achieve a Prespecified Blocking Probability
Johann Hurink, Theresia van Essen
to
When the number of available beds in a hospital is limited and fixed,
it can be beneficial to cluster several clinical departments such that the
probability of not being able to admit a patient is acceptably small. The
clusters are then assigned to the available wards such that enough beds
are available to guarantee a blocking probability below a prespecified
value. We give an exact formulation of the problem and introduce two
heuristic solution methods. Furthermore, we present some computational results based on data of a Dutch hospital.
4 - Master Surgical Scheduling Considering Stochastic
Surgery Durations
Alexander Kressner, Katja Schimmelpfeng
Operating rooms (OR) are a hospital’s most important and expensive
resources. Thus hospitals strive to operate ORs at high utilization without jeopardizing patient service. In this context, one of the main challenges is to cope with the natural uncertainty in surgery durations. We
consider the problem of scheduling types of elective procedures to ORs
over a mid-term planning horizon (Master Surgical Scheduling). The
resulting OR-planning model is stochastic and allows to control overtime. We present different linearization approaches of the non-linear
base model and further extensions.
TD-07
Tuesday, 14:00-15:30 - Room 003
Challenges in Electricity Systems
Stream: Equilibrium Problems in Energy
Invited session
Chair: Christoph Weber
2 - The Impact of Disequilibria in Power Markets
Thomas Kallabis, Christoph Weber
Frequently, energy market models focus on the analysis of equilibria and equilibrium development paths. But the history of competitive electricity markets in Europe is more resembling to a sequence of
booms and busts - with currently a bust period. A key reason are the
long lead times for construction. By investigating the impacts of deviations from an (anticipated) equilibrium, the relevance of various risk
factors for profitability is highlighted. This will contribute to improve
investment decision making under uncertainty.
3 - Equilibrium Pricing of Reserve Power
Christoph Weber, Lenja Niesen
With increasing shares of renewable generation, reserve power markets
are expected to gain in importance. Competitively organized markets
like in Germany are characterized by high prices with considerable
fluctuations. Analytical investigations in a partial equilibrium framework reveal however that capacity prices should be rather low if reserve power is auctioned on an hourly basis. Numerical analyses are
then used to quantify in a large European electricity market model the
impact of different specifications of the reserve power products.
4 - Production Intermittence in Spot Markets
Olivier Massol, Albert Banal Estanol, Augusto Rupérez
Micola
This paper analyses the influence of production intermittence on spot
markets. We use both game theory and an agent-based simulation approach derived from the Camerer and Ho (1999) behavioral model.
Controlling for costs, we find that intermittent technologies yield lower
prices when incumbents have individual market power, but higher
when they do not have it. This happens when firms are risk-neutral
and risk-averse, and also under different intermittence and ownership
configurations. Replacing high-cost assets with low-cost ones results
in higher prices than letting them co-exist.
TD-08
Tuesday, 14:00-15:30 - Room 120
Green Design and Risk Pooling
Stream: Energy Economics, Environmental Management and Multicriteria Decision Making
Contributed session
Chair: Andreas Welling
1 - The Timing of Green Investments under Regime
Switching and Ambiguity
Andreas Welling, Elmar Lukas, Stefan Kupfer
The economic success of green investments does not only depend on
the uncertain economic development but also on regime switches in
the relevant legislation. As a result of political decision-making the
latter are assumed to be rather ambiguous than uncertain. We develop
a real options model that takes into account economic uncertainty as
well as political ambiguity. We calculate the option value of the green
investment and derive the optimal investment-timing strategy. Furthermore, we analyze the sole and the combined influence of economic
uncertainty and political ambiguity on these topics.
1 - Capacity Markets in Europe — Assessing the Benefits of Coordinated Mechanisms versus National Appro
Michael Bucksteeg, Christoph Weber
2 - Green Investment Decisions in Battery Technology
for Electric Vehicles: The Role of Uncertainty in the
Product Life Cycle
Stefan Kupfer, Karsten Kieckhäfer, Elmar Lukas, Thomas
Spengler
In Europe, there is an on-going debate about the introduction of national vs. internationally coordinated capacity mechanisms We therefore model the impacts of capacity markets in Europe with different
levels of coordination between the considered countries. A stochastic
partial equilibrium model of the electricity market is used for a quantification of the economic effects. Beforehand we calculate the capacity requirements with a stochastic convolution approach. Thereby, we
assume that the probability of a capacity shortage may not exceed a
pre-defined security level.
Electric vehicles play a decisive role in current strategies to green the
automotive industry. Since the battery accounts for the highest share of
value creation in electric vehicles, make or buy decisions for a specific
battery technology are crucial investment decisions for car manufacturers. This paper studies the effect of technology and market uncertainty
on the investment decision of car manufacturers in battery technology.
Thereby we take into account that the adoption of a new but uncertain
technology typically follows a product life cycle commonly neglected
in the finance literature.
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IFORS 2014 - Barcelona
3 - Discriminated Fee based Incentive Mechanisms for
Green Design Products
I-Hsuan Hong
Green design products can enhance the reclaimed value of end-of-life
products. This paper examines how different advanced recycling fees
affect a manufacturer’s green design of products. We apply the Stackelberg model to determe the optimally discriminated advanced recycling
fees in the perspective of the government. This study investigates two
different mechanism designs to deduce manufacturers designing green
products: incentives to manufacturers or subsidies to consumers. Finally, we compare two mechanisms and discuss the pros and cons of
these two mechanisms.
TD-10
4 - A Spot-Forward Model for Electricity Prices
Michael Schürle, Florentina Paraschiv
We propose a novel regime-switching approach for modeling electricity spot prices that takes into account the relation between spot and
forward prices. Additionally the model is able to reproduce spikes
and negative prices. Market prices are based on an observed forward
curve. We distinguish between a base regime and an upper as well as a
lower spike regime. The model parameters are calibrated using historical hourly price forward curves for EEX Phelix and the dynamics of
hourly spot prices. The model is compared with common time series
approaches like ARMA and GARCH.
4 - Risk Pooling in Commercial Returns by Managing
Product Return Period
Muhammad Naiman Jalil, Sadeeqa Shahzad
Retailers typically specify product return period as per return policy.
The impact of return period length on product return volumes and their
variability is not understood. We analytically show that increasing return period length results in reducing variability of product returns—
commonly known as risk pooling. Risk pooling in product returns is
structurally different from existing risk pooling examples in literature.
Risk pooling in product returns by increasing return period length occurs by prompting a behavioral change in the underlying stochastic
sales and return process.
TD-09
TD-10
Tuesday, 14:00-15:30 - Room 122
Decision Support Models for the Energy
Industry III
Stream: Optimization Models and Algorithms in Energy
Industry
Invited session
Chair: F.-Javier Heredia
Tuesday, 14:00-15:30 - Room 121
Modeling and Optimizing Electricity
Markets
Stream: Technical and Financial Aspects of Energy
Problems
Invited session
Chair: Florentina Paraschiv
1 - Medium-Term Planning for Thermal Electricity Production
Florentina Paraschiv, Raimund Kovacevic
We present a mid-term planning model for thermal power generation which is based on multistage stochastic optimization and involves
stochastic electricity spot prices, a mixture of fuels with stochastic
prices, the effect of CO2 emission prices and various types of further
operating costs. We solve a 1-year planning problem for a fictitious
configuration of thermal units, producing against the markets. We use
the implemented model to demonstrate the effect of CO2 prices on cumulated emissions and to apply the indifference pricing principle to
simple electricity delivery contracts.
2 - Forecasting Electrical Demand in Commercial Buildings through Energy Performance Indicators using
Time Series Methods.
Stamatios Paterakis, Evangelos Spiliotis, Vasilis
Assimakopoulos
In this study, a methodology for predicting electrical consumption
in commercial buildings is proposed. Initially, Time Series forecasting methods are applied on data from sub-sector energy consumption
groups of the buildings. In addition, time series of key Energy Performance Indicators are constructed per sector and used as input data for
the above methods. In each case, the optimal forecasting model is selected and combinations of these methods are examined for maximized
accuracy. Finally, bottom-up, top-down and optimal hierarchical methods are used to obtain the final forecasts.
3 - Electricity Swing Option Pricing by Bilevel Optimzation
Raimund Kovacevic, Georg Pflug
Swing options are an important type of flexible energy delivery contracts. Due to nonstorability and imcompleteness of eletricity markets, electricity swing options are difficult to price by purely financial
approaches. We formulate the pricing problem as a bilevel decision
problem (Stackelberg game) and present related optimality conditions
and solution algorithms.
1 - Stochastic Optimal Generation Bid to Electricity Markets with Emission Risk Constraints
F.-Javier Heredia, Julián Cifuentes Rubiano, Cristina
Corchero
This work investigates the influence of the emission reduction rules
in the optimal generation bidding strategy to the day-ahead electricity market through the new concept of Conditional Emission at Risk
(CEaR). A stochastic programming model is used to determinate the
optimal generation bid to the wholesale electricity market that maximizes the long-run profits of the utility abiding by the Iberian Electricity Market and the environmental restrictions set by the Spanish
National Emissions Reduction Plan.
2 - Modeling Renewable Generation Sources
Medium-Term Electricity Generation Planning
Laura Marí, Narcis Nabona
for
Medium-term generation planning is an essential tool for Generation
Companies participating in liberalized electricity markets as it permits
to predict revenues and to plan next year’s fuel procurements. A new
model for non-dispatchable renewables, such as wind power and solar photovoltaic generation, is proposed for generation planning using probabilistic methods for load matching taking into account forced
outage rates. A stochastic programming framework using quasi-Monte
Carlo techniques is developed to model the randomness of wind and of
solar photovoltaic power, and of hydro inflows.
3 - Mixed-Integer Linear Programming Models to Solve
Optimization Problems of Radial Electrical Distribution Systems
Marcos J. Rider, Rogério dos Reis Gonçalves
This paper presents mixed-integer linear programming (MILP) models
to solve: a) operation planning of radial electrical distribution systems
(REDS), considering the presence of distributed generators and devices
voltage regulators (DVR); b) optimal allocation of DVR in REDS; and
c) short-term expansion planning of REDS. All proposed MILP models
are equivalent to their respective original models. The proposed models have been implemented in AMPL and solved using the CPLEX.
Several test systems were used to show the accuracy of the mathematical models and efficiency of the proposed solution.
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IFORS 2014 - Barcelona
4 - Solving Natural-Gas Infrastructure Planning Models
with the Branch-and-Fix Coordination Algorithm
Adela Pages Bernaus, Gerardo Perez Valdes, Asgeir
Tomasgard
Assessing the expansion of a natural-gas infrastructure can be modeled as a large-scale mixed-integer programming (MIP) problem. To
ensure robust and flexible decisions, such model must consider the unavoidable uncertainty of some of the parameters making it a large-scale
multi-stage stochastic MIP problem. Decomposition techniques such
as the parallelized branch-and-fix coordination algorithm are required
to solve realistic problems. In this talk, we will present the infrastructure problem together with the solution algorithm.
TD-11
Tuesday, 14:00-15:30 - Room 113
Various New Advances in Combinatorial
Optimization
Stream: Combinatorial Optimization
Invited session
Chair: Gerhard-Wilhelm Weber
Chair: José Paixão
1 - A Very Fast Implementation of the Work Function Algorithm based on Network Flows and Flow Cost Reduction
Robert Manger, Tomislav Rudec
We propose a new implementation of the work function algorithm
(WFA) for solving the on-line k-server problem, which is based on
a simple network flow model and on flow cost reduction. Thanks to
a suitable parameter, our new implementation can achieve tradeoff between accuracy and speed, i.e. it can be either exact or approximate.
According to the presented experiments, the exact version already assures fast execution, while the approximate version can be an order of
magnitude faster. At the same time, the approximate version can still
closely mimic the original WFA in terms of serving costs.
2 - Schedules for Marketing Products with Negative Externalities
Xujin Chen, Zhigang Cao, Changjun Wang
With the fast development of social network services, network marketing of products with externalities has been attracting more and more
attention from both academia and business. We design polynomial
time algorithms that find marketing schedules for products with negative externalities. The goals are two-fold: maximizing the product sale
and ensuring consumer regret-free decisions. Our algorithms achieve
satisfactory performance guarantees for both profit maximization and
regret-proofness. Our work is the first attempt to address these marketing problems from an algorithmic point of view.
3 - Method of Pattern Analysis: New Algorithms
Alexey Myachin
Research is devoted to the aggregated analysis of data in order to obtain high-quality results that give the most extensive view of the investigated objects, their structural components and behavior in time.
New analysis algorithms are proposed: a linear pattern classification,
ordinal-invariant and diffusion-invariant pattern clustering. Paper describes the main advantages of the proposed methodology to the classical methods of analysis. The proposed methodology is considered by
the data of science, education and innovation activity in regions of the
Russian Federation.
4 - Vehicle Routing for Solid Waste Collection: A Hybrid
Metaheuristic Approach
Antonio Chaves, Eliseu Araújo
The aim of this paper is to present an heuristic for the periodic vehicle routing problem applied to solid waste collection. The solution is
a one-week plan of daily routes for the transport of waste from containers to facilities, taking into account the frequency of collection,
the road network and the resources available. We present a hybrid
method called Clustering Search (CS), that combines metaheuristics
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and heuristics intensifying the search only in promising areas. A realworld case supported this study. Computational tests show that CS has
an improved performance against other methods.
TD-12
Tuesday, 14:00-15:30 - Room 004
Difference Equations and Discrete
Dynamical Systems
Stream: Continuous and Discontinuous Dynamical
Systems
Invited session
Chair: Ozan Özkan
1 - The Dynamics of a Difference Equation
İbrahim Yalçınkaya
Difference equations appear naturally as discrete analogues and as
numerical solutions of differential equations having applications in
physics,biology, economy, etc. Recenlty there has been an increasing
interest in the study of global behavior of rational difference equations.
Although difference equations are relatively simple in form, it is extremely difficult to understand thoroughly the global behavior of their
solutions. In this paper, we investigate the global behavior of a difference equation with non-negative parameters and initial conditions.
2 - On a System of Difference Equations
Abdullah Selçuk Kurbanlı
Recently, there has been great interest in studying difference equation
systems. One of the reasons for this is a necessity for some techniques
which can be used in investigating equations arising in mathematical
models describing real life situations in population biology, economic,
probability theory, genetics, psychology etc. In this paper, we investigate the behavior of the solutions of the difference equations systems.
3 - Solving Fractional Vibrational Problem Using Generalized Differential Transform Method
Ummugulsum Cansu, Ozan Özkan, Suat Kurt
In this paper we propose approximate analytical solutions for time fractional vibration equation by using generalized differential transform
method. The solution of the equation is obtained in the form of convergent series. The fractional derivatives are described in the Caputo
sense. The numerical results show that the approach is easy to implement to fractional vibration equations without any restrictive assumptions. Hence, by this method, the numerical computations are reduced.
Finally an examples is solved to illustrate the accurateness and effectiveness of the method.
TD-13
Tuesday, 14:00-15:30 - Room 123
Scheduling and Logistics
Stream: Scheduling
Invited session
Chair: Michal Penn
1 - The Routing of Sea Buses via Integer Linear Programming: The Case of Bosphorus
Tekiner Kaya
In this paper, since the sea buses’ current schedules in Bosphorus/Turkey were developed through past experiences, the main objective of this study was to prepare a model to minimize cost and the number of sea buses performing in Bosphorus. Thus, in order to manage
the current order-demand pairs rationally, the problem is formulated
as Vehicle Routing Problem with Simultaneous Pick-Ups Deliveries
and a mathematical model consisting 65326 variables and 65847 constraints were developed. Results showed that number of used sea buses
reduced by %5,9 and sea buses usage ratio improved by %5,18.
IFORS 2014 - Barcelona
2 - Two approaches of scheduling problems in a distribution center with two cranes and interference constraint
Gabriela Naves Maschietto, Martin Gomez Ravetti, De Souza
Mauricio
This work deals with the scheduling of jobs on two machines that
may interfere each other. This problem often appears at logistic centers, such as warehouses and stockyards. Machinery as cranes and
reclaimers, sharing the same rail may interfere in each other jobs. This
work is based on a real case at a distribution center of steel coils, where
two cranes on the same trail must load a sequence of trucks. We model
the problem as a parallel scheduling problem and as a single multiprocessor. Mathematical programming models are proposed and tested
for different organization policies of the coils.
3 - Energy efficient scheduling on a Single Machine
Michal Penn, Tal Raviv
Consider the problem of scheduling jobs on a single machine over T
units of time. The time horizon [0,T] is divided into electricity tariff intervals of different lengths and tariffs. Each job delivered from the system yields a revenue and the energy cost of processing it is calculated
proportionally to the lengths times the electricity tariffs the processing extends over. We consider two problems: Decide on the number
of jobs to be produced and their schedule to maximize the total profit
(revenue net energy cost).
4 - Scheduling of Identical Parts in Robotic Flow-shop
for Different Cell Layouts
Florence Thiard, Nicolas Catusse, Nadia Brauner
Modeling modern manufacturing systems require to take into account
transportation resources. Robotic cells consists in a flow-shop setup
where transportation of the parts between machines is handled by a
robot. We consider cyclic production of identical parts and optimization of the cell’s throughput. Most results in the literature concern
linear cells and one unit-production cycles; few studies consider other
layouts. We study the extension of classical results to circular layout,
where the cell’s input and output buffers are at the same position.
TD-15
3 - Measuring the Impact of Energy on Industry through:
A DEA Approch
Nadia Kpondjo, Frederic Lantz, Anna Creti
In this paper, we solve the question of productive performance of DMU
(Decision Making Unit) of the primary aluminium industry and analyze the impact of external factors such as energy supply on the change
of these performances. Our methodology is based on a DEA approach.
The key points that make up our contributions are: First: applying
recent developments in DEA; Second: analyzing the change in performance of DMU over time; Third: analyzing the impact of external
factors on conditional efficiency. We expect a disparity in the efficiencies of DMU with their technology and location.
4 - Water Treatment Plants Efficiency in México
M. Violeta Vargas-Parra, Francisco Vargas, Noemi Haro, Luis
Rentería Guerrero
As energy prices increase, environmental concerns highlight the need
to improve processes. The aim of this study is to measure the performance of water treatment plants during 2004-2010. The analysis
encompasses all plants in the 32 states of Mexico. An input-oriented
DEA model for determining an efficient frontier and derive relative positions of water treatment plants over the states, is applied. A ranking
in best practices is obtained from this research, evidencing improvement opportunities oriented to cost reduction and environmental improvement throughout resource consumption reduction.
TD-15
Tuesday, 14:00-15:30 - Room 125
Strategic Consumer Behavior, Pricing and
Customer Choice
Stream: Revenue Management II
Invited session
Chair: Sumit Kunnumkal
TD-14
Tuesday, 14:00-15:30 - Room 124
DEA in Energy and Water services
Stream: DEA Applications
Contributed session
Chair: M. Violeta Vargas-Parra
1 - Evaluation of the Brazilian Electricity Distribution using Network DEA
Lidia Angulo-Meza, Placido Moreno, João Carlos Soares de
Mello
Worldwide, DEA has been used to assess the electricity distributors’
efficiency. Operational expenditures (OPEX) is the most used input, while energy distributed and number of consumers are the outputs. However, some papers use the network length as a second input,
whereas research conducted in Brazil considers the network length as
an output. We propose a new 2-stage model in which OPEX is the
only input, energy distributed and number of consumers as outputs,
and network length is the intermediate variable. Since OPEX is an
input to both stages, we use a shared-input Network DEA model.
2 - Monitoring Efficiency and Productivity of Promoters
in Wind Energy Sector
Clara Vaz, Ângela Ferreira
A DEA framework is proposed to explore the differences in performance of a set of wind farms, which involves two main promoters in
the Portuguese wind energy sector. The study investigates the efficiency of the promoters in maximizing the energy produced from the
physical resources and the wind velocity available in each farm. The
overall performance of the two promoters is analyzed by comparing
their differences in terms of the efficiency spread and productivity between their best-practice frontiers. Results may be used to support
decision makers in the establishment of regulation policies.
1 - Quantity Competition in the Presence of Strategic
Consumers
Yuri Levin, Mikhail Nediak, Andrei Bazhanov
Oligopolistic retailers sell an undifferentiated limited-lifetime product
to strategic consumers. A manufacturer sets the first-period (full) price,
while the second-period (clearance) price is determined by Cournot
equilibrium. Symmetric pure-strategy equilibria may result in no sales
in the periods 1 or 2 (Cournot outcome versus collusion), and sales
in both periods with the clearance price above or at the salvage value.
Higher strategic behavior can be a benefit for retailers but hurt consumers, higher competition may harm local economy, and strategic
behavior may insure against oversupply.
2 - Dynamic Pricing with Reference Price Effects under
Heterogeneous Customer Arrivals
Zizhuo Wang
We consider a monopoly selling a single product over a certain horizon. Customers belong to different groups with different arrival patterns. For each customer, his demand depends on the price in this
period, as well as the prices he observed in the past. Contrary to the
prior literature on pricing with reference effect, we show that under the
above assumptions, the optimal price path does not necessarily converge. Instead, it asymptotically converges to a cyclic pricing strategy
with provable cycle lengths. Other properties of the optimal prices as
well as numerical tests are studied.
3 - New Compact Linear Programming Formulations for
Choice Network Revenue Management
Sumit Kunnumkal, Kalyan Talluri
We consider the network RM problem with customer choice and show
that the affine relaxation is NP-complete even for a single-segment
MNL model. Nevertheless, by analyzing the affine relaxation we derive new compact linear programs that approximates the dynamic programming value function better than choice deterministic LP, provably
between the choice deterministic LP value and the affine relaxation,
and often coming close to the latter in our numerical experiments.
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TD-16
IFORS 2014 - Barcelona
4 - Pricing Strategies in a Fairness-sensitive Market
Steven Shugan, Jihwan Moon
Overwhelming empirical evidence finds: (1) consumers consider fairness but (2) competitive equilibria occur without considering fairness. Consistent with both findings, we develop pricing strategies
with fairness-sensitive consumers. Ostensibly unfair actions are information events that (1) hurt consumers who view them as unfair and
(2) deviate from the market norm. We find that adverse cost shocks
cause the imposition of unfair fees regardless of whether consumers
are fairness-sensitive. However, the transition to that equilibrium depends on whether consumers are fairness.
TD-16
Tuesday, 14:00-15:30 - Room 127
Machine Learning Applications in Web
Technology
Stream: Intelligent Optimization in Machine Learning
and Data Analysis
Invited session
Chair: Takashi Onoda
1 - Composition of Web Services for Scaling Using Finite States Machines
Nadia Halfoune, Khaled Sellami
The main goal of our work is to ensure a precise composition of Web
services. We use business protocols to model the exchanges between
the different entities (supplier, consumer, intermediaries). Our work
is based on the technology of Web services and the finite state machines to define our approach of services composition. In this work, we
present an improvement of an existing algorithm of consumer-server
composition. Then, we develop two new algorithms of composition:
series composition and parallel composition of Web services.
2 - Big Data - Classification and Optimization Algorithms
Stanislav Sopko
The main focus of paper is to study the effectiveness of different optimization algorithms in an area called big data. The data will be examined using statistical and data mining methods. Optimization takes
place both in terms of optimization of classification process, as well
as optimization of the work process with the results. Classification and
optimization algorithms in this work will be based on a combination of
traditional approaches in this sector, but also supported by a series of
new approaches based on the theory of artificial intelligence and neural
networks.
3 - Automated Radial Basis Function Neural Network
Construction for Malicious URL Classification
Dirk Snyman, Tiny Du Toit, Hennie Kruger
Phishing attacks which employ URLs pointing to fraudulent resources
are directed at end users in order to steal sensitive or identifying information. Attackers exploit many weaknesses of current methods used
to detect malicious URLs. In this study malicious URLs are identified
by a new automated RBF neural network construction algorithm. This
technique uses an in-sample model selection criterion to determine the
best neural network architecture. Example URLs from the Open Directory and Phishtank are utilized to train and test the neural network.
Results obtained will be presented.
4 - Semantic Requests in Web Services Search
Abdelmalek Boudries, Amad Mourad, Rabah Kassa
The semantic Web has attracted the attention of many searchers since
these last years. It concerns to arrive to an intelligent Web, were the
information would be no more stored but translated by computers in order to answer to the users’ needs. The semantic Web Services (WS) are
situated at the convergence of two important research domains which
concerns the internet technology, as the semantic Web and the WS. In
this work, we have studied some semantic annotations approaches in
the WS contest and we have proposed an annotation method and an
algorithm of construction of semantic queries.
TD-17
Tuesday, 14:00-15:30 - Room 005
Interior Point Methods for Large-Scale
Optimization
Stream: Interior Point Methods and Conic Optimization
Invited session
Chair: Miguel Anjos
1 - Inexact Search Directions and Matrix-free Interior
Point Method for Quantum Information Problems
Jacek Gondzio
Many large-scale optimization problems cannot be solved with methods which rely on exact directions obtained by factoring matrices. I
will argue that second-order methods (including interior point algorithms) which use inexact directions computed by iterative techniques
and run in a matrix-free regime offer an attractive alternative. I will
address a theoretical issue of how much of inexactness is allowed in
directions and support the findings with computational experience of
solving some very large optimization problems which arise in quantum
mechanics.
2 - BlockIP: An Interior-Point Solver for Block Angular
Problems
Jordi Castro, Xavi Jimenez
A new interior-point solver for block angular structures is introduced.
It implements an approach based on the solution of normal equations by Cholesky factorizations and preconditioned conjugate gradients (PCG). Some of its features are: it is written in C++, allowing
several input formats (C++ interface, extended MPS, AMPL SML);
it solves separable convex problems (linear, quadratic and nonlinear);
both proximal point and quadratic regularizations are included; normal
equation are solved by either Cholesky or Cholesky and PCG. Computational results with some problems will be reported.
3 - Finding a Basis for the Splitting Preconditioner on
Interior Point Methods
Aurelio Oliveira, Porfirio Suñagua-Salgado
The splitting preconditioner works well on linear systems arising from
interior point methods near a LP solution when the matrices are highly
ill-conditioned. It needs a basis computed by a sophisticated rectangular LU factorization. We propose a new approach to find a better
conditioned basis computing the standard rectangular LU factorization
with partial pivoting of the transpose scaled constraint matrix. Additionally, a penalty parameter is applied in the interior point method
to reduce ill-conditioning. Numerical results reveal the new approach
better performance on large-scale problems.
4 - Using Hybrid Preconditioners in an IPM for Large
Block-Angular Problems
Silvana Bocanegra, Jordi Castro, Aurelio Oliveira
The main computational burden of interior point methods (IPMs) is the
solution of linear systems. An IPM for block-angular problems solves
these systems by combining Cholesky and a conjugate gradient based
on a power series preconditioner for block and linking constraints, respectively. This preconditioner may become inefficient in the last IP
iterations. A hybrid approach is proposed: the power series preconditioner is used at the first iterations and a splitting preconditioner based
on LU is applied in the last ones. This approach improves the performance and robustness of the IPM.
TD-18
Tuesday, 14:00-15:30 - Room 112
New Trends in Evolutionary Multiobjective
Optimization
Stream: Multiobjective Optimization - Theory, Methods
and Applications
Invited session
Chair: Mariano Luque
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IFORS 2014 - Barcelona
TD-20
1 - An Interactive Evolutionary Multiobjective Optimization Method based on the WASF-GA Algorithm
Mariano Luque, Kaisa Miettinen, Ana Belen Ruiz, Rubén
Saborido Infantes
products they will purchase. We focus on two-customer segments and
study the optimal pricing problem and the problem of adding or dropping products from the line. We also present numeric results based on
our algorithms.
We describe an interactive evolutionary algorithm to solve multiobjective optimization problems. It is based on a preference-based evolutionary multiobjective optimization algorithm called WASF-GA. In
the interactive version of WASF-GA to be introduced, at each iteration,
the decision maker can provide desirable aspiration values and several
nondominated objective vectors are generated based on them. They
are filtered and shown to the decision maker who has also the option
of expressing minimally acceptable values for each objective function
in the form of reservation values.
2 - A Comparison of Different Types of Probit Models for
Conjoint Segmentation
Friederike Paetz, Winfried Steiner
2 - A Hybrid GA and ACS Preemptive Multiobjective
Model to Approach a Hydroelectric Dynamic Dispatch
Regiane Silva de Barros, Jéssica Pillon Torralba Fernandes,
João Paulo Estrócio, Ieda Hidalgo, Paulo Correia
This paper approaches a hydroelectric dynamic dispatch with hybrid
Genetic Algorithm (GA) and Ant Colony System (ACS) tools in a
preemptive multiobjective model. It seeks to maximize the plant efficiency and to minimize the units’ start-ups and shut-downs. In the
first priority, GA solves the 24 hourly static dispatches to provide a set
of good solutions (optimal or sub-optimal) in terms of the efficiency.
In the second priority, ACS minimizes the shut-downs and start-ups to
find optimal Pareto diary paths. This model was successfully applied
to a real plant, whose results are discussed.
3 - A Metamodel Assisted NSGA-II Algorithm for Multiobjective Optimization
Karthik Sindhya
Industrial multiobjective optimization problems often involve objective and constraint functions, which are very computationally expensive to evaluate. Evolutionary multiobjective optimization algorithms
like NSGA-II are often used to handle multiobjective optimization
problems, are not suitable for computationally expensive problems as
they require calculation of objective and constraint functions of a population of solutions over a large number of generations. In this paper
we augment NSGA-II algorithm with a metamodel in order to be better
able to handle computationally expensive problems.
4 - Solving Two-Stage Stochastic Integer Linear Programming with Multiple Objective
Salima Amrouche
In this paper, we present a new method of multiobjective two-stage
stochastic integer linear programming MOSILP cosidering the parameters of linear objective functions and some linear constraints as discrete random variables with known probability distribution. To solve
the stated problem, first we remove the randomness of the problem
and formulate an equivalent deterministic multiobjective integer linear
programming model MOILP. Then an optimal solution of LP whose
objective is a positive combination of the criteria, with respect to the
first-stage constraints and existing feasibility.
Finite Mixture (FM) Choice Models so far do not account for dependencies between alternatives. We propose a new FM-MNP model that
considers such different pairwise similarities. To analyze whether the
independence assumption is as restrictive as it seems, we contrast the
FM-MNP model to its nested version, the FM-IP model, which assumes independence. In a simulation study we compare these models
w.r.t. parameter recovery, fit and prediction. While incorporating dependencies pays off for parameter recovery and unpenalized model fit,
the models are comparable with regard to forecasting accuracy.
3 - Association Rules Based on Tree-Building Technique in Market Basket Analysis
Marijana Zekic-Susac, Adela Has
As a data mining method, association rules have been used in marketing and retail management to reveal which products are frequently purchased together or sequentially by the same customer. This paper investigates the efficiency of association rules based on the tree-building
technique in case with a large number of items. A real dataset was collected from a major Croatian supermarket, and association rules generated with two different item-grouping strategies were analyzed. The
selection of interesting rules is then performed by integrating objective
measures and expert knowledge.
4 - Optimal Diapers Production Using Simplex Method
Zaid Montenegro, Jose Luis Chavez - Hurtado, Humberto
Palos Delgadillo
SCA is a leading global hygiene and forest products company that develops and produces sustainable personal care, tissue and forest products. In Guadalajara, Mexico, there is an area of the company dedicated to produce baby care products, focusing especially in producing
diapers. This work shows the results of a consultancy made for SCA
Guadalajara which aimed to optimize production of diapers for different brands in order to maximize company profits by taking into account
different constrains (product demand, available resources, production
capacity, etc.) and solved using simplex method.
TD-20
Tuesday, 14:00-15:30 - Room 129
Power System Design and Operation
Stream: Stochastic Optimization in Energy
Invited session
Chair: Asgeir Tomasgard
TD-19
Tuesday, 14:00-15:30 - Room 128
Retail Demand Planning
Stream: Demand and Supply Planning in Consumer
Goods and Retailing
Invited session
Chair: Winfried Steiner
1 - Product Line Pricing and Design for Aspirational
Products with Multiple Customer Segments
Udatta Palekar
We consider the problem of determining the optimal pricing for a
product line where the products are vertically differentiated and customers choose the best product that fits within their budget. Customers
are grouped into segments based on minimum quality requirements of
1 - Wind Power, Congestion Management and the Variability of Power Prices
Mette Bjørndal, Jonas Andersson, Endre Bjørndal, Linda Rud
New interconnectors and added intermittent generation capacity will
expose the Nordic market to more variability. While price variations
from uncorrelated wind power production may cancel out, variability
may be enhanced due to the network topology and capacity. This has
implications for congestion management. In a model of the Nordic
electricity market and its transmission system, we study implications
of spot market volatility given various scenarios of wind power and
transmission investment, using different methods of congestion management.
2 - Congestion Management by Dispatch or Redispatch: Flexibility Costs and Stochastic Effects
Endre Bjørndal, Mette Bjørndal, Asgeir Tomasgard, Kjetil
Midthun
121
TD-21
IFORS 2014 - Barcelona
Several European electricity spot markets use simplified congestion
management methods such as uniform or zonal pricing, and redispatch is necessary to achieve a feasible flow. Bjørndal et al. (2013)
discussed the effects of flexibility costs in a deterministic setting. We
extend their model to include stochastic effects, e.g., caused by intermittent renewables, and we apply our model to the Nordic power market. We discuss the combined effect of uncertainty and flexibility costs
for different choices with respect to congestion management method.
3 - Reliability in the Power System Modeled in a MultiStage Stochastic Mixed Integer Programming Model
Michael Pascal Simonsen Nielsen
Contributions from this article are that it takes the characteristics of
the power system into account at different stages, which gives a more
realistic presentation of the welfare aspects to be gained by an optimal operation/ dispatch of the power system. This article is utilizing
a Multi-Stage Stochastic Mixed Integer Programming Model that handles uncertainty in a flexible and practical way. The method applied
relies on state-of-the-art modeling within this field, but the method applied in this article is extended by using decomposition.
4 - Estimation of Stochastic Frontier Cost Efficiency for
Companies in the Electricity Distribution Sector in
Brazil
João Silveira, Julio Siluk, Simone Naimer
This paper presents the estimation of a cost efficiency stochastic frontier panel for a sample of the Brazilian electricity distribution sector,
using in the main function explanatory variables of average operational
cost of the companies, such as average salary, cost of energy purchased
and volume of energy supplied. In the equation of inefficiency is tested
the average duration of the supply interruption per year in hours (DEC)
and the average frequency of the supply interruption per year (FEC),
as well as the productivity in MWhs sold by employee.
The company wants to open new IT departments in different locations.
The study aims to decide the optimal locations of the new IT departments, to assign the number of workers for each and determine the
work hour schedule of the workers. Discussions with the client about
implementing the results will also be covered.
4 - A Predictive Analytics Approach for Demand Forecasting in the Process Industry
Benjamin Priese, Robert Blackburn, Kristina Lurz, Rainer
Göb, Inga-Lena Darkow
Anticipating demand changes is critical in the process industry with
high capacity utilization. The developed solution is based on a new
predictive analytics approach and sophisticated information technology, which allows combining company data and economic information
specifically matched to the market environment of product segments.
The approach systematically selects the best information for a business outlook. Based on data from the global chemical company BASF,
first empirical results show that our approach significantly outperforms
statistical approaches based on historical demand data.
TD-22
Tuesday, 14:00-15:30 - Room 007
Game Theory Applications in Supply
Chains
Stream: Game Theory and Operations Management
Invited session
Chair: Eda Kemahlioglu-Ziya
TD-21
Tuesday, 14:00-15:30 - Room 006
ORCCS1
Stream: OR Consultancy and Case Studies
Invited session
Chair: Sue Merchant
1 - Learning from OR Practice
John Ranyard, Robert Fildes
The IFORS sponsored global survey of OR practice, that was fully reported at the last IFORS conference, raised several key challenges for
the OR community. These include: preserving and enhancing the traditional (hard) OR methodology; extending the scope of OR via problem structuring methodologies (soft OR); and taking advantage of the
Board Room popularity of Analytics. Proposals for meeting these challenges, supported by relevant literature, will be made.
2 - Optimizing Collection Routes for Bottle Banks
Jeroen Belien, Philippe De Bruecker, Simon De Jaeger, Liesje
De Boeck
This paper presents an integrative optimization-simulation approach
for optimizing the collection routes for bottle banks. A bottle bank is
a large container into which the public may throw glass bottles for recycling. The objective is to minimize the collection time while avoiding containers becoming full. Our model has been used to determine
the return on investment of providing the containers with filling level
sensors and to compare flexible routes with fixed, cyclic routes. Discussions with the client about implementing the results will also be
covered.
3 - Optimal Department Locations Determination and
Workforce Schedule in Textile Industry
Sila Halulu, Engin Bayturk, Fadime Üney-Yüksektepe
This study involves the biggest textile store chain in Turkey which has
many stores in seventeen countries. Currently, one IT department in
Turkey covers all stores. Since stores are located in different time
zones, it is difficult to manage stores’ problems from single location.
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1 - On Using Incentives to Induce Reliable Supply: The
Interplay of Supply Risk, Bargaining Power, and Process Design
Woonam Hwang, Nitin Bakshi, Victor DeMiguel
Supply risk can be mitigated through the supplier’s effort, but effort is
often not contractible in decentralized supply chains. We investigate
how contractual incentives may be used to induce reliable supply, and
how it is influenced by the interplay of the type of supply risk, the balance of bargaining power, and the allocation of decision rights in the
procurement process. We find that a simple wholesale-price contract
can often generate high efficiency. Moreover, multitask moral hazard
can actually mitigate the problem of incentive alignment, generally resulting in higher efficiency.
2 - Can You Be Too Fast? Assortment Competition and
Supply Chain Responsiveness
Victor Martínez de Albéniz, Gurhan Kok
In industries where customer needs quickly change, retailers can postpone their assortment decisions if they are quick enough. We study
here how assortment competition depends on the postponement capabilities of retailers. We develop a stylized model where two retailers
choose their assortment breadth either before or after market characteristics are revealed.
3 - Setting the Right Incentives for Global Planning and
Operations
Ulas Ozen, Marco Slikker, Henk Norde
We consider a firm selling a group of products that require the same
production technology and share resources through multiple regional
business units. The demand in each region is stochastic and best observed by the regional units. The firm is engaged in global planning
and manufacturing activities and relies on the regional units’ forecasts.
In this research, we are studying incentive mechanisms that induce the
business units to reveal their private information truthfully and work
hard.
IFORS 2014 - Barcelona
4 - Contracting for Capacity under Renegotiation: Partner Preferences and the Value of Anticipating Renegotiation
Eda Kemahlioglu-Ziya
This paper studies contract renegotiation in a stylized supply chain
model. Two original equipment manufacturers (OEMs) sign fixedquantity contracts with a contract manufacturer (CM) prior to demand
realization. Contract renegotiation after demand realization allows the
OEMs to use capacity that is more or less than what they contracted
for. We assume that the extra profit due to efficient allocation of capacity is allocated to the supply chain parties according to the egalitarian
rule and investigate when an OEM’s expected post-renegotiation profit
is maximized.
TD-23
Tuesday, 14:00-15:30 - Room 008
Behavioural Operations and Supply-Chain
Management
Stream: Behavioural Operational Research
Invited session
Chair: Hajnalka Vaagen
1 - Workers to Job Allocation — Case Study of Central
Europe Countries
Peter Horvát, Miroslav Štefánik
In this paper we present results based on EU Labour Force Survey microdata. We analyze the decisions of individuals on the combination of
economic sector and occupation where they accept employment. These
decisions determine the allocation of supply of labour on the labour
market. Two groups of factors are identified: individual (gender, age,
education, and region), market (wage, unemployment, dynamic of employment). We explore these factors using a multinomial logit model.
The data allow us to compare the contributions of particular factors to
individuals’ decisions between countries.
2 - Simulation and Experimental Analysis of Pull-Type
Ordering Methods
Javier Pereira, Fernando Paredes, Claudio Lavin, Luis
Contreras-Huerta, Claudio Fuentes
Ordering methods are simulated under an AR(1) demand processes
when a supply chain model is considered. Three criteria are computed
and aggregated on diverse scenarios: the stage’s amplification, average inventory and backlog levels. Pull-type ordering methods have
better results than push-type procedures. An experiment is developed
with twelve individuals who are instructed to use a pull-type policy.
The high amplification and average inventory levels observed show
that people persistently tends to prospective behaviour implementing
re-order and push methods, but introducing serious bias.
3 - Social Preconditions for Operational Excellence in
Engineer-to-Order Dynamic Systems — The Context
of Norwegian Offshore Shipbuilding
Hajnalka Vaagen, Jan Emblemsvag
The aim is to build understanding on the inner network mechanisms
and human factors that drive operational excellence in engineer-toorder dynamic systems: from the structural- to the cognitive dimension. Understanding is built by the triangulation of social network
analysis and behavioral studies, within the context of shipbuilding engineering planning. Besides establishing the true informal network
structures, explicit discussions are expected on how micro level behavior (like job rotation, motivation) influences macro level operations
(like outfitting flexibility offered to customers.
TD-25
TD-24
Tuesday, 14:00-15:30 - Room 212
Operations Finance Interface 1
Stream: Operations Finance Interface
Invited session
Chair: Burak Kazaz
1 - Supply Chain Network Structure and Firm Performance
John Birge, Jing Wu
The complexity and opacity of the network of interconnections among
firms and their supply chains inhibits understanding of the impact of
management decisions concerning the boundaries of the firm and the
number and intensity of its relationships with suppliers and customers.
Using recently available data on the relationships of public US firms,
we investigate the effects of supply chain connections on firm performance as reflected in stock returns. We find that supply chain structure
is closely related to firm returns at two levels, first from direct connection and second from centrality.
2 - Pre-shipment Financing: Credit Capacities and Supply Chain Consequences
Anne Lange, Fehmi Tanrisever, Matthew Reindorp
We study a supply chain where a wealthy retailer buys from a debtconstrained supplier who cannot internally finance his entire production operations. The retailer commits to a minimum purchase quantity
to facilitate pre-shipment financing, which enables the supplier to extend his debt capacity and thereby also his production level. In equilibrium, we illustrate that the retailer has an interest to collaborate with
a financially strong supplier. In contrast, we find that the supplier may
be at a disadvantage when doing business with a highly creditworthy
retailer.
3 - Multinational Newsvendor Networks: On the ProfitShifting Option of Multi-Plant Sourcing
Gerd J. Hahn, David Francas, Shailesh Kulkarni
We extend the classical newsvendor networks approach to a setting
with taxes and a profit-shifting mechanism. Optimal cost allocations,
transfer prices, capacity, and production levels are determined for a
multinational company that serves one domestic market under stochastic demand with a secondary sourcing option in a low-tax country.
While shifting the disposable income to the low-tax country is (obviously) optimal, the capacity investment strategy has two distinct forms
(single vs. dual-sourcing) depending on the cost parameters. A numerical example illustrates our analytical findings.
TD-25
Tuesday, 14:00-15:30 - Room 009
Patterns Detection in Very Large Datasets
Stream: Data Mining
Invited session
Chair: Bart Baesens
1 - A Social Network Approach to Identifying Key Police
Suspects using Data Mining
Fredy Troncoso, Richard Weber
The analysis of criminal groups through social networks has been a key
element in police analysis. A commonly used approach is the evaluation of the nodes importance and its application has been appropriate
where the links between individuals are the only information available.
This work propose an effective evaluator of the nodes importance in
a network composed of suspect individuals, considering the criminal
propensity of each individual. This evaluator, called Social Network
Criminal Capacity Evaluator (SNCCE), outperformed alternative evaluators that are commonly used in network analysis.
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IFORS 2014 - Barcelona
2 - Finding Cliques in Large Fraudulent Networks: Theory and Insights
Véronique Van Vlasselaer, Leman Akoglu, Tina Eliassi-Rad,
Bart Baesens
Given a bipartite graph consisting of people and activities, can we find
groups of persons frequently involved in the same activities? Moreover, given that some activities are fraudulent, are we able to identify
those groups of persons that are frequently involved in the same crimes.
This study concerns the detection of fraudulent clique structures in a
social security context. Using row- and column reordering techniques
and simultaneously spreading fraud through the network, our approach
successfully succeeds to find cross-associations, as well as to assign a
fraud score to each clique.
3 - Detecting Collusion-Based Occupational Fraud in
Business Processes
Filip Caron, Jan Vanthienen, Bart Baesens
According to the Association of Certified Fraud Examiners, an organization loses on average about 5% of its revenue to occupational
fraud. Collusion allows perpetrators to more easily circumvent antifraud controls, resulting in a median loss that is twice the loss of a single perpetrator scheme. While collusion remains hard to prove, event
logs of process-aware information systems can assist in uncovering
highly unusual interaction patterns. Based on the transaction data in
the logs, materiality based metrics can be defined for selecting the optimal fraction of potential fraud issues.
4 - Optimization Techniques in Astronomy
Mauricio Solar, Rodrigo Gregorio
In the context of ChiVO (www.chivo.cl) used for search of ALMA
data, processing tools and image analysis to detect and classify astronomical structures are developed. We will show an algorithm to identify and classify astronomical structures at different scales using the
wavelet transform (WT) in 2D images. WT provides a matrix to decompose it into several images of different scales. Identifying objects
in WT is, given a scale, isolate structures. Then a classification algorithm is applied to recognize the structures and incorporate them into
an astronomical catalog.
TD-26
Tuesday, 14:00-15:30 - Room 010
Fuzzy Systems
Stream: Fuzzy Decision Support Systems, Soft Computing, Neural Network
Invited session
Chair: Pavel Holeček
Chair: Siamak Naderi
1 - Fuzzy Clustering with Equity Constraints
Siamak Naderi, Kemal Kilic
The well known FCM algorithm, which developed for fuzzy clustering
problem, minimizes the within distance of the fuzzy sets such that the
membership degrees of data points sums up to 1. A related problem
is the zoning problems. However, a compact cluster is not the only
concern and equity among the zones is also widely desired; e.g., number of servers in a particular zone, number of customers assigned to a
particular salesperson and etc. In this research an equity constraint is
included to the fuzzy clustering problem formulation and an algorithm
is developed based on Lagrange multipliers.
2 - Multiple-criteria Fuzzy Evaluation in FuzzME - Recent
Development
Pavel Holeček, Jana Talasova
FuzzME is a software tool for multiple-criteria fuzzy evaluation. The
vast number of supported methods (fuzzy weighted average, fuzzy
OWA operator, fuzzified WOWA operator, fuzzified discrete Choquet
integral, and fuzzy expert system) makes it incomparable to any other
fuzzy decision-making support system. This presentation will summarize the recent development of the software and the theoretical results
used in it. Specifically, possible transitions between the various aggregation operators and methods of deriving their parameters from the
parameters of the original operator will be studied.
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3 - SPRINT SMEs: A Fuzzy Linguistic 2-Tuple Recommendation Approach for Allocating human Resources in Software Projects
Vassilis Gerogiannis, Pandelis Ipsilandis
Assignment of human resources to the activities of a software project
is a decision that is based on subjective/vague evaluation for the required skills and the capabilities of available resources. We suggest
content-based recommendation to handle this imprecise information.
The 2-tuple fuzzy linguistic model is used to adequately represent and
evaluate skills’ ratings. The development of the approach was cofinanced by the EU Social Fund and Greek national funds through the
Operational Program "Education & Lifelong Learning" of the National
Strategic Reference Framework (ARCHIMEDES III).
4 - Direct Search methods to optimize Indoor Location
Using Fuzzy Logic
Aldina Correia, Pedro Mestre, João Matias, Carlos Serôdio,
Carlos Serôdio
Optimization problems in areas such as engineering are characterized
by the fact that objective and constraints functions are non-smooth
and/or their derivatives are not know. Therefore, optimization methods based on derivatives cannot be used and direct search methods
must be an alternative. In this work these methods were used to tune
the Fuzzy Logic parameters of the membership functions used in the
location systems as well as the weights of the rules used in the on-line
phase of Fingerprinting location method, minimizing the value of the
precision.
TD-27
Tuesday, 14:00-15:30 - Room 213
Contracts, Auctions, Upgrade Timing, and
Reverse Supply Chain Management
Stream: Operations/Marketing Interface
Invited session
Chair: Samar Mukhopadhyay
1 - Buyback Contract and Price Postponement in a Decentralized Supply Chain with Additive and PriceDependent Demand
Weixin Shang
We study a decentralized supply chain with one supplier offering buyback contract to one retailer who postpones retail pricing decision after
demand realization. We find some mild conditions on demand distribution that guarantee the existence of a unique equilibrium when demand
is additive in uncertainty. We discuss the impact of buyback contract
on operational decisions and supply chain performance. Different from
the game with multiplicative demand, the equilibrium buyback ratio,
profit allocation ratio between supply chain members and the channel
efficiency depend on demand distribution.
2 - The Timing of Product Upgrades with Brand Loyalty
and Demand Aggregation
Sam Kirshner, Yuri Levin, Mikhail Nediak
This work examines how brand loyalty impacts the timing of product upgrades in industries with stochastic improvements in technology.
Loyalty is shown to be an important determinant of the upgrade decision, since it enables a firm to aggregate demand for a future product
release. Modeling the upgrade problem as a Markov Decision Process,
we prove the optimality of a threshold policy based on the concept of
demand aggregation. Numerical experiments are used to examine the
behavior of the threshold policy and profitability for varying degrees
of brand loyalty in different market conditions.
IFORS 2014 - Barcelona
3 - Supply Network Coordination by Auctions
Petr Fiala
A structure of supply networks is composed from layers of potential suppliers, producers, distributors, retailers, customers. The units
are interconnected by material, financial, information and decisional
flows. Developing coordination can significantly improve the efficiency of supply networks and provide a way to ensure competitive
advantage. Auctions are important market mechanisms for dynamic
pricing and allocation of goods and services. We propose coordination of supply networks by multi-dimensional auctions. Mathematical
models and solutions of the coordination process are presented.
TD-28
Tuesday, 14:00-15:30 - Room 130
International Outreach and Implicit
Expectations in OR
Stream: International Aspects of OR: Cooperation —
Coordination — Communication
Invited session
Chair:
Chair:
Chair:
Chair:
Graham Rand
Jakob Krarup
Ulrike Reisach
Gerhard-Wilhelm Weber
1 - Extending the Boundaries of IFORS
Jakob Krarup
A talented scientist, a group of scientists, a group of groups, a club,
a national society, a group of national societies, an international federation: embarking from "Blackett’s Circus" on the eve of WWII this
is what led to the birth of IFORS in 1959. Today, 55 years after, new
groups have emerged outside the IFORS community, amongst others
in Africa. How are they identified? How to find ways to include them?
No conclusive answer is provided whereas some initial approaches are
accounted for.
2 - Discovering and Dealing with Intercultural Issues in
Operational Research
Ulrike Reisach
OR as the development and application of scientific methods to improve decision making is useful for all challenges and countries
throughout this world. But different cultures influence the way problems are perceived and decisions are taken. Local conditions have
shaped people’s experiences, expectations and behavior — not only
in private life but also in the way of dealing with complex problems
relevant to industry and society. A previous analysis and reflection on
the societies, their history and implicit values and assumptions, helps
to implement OR successfully.
3 - A Survey of Manpower Planning Process: A Bane or
Boon of Unbounded Uncertainty and Bounded Rationality?
Joshua Magbagbeola
Although there have been a substantial number of critical dissections
in recent years on how to improve the manpower planning process,
most of them have been based on piece-meal rather than on a holistic,
systemic inquiry. This exploratory systemic formulation of an innovative framework aimed to organize and steer the manpower planning
process in the face of bounded rationality, unbounded uncertainty is
almost non-existence or elusive. There are other related issue, such as
wicked problems, complexity, and conflict that is also examined.
TD-30
TD-29
Tuesday, 14:00-15:30 - Room 011
Multiple Criteria Decision Making and
Optimization 4
Stream: Multiple Criteria Decision Making and Optimization
Contributed session
Chair: Jelena Stankovic
1 - Elicitation of Criteria Importance Weights with the
Simos Method: A Robustness Concern
Eleftherios Siskos, Nikos Tsotsolas, Yannis Siskos
In MCDA, the Simos method is considered as an effective tool to assess criteria importance weights. However, the method’s input data,
required by a decision maker, do not insure a single weighting vector. This paper shows that solutions of both original and revised Simos
procedures are vectors of a non-empty convex polyhedron. A set of robustness analysis techniques is proposed to help analysts and decision
makers in fixing a single set of criteria weights or in applying robust
rules based on multiple acceptable sets of weights. Results should be
considered as complementary to Simos method.
2 - Dynamic MCDA with PROMETHEE and GAIA
Bertrand Mareschal
Most MCDA methods are limited to static data evaluated at a single
given time. However many decision or evaluation problems involve
time-dependent data and multiple time periods. We propose to extend
the PROMETHEE-GAIA methodology to that case. Different types of
dynamic problematics are considered and several practical extensions
are implemented in the Visual PROMETHEE software including predictive PROMETHEE rankings and a dynamic version of the GAIA
analysis. Numerical examples are used to illustrate these extensions.
3 - What Social Choice Rules Could be Simplified to
Scoring Rules?
Yuliya Veselova
We consider social choice rules satisfying anonymity, neutrality, and
consistency axioms. These rules are called composite scoring rules,
since they could be represented via composition of simple scoring rules
(Young 1975). We show how a composite scoring rule is simplified to
a simple scoring rule for any given number of voters and alternatives.
This simplification provides a benefit in time complexity, what is important in group decision making with large number of alternatives or
voters. However, it is compensated by losses in space complexity in
some particular cases.
4 - Fuzzy AHP application for improving BFC SEE model
Jelena Stankovic, Sasa Drezgic, Zarko Popovic, Nikola
Makojevic
Business Friendly Certification (BFC) is a process that is conducted in
the countries of South-Eastern Europe in aim improve local business
environment. The mathematical background of BFC is multi-criteria
model with 12 criteria. The subject of this paper is to analyze the attitudes of the business communities about the relevance and importance
of these criteria. Research will be carried out at the urban level in the
cities in Serbia and Croatia, with emphasis on the analysis of regional
differences in the perception of criteria importance. In the analysis will
be used fuzzy AHP method.
4 - Pro Bono OR
Graham Rand
The Operational Research Society recently appointed a O.R. Pro Bono
Manager. This scheme provides free O.R. support to Third Sector organisations (mainly charities) in the UK and is carried out by O.R.
professionals. How projects and volunteers are found and matched
will be described. The advantages for the organisations, for the ORS
and for the volunteers will be explained, as well as some of the difficulties faced. Examples will be given of completed projects, as well
as similar work carried out in Uganda and for a charity involved with
street children.
TD-30
Tuesday, 14:00-15:30 - Room 012
Location-Allocation Models
Stream: Allocation Problems in Game Theory
Invited session
Chair: Lina Mallozzi
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IFORS 2014 - Barcelona
1 - Mathematical Models for a Location- Allocation Problem of Traffic Flow Capturing Facilities
Yoichi Shimakawa, Hirotaka Takahashi, Hiroyuki Goto
Practical mathematical models are formulated for a location-allocation
problem for the facilities that capture the traffic flow. It is an optimization problem that maximizes the total flow captured by locating
facilities on the road link. The main feature is that the traffic flow can
be captured commonly even in the case that some facilities are located
on the route. We assume several routes between the origin and destination. We formulate the optimization problems in terms of total traveler
kilometer and the number of O-D pairs. Using GIS, we study some
results of the numerical simulations.
2 - Maxmin Allocation of Homogeneous Goods: The
Three Players Case
Lucia Milone, Marco Dall’Aglio, Camilla Di Luca
We consider the maxmin equitable allocation of a finite number of
homogeneous divisible items among three players with idiosyncratic
preferences. We characterize the optimal allocations and develop an
algorithm for its search. Both goals are obtained considering two important structures from fair division theory: the partition range and the
Radon-Nikodym set.
3 - On the Problem of Optimally Locating Facilities and
Allocating Customers to Facilities
Egidio D’Amato, Elia Daniele, Lina Mallozzi
A two-stage optimization model is proposed to find the optimal location of new facilities and also the optimal partition of a market area. In
this location-allocation problem the social planner minimizes the social costs, i.e., the fixed costs plus the waiting time costs, taking into
account that citizens are partitioned according to minimizing the capacity acquisition costs plus the distribution costs. The solution of the
bilevel problem gives the optimal facility location. Theoretical and
computational results are presented in a planar region.
4 - A Game Theoretical Model of Sensor Devices Placement in a Planar Region
Lina Mallozzi, Egidio D’Amato, Elia Daniele
In this paper a noncooperative game theoretical model for the experimental design problem is presented. The design variables are the coordinates of points in a region of the plane, similar to a facility location problem. The optimal solution gives the values of the experiment
variables and corresponds to a Nash equilibrium solution of a suitable
game. We study an application of the model to the problem of locating a given number of cosmic wave receivers on a bounded region.
Theoretical and computational results are presented for this location
problem.
TD-31
Tuesday, 14:00-15:30 - Room 013
Security Decision Processes
Stream: Decision Processes
Invited session
Chair: Javier Cano
1 - An Adversarial Risk Analysis Approach to Fraud Detection
Javier Cano, David Rios-Insua
Risk analysis provides a methodology aimed at mitigating the negative
effects of threats that may harm the performance of a system. Adversarial risk analysis expands the methodology focusing on threats coming from intelligent intentional adversaries. In this paper, we provide
a an approach combining risk analysis and adversarial risk analysis to
determine best security portfolios when dealing with fraud detection in
relation with access to a physical paid facility.
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2 - Cibersecurity Decision and Risk Management Process
José Antonio Rubio Blanco, David Rios-Insua
The purpose of this work is to consider the influence and impact of all
the elements related with the cibersecurity decision cycle, especially
regarding computer system and critical infrastructure. We discuss the
fundamental points for cibersecurity, critical infrastructure protection
and decision-making cycles, taking into account aspects of cyber deterrence and cyber threat intelligence. We build a framework for strategic, tactical and operational approaches to cibersecurity, providing a
decision-making model to support the selection of information security controls.
3 - Incident Handling Decision Processes in Oil and Gas
Offshore Drilling
Aitor Couce Vieira, Siv Hilde Houmb, Paula deWitte
Incident handling on offshore drilling rigs involves critical activities to
respond complex events that may lead to serious consequences. The
article provides an analysis of the decision processes and stakeholders involved in such activity, as well as guidelines on how to improve
decision-making, command and control structures, information and
communication procedures, and coordination with other security activities. The aim is refining incident handling procedures to avoid failures, to enable a more coordinated and traceable incident handling, and
— the ultimate goal — to minimize risk.
4 - Potential Trade-offs of Different Financing and Regulatory Structures for Airport Security in Europe
Woohyun Shim, Fabio Massacci, Julian Williams
Recently, many security regulations that require increased expenditures have been enacted in the aviation industry. These regulations
have different regulatory (i.e., customized vs. one-size-fits-all) and financing rules (i.e., centralized vs. decentralized). However, the tradeoffs between these rules has not been studied well. This study reviews
various alternative financing and regulatory rules for airport security
in Europe, and discuss the potential trade-offs of these using a simple
conceptual model.
TD-32
Tuesday, 14:00-15:30 - Room 014
Information Systems
Stream: Data Mining, Knowledge Discovery and Artificial Intelligence
Contributed session
Chair: Laura Turrini
1 - Assessing Financial Incentives for Energy PolicyMaking
Yulia Malitskaia, Barry OSullivan
The EU FP7-funded ePolicy project (http://epolicy-project.eu), Grant
288147, aims to provide a system to support the policy decisionmaking process. The support system represents a global multiobjective optimization framework that takes into account several categories of explicitly-defined requirements and the effects of financial incentives on promoting photo-voltaic (PV) panel installations. This paper presents an analytical model for quantifying the feed-in tariff policy derived from a composite econometric and data-mining approach
analyzing multiple PV systems in several Italian regions.
2 - Towards Immune Genetic Algorithm for Composition
of Web Services with Constraints
Khaled Sellami, Djamal Dris
Web service is a promising technology that allows dynamic composability, however how to achieve this is one of the current research challenges. The purpose of this work is to present an approach for web
services composition based on genetic algorithm which focuses on two
aspects in order to find the optimal solution; (1) the functional aspect
by considering the semantic description of the web service, and (2)
the non- functional aspect by considering the values of QoS of the service components. The use of a vaccine during the evolution provides
heuristic information.
IFORS 2014 - Barcelona
TD-34
3 - Operational Tasks Process Design in Architecture
Program based on Improved HTN
Zhang Xiaoxue
4 - The Multiple Traveling Salesmen Problem with Moving Targets
Anke Stieber, Armin Fügenschuh
Operational tasks process design is key part in architecture program
design, which involves design of multiple architecture data and products. Hierarchical task network (HTN) is widely used in tasks process
design. We presented cohesion measured-based task decomposition
method in improved HTN, then proposed modified tasks process generation algorithm based on extended task timing relationships. Finally,
case study verified the proposed method and apply it into architecture
design process design to assist architects to develop process-related architecture data and products.
The multiple weapons to multiple targets assignment problem can be
seen as a multiple traveling salesmen problem with moving targets,
where the weapons correspond to the salesmen, and the targets to the
cities. Our approach is not based on restrictions to the movement of
the targets. A discretization of time leads to large-scale integer linear programming (ILP) problems, that need to be solved in very short
time. Computational studies on test problems demonstrate what problem sizes can be handled, and how much solutions from a fast and
simple first come, first served heuristic can be improved.
4 - Simulation as a key element of advisory system in
construction engineering
Aneta Konczak, Jerzy Paslawski
An important role of simulation in support of production planning processes in the construction sector are presented. Simulation is a key
element of hybrid advisory system, including various methods: analogy based on similarity of cyclical construction processes executed in
similar conditions, abductive and deductive approach, and mentioned
simulation. An implementation of this advisory system in ready-mix
concrete delivery is presented as case study.
TD-34
Tuesday, 14:00-15:30 - Room 016
Risk Analysis and Assessment
Stream: Decision Making Modeling and Risk Assessment in the Financial Sector
Invited session
Chair: Jean-Luc Prigent
TD-33
Tuesday, 14:00-15:30 - Room 015
Defence and Security Applications III
Stream: Defence and Security Applications
Invited session
Chair: Ana Isabel Barros
1 - Optimizing Adversary Aircraft Fleet Composition and
Employment
Robert Dell, Ryan McLaughlin, Matthew Carlyle
This talk presents an integer-linear program (ILP) to plan adversary aircraft fleet composition and employment to best satisfy the US Navy’s
annual adversary training demands over a 20-year horizon. Subject to
annual budgets and other rules on aircraft use, the ILP prescribes sorties by aircraft type as well as yearly upgrades to the fleet, including
procurement of new aircraft, procurement of performance enhancing
upgrades, and retirement of older aircraft. ILP solutions to numerous
real-world excursions suggest that training can be improved while simultaneously reducing operating costs.
2 - Optimal Scheduling of Canadian Armed Forces
Search and Rescue Response Posture
Bohdan Kaluzny
The Canadian Armed Forces provide search and rescue (SAR) response for incidents involving aircraft and vessels in an area covering
over 18 million square kilometres. SAR squadrons maintain a response
posture defined as the ability to be airborne within a stated time period:
either 30 minutes (RP30) or 2 hours. Time on RP30 is limited due to resource constraints. A mixed-integer linear program was formulated to
determine optimal schedules aligning time on RP30 to historical SAR
incident times. We present the mathematical formulation and related
data visualization and optimization results.
3 - A Routing Problem of UAVs by Mission-Adapted
Mathematical Programming
Ryusuke Hohzaki, Shunya Nakamura
An unmanned aerial vehicle (UAV) plays an important role for reconnaissance and intelligence use. It is a good tool to search for moving
targets on the ground as well as in the sea. We propose mathematical programming methods, LP and DP, to solve a routing problem of
the UAVs. We adopt adequate criteria for the problem, corresponding to the reconnaissance and the intelligence mission of the UAV. In
our methods, we revise the scenarios of the target movement by Bayes’
theorem and take account of the limited motion of the fixed-wing UAV.
1 - Correlation Across Latent Variables in Credit Risk
Models: A Direct Inference from Default Rates
Fernando Moreira
The correlation across latent variables assumed to drive defaults is a
key parameter in the credit risk model used by financial regulators. We
point out some inconsistencies in this approach and suggest the use of
a more coherent measure in this context (the tetrachoric correlation coefficient). We show that the number of loans in the portfolios and their
default rates are sufficient to estimate the correlations. Our results support empirical findings in other studies based on different approaches.
The technique suggested here can be easily implemented by practitioners and regulators.
2 - A Generalization of Cornish Fischer Formula to Compute VaR: Evidence on Real Estate Data
Charles-Olivier Amedee-Manesme
This paper proposes to better modeled infrequently published returns
indices. Infrequent returns are common in alternative investments such
as art, wine or real estate where transactions are characterized by their
heterogeneity, their low number or their illiquidity. Using a derivation
of the Cornish Fischer expansion, the proposed approach allows to better estimate the true distribution. The proposed model is applied on real
estate databases. The approach is relevant for fund or risk managers.
3 - On the Debt Capacity of Growth and Decay Options
Jean-Luc Prigent, Nourdine Letifi
This paper focuses on the impact of debt on the optimal policy for investment and hiring. We extend the model introduced by Tserlukevich
(2008) by first adding another key control variable, namely the employment level, second by considering a no longer perpetual debt. We
detail and analyze the optimal strategies, by using results about singular stochastic optimal control with triggered solutions. The novelty of
our approach is based on the combination of optimal firm management
with the valuation proposed by Merton (1974).
4 - Scoring Method of Enterprise Risk Management
Juthamon Sithipolvanichgul, Jake Ansell
The main objective of this paper is to propose Enterprise Risk Management (ERM) scoring method from integrating well-implemented ERM
components where contribution measurement can be standardized by
constructing a sample of firms from all public listed firms in Thailand
and classified level of ERM adoption. Stepwise regression model is
used to find relationship of ERM implementation level and Tobin’s Q.
There are positive significant different between ERM and firm value.
Finally, not only financial companies will advantage implementation
of ERM but also non-financial companies as well.
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IFORS 2014 - Barcelona
TD-35
Tuesday, 14:00-15:30 - Room 131
Game Theory with Applications III
Stream: Stochastic Modeling and Simulation in Engineering, Management and Science
Invited session
Chair: Yasushi Masuda
1 - Comparison of Discrete Fixed Point Theorems by a
Bimatrix Game
Hidefumi Kawasaki
There are three types of discrete fixed point theorems: type (C) deals
with contraction mappings, type (M) deals with monotone mappings,
and type (B) is based on Brouwer’s fixed point theorem. In this talk,
we mainly deal with types (M) and (B), and make a comparison of
them by a bimatrix game. We will show that the simplicial decomposition of the convex hull of the domain of the mapping is important for
analyzing type (B).
2 - Optimal Licensing for Incumbent Innovator in Differentiated Product Markets
Masashi Umezawa, Tatsuya Kitagawa, Yasushi Masuda
We investigate a two-part tariff licensing contract that enables an incumbent innovator to license the technology for a new product to a potential rival, who may alternatively develop a compatible technology
for an imperfectly substitutable product. We identify the optimal twopart tariff licensing contract based on the development cost incurred by
the rival, the market parameter, and the substitution coefficient.
3 - Game Theoretic User Equilibrium in a CongestionProne System with Priority
Yasushi Masuda, Akira Tsuji
We consider a stylized congestion-prone system of multiple resources
where a fixed number of priority passes are allocated to each customer,
and demonstrate that a priority system could be an effective method of
congestion control even when customers are homogeneous. We prove
that there exists an equilibrium of customers’ behavior. In particular, the system without priority has a unique equilibrium. Numerical
examples show that the proposed priority system is effective. Furthermore with a proper number of priority passes the equilibrium sometimes achieves the first best solution.
TD-36
Tuesday, 14:00-15:30 - Room 132
Forest Management for Biodiversity
Stream: OR in Agriculture, Forestry and Fisheries
Invited session
Chair: Mustapha Ohimmou
1 - Towards the Development of a Spatially Explicit Management Model to Protect the Fisher (Martes Pennanti) in an Industrial Forest in California
Richard Church, Matthew Niblett, Klaus Barber
The fisher (Martes Pennanti) is a small weasel that is one of the key
species of concern in forest management in California. A viable home
range territory of a female fisher needs high canopy cover in approximately 70% of the area, as well as a number of scattered large structural
trees and snags. It is necessary to model canopy and structures within
unit areas no larger than 40 acres in size, where a typical home range
is comprised of 60 or more planning units. In this paper, we propose a
new spatial optimization model to optimize harvesting activities while
protecting the fisher.
128
2 - Production Possibility Frontiers for Energy Wood,
Timber Production and Biological Diversity in North
Karelia, Finland
Mikko Kurttila, Leena Kärkkäinen, Olli Salminen
A large-scale planning system was used to define production possibilities for energy wood, timber production and biodiversity. The results
were reported through production possibility frontiers. They indicate
that rather high amounts of energy wood can be harvested with minor
impact on the studied variables. Energy wood harvesting from thinning stands is supportive to timber production. Energy wood removals
from young stands cause minor effects on variables related to biodiversity. Economically sound production of energy wood is connected to
harvesting operations of other forest industries.
3 - Wood Allocation and Selection of Forest Harvest Areas - How to Consider Spatial Dispersion and Sustainable Forest Management Policies?
Mustapha Ohimmou, Azdeh Mobtaker, Mikael Rönnqvist,
Marc Paquet
The tactical planning in forest management involves the selection of
harvest areas over a horizon of several years and allocates them to
mills to fulfill certain demand. Several optimization criteria must be
included to achieve sustainable forest management policies. Both government and industry face these questions and need decision support
system to enable efficient plans. In this paper, we address this wood
allocation problem and the selection of harvest areas while taking into
account spatial dispersion Sustainable Forest Management Policies in
a case study in crown land in Canada.
TD-37
Tuesday, 14:00-15:30 - Room 017
Multicriteria Decision Making in
Humanitarian Logistics
Stream: Multiobjective Optimization
Invited session
Chair: Begoña Vitoriano
Chair: F. Javier Martin-Campo
1 - A Multicriteria Proposal for a Humanitarian Logistics
Problem: An Integral Approach
Julian Molina, Christopher Mejía-Argueta, Juan Gaytán,
Rafael Caballero, Begoña Vitoriano
Disasters are phenomena which strike countries around the world. The
work introduces an integral proposal to consider distribution, evacuation, location of facilities and a preposition stock policy during floods
with multicriteria (equity: minimizing the maximum evacuation and
distribution flow-times, as well as total cost). The efficient frontier for
the preparedness phase is built through the weighting with the epsilonconstraint methods and for the response phase through a metaheuristic
based on tabu and scatter search. The usefulness of the model is validated by a case study in Mexico.
2 - Metaheuristics for a Multi-Criteria Humanitarian Aid
Distribution Problem
José María Ferrer, M. Teresa Ortuño, Gregorio Tirado
Planning the delivery of humanitarian aid involves several factors such
as cost, operation time, equity of the distribution, reliability of the
itineraries, security, etc., which lead to a complex multi-criteria optimization problem. In this work a metaheuristic inspired on a GRASP
(Greedy Randomized Adaptive Local Search Procedure) methodology
is presented to solve this problem. The proposed method guides the
construction of solutions prioritizing the elements that provide larger
local improvements as well as those that were part of the best solutions
obtained previously.
3 - A Decomposition-based Heuristic for Optimizing
Post-Disaster Relief
Christophe Duhamel, Andréa Cynthia Santos, Daniel Brasil
IFORS 2014 - Barcelona
We consider the problem of setting up post-disaster distribution centers
and supplies delivery to the population over a given time period. Financial, operational and human restrictions limit both the centers opening
schedule and the distribution. We present a non-linear model and we
propose a mathematical decomposition where the primary variables
(centers opening dates) are addressed by NOMAD solver while the
distribution is computed by heuristics and a VND local search. Our
approach is calibrated on several instances and scenarios, and evaluated on a realistic instance.
4 - Interactive Decision Making Approach for Selecting
an Evacuation Plan
Juan Gaytán, Javier Garcia-Gutierrez
Given the multi-criteria nature faced in the humanitarian logistics context, there is the issue of providing a quick solution adding the good
judgment and expertise of the decision maker. Formal and evolutionary approaches exist to identify promissory solutions at the Pareto front
as well as providing interaction with the decision maker to end up with
a best compromise. We present a fast-solved interactive multi-criteria
procedure that starts from a knee point of the Pareto front and a local
guided search.
TD-38
Tuesday, 14:00-15:30 - Room 214
Proximal and Splitting Algorithms
Stream: Convex Optimization Methods and Applications
Invited session
Chair: Xiaoming Yuan
1 - On the Extension of ADMM for Separable Convex
Programming and Beyond: From Variational Inequality Perspective
Xiaoming Yuan
The direct extension of the alternating direction method of multipliers (ADMM) for a multi-block separable convex minimization model
is not necessarily convergent. We propose a prototype algorithm that
can preserve completely the numerical advantages of the direct extension of ADMM but with guaranteed convergence. A unified and easily
checkable condition to ensure the convergence of this prototype algorithm is given. Based on this prototype algorithm, we also propose a
class of specific ADMM-based algorithms. The analysis is conducted
in the variational inequality context.
2 - A Proximal Point Algorithm Using an Asymmetric
Linear Term
Deren Han
In this paper, we propose a new PPA with asymmetric proximal term.
For a given iteration, the next iteration is generated by solving a PPAlike subproblem, which is similar to that in the classical PPAs. The less
restrictions on the proximal term provides us the possibility of designing some efficient splitting algorithms, taking into account the original
problems’ special structures. Moreover, discarding the correction step
can help us keep the favorable properties of the iteration generated by
PPA-like subproblems.
3 - Smoothing Proximal Gradient Methods for a Class of
Nonsmooth Convex Minimization Problems
Sanming Liu
Inspired by various applications, we propose a novel optimization algorithm for minimizing a convex objective which decomposes into
three parts: a smooth part, a simple non-smooth Lipschitz part, and a
simple non-smooth non-Lipschitz part. We use a time variant smoothing strategy that allows us to obtain a guarantee that does not depend
on knowing in advance the total number of iterations nor a bound on
the domain.
TD-40
TD-39
Tuesday, 14:00-15:30 - Room 018
Algorithms for Large-Scale 0-1 Linear and
Quadratic Programming Problems
Stream: Discrete and Global Optimization
Invited session
Chair: Jitamitra Desai
1 - An Improved RLT-based Mechanism for Solving Nonconvex 0-1 Quadratic Programs
Jitamitra Desai
There are several well-known convexification methods for solving nonconvex quadratically constrained quadratic programs (QCQPs). We introduce a new class of cutting planes that we refer to as minimum triangle inequalities (MINTI). Motivated by these MINTI cuts, an improved
version of the RLT-based branch-and-bound algorithm is presented for
solving nonconvex 0-1 QCQPs.
2 - On Augmented Lagrangian Duality In Integer Programming
Andrew Eberhard, Natashia Boland
We consider the augmented Lagrangian dual for integer programming,
and provide a primal characterization of the resulting bound. As a
corollary, we obtain proof that the augmented Lagrangian is a strong
dual for integer programming. We are able to show that the penalty
parameter applied to the augmented Lagrangian term may be placed
at a fixed, large value and still obtain strong duality for pure integer
programs. Some potential avenue of application of these results are
discussed.
3 - Integer Bilevel Quadratic Fractional and Quadratic
Programming Problem
Nacera Maachou, Mustapha Moulai
The purpose of this paper is to find the integer solution for the bilevel
quadratic fractional/quadratic programming problem (BQFP) in which
the leader’s objective is quadratic fractional and the follower’s objective is quadratic. Applying the Kuhn-Tucker conditions at the lower
level, the (BQFP) is converted to a quadrtaic fractional programming
problem with complementarity constraints. A related bilevel linear
fractional/quadratic problem problem (BLFP) is constructed in order
to obtain an integer optimal solution of a (BQFP).
4 - C-GRASP for Mixed Integer Global Optimization
Joao Lauro D. Faco’, Mauricio Resende, Ricardo Silva
Continuous GRASP (C-GRASP) is based on the guidelines of the
greedy randomized adaptive search metaheuristic procedure (GRASP)
of Feo & Resende (1989, 1995) to find optimal or near optimal
solutions to constrained global optimization programming problems
(Hirsch et al., 2007). We adapt C-GRASP to handle both discrete and
continuous variables. The linear or nonlinear constraints as well as the
variable integrality constraints are incorporated in the objective function using a penalty term. We present results of computational experiments with hard mixed integer nonlinear programming problems.
TD-40
Tuesday, 14:00-15:30 - Room 019
Innovations in Meta-Analytics I
Stream: Meta-Analytics: A Marriage of Metaheuristics
and Analytics
Invited session
Chair: Fred Glover
Chair: Manuel Laguna
Chair: Gary Kochenberger
129
TD-41
IFORS 2014 - Barcelona
1 - Variable Association Networks for Identifying Patterns in 0-1 Integer Programs
Shunji Umetani
The latest MIP solvers have become to solve many real instances optimally in recent years. However, many large and/or hard MIP instances
still remain because of little hope to close large gap between lower and
upper bounds by the standard mathematical programming methods. To
overcome this, we incorporate a data mining technique into an efficient
local search algorithm, in which we construct variable association networks that identify promising pairs of flipping variables in the large
neighborhood search.
2 - A Two-Stage Population-Based Approach with Learning Mechanisms
Eduardo Lalla Ruiz, Christopher Expósito Izquierdo, Belen
Melian Batista, Marcos Moreno-Vega
In this work, we propose a two-stage population-based approach to
solve optimization problems. Our approach exploits the information
obtained from preliminary tests in order to learn and tune up its own
components. During the first stage, a pre-search process that consists
of conducting analytical tests regarding different search components of
the algorithm is performed. In the second stage, the collected data regarding the performance of each search component is analyzed and
used to determine which components are promising to enhance the
overall algorithm behaviour through the search process.
3 - SAT-DM: Satisfiability Data Mining for Classification
Problems
Vincent Gardeux, Lars Magnus Hvattum, Fred Glover
SAT-DM is a new classification method that generates a representative
set of binary inequalities for each class. The inequalities are feasible
solutions to a special variant of a satisfiability problem. A new sample is assigned to the class whose inequalities are the less violated.
Although primarily designed for handling binary attributes, SAT-DM
has been extended to any representation using a binarization method,
inspired by the IDEAL algorithm. SAT-DM belongs to the class of
Meta-Analytics procedures, joining metaheuristics with the field of analytics to enhance machine learning processes.
4 - Meta-Analytics for Improved Heuristic Search in
Combinatorial Spaces
Manuel Laguna, Abraham Duarte, Rafael Marti, Anna
Martínez-Gavara
Metaheuristics are typically configured and implemented as a set of
search strategies that are chosen a-priori by following general methodological principles and context information. Programming by Optimization (PbO) is a noteworthy exception, where design choices are
delayed and the task of determining the algorithmic configuration for
a class of problems is viewed as an optimization problem. We propose
applying data meta-analytics to discover search strategies that could be
more effective than design choices that are either hard-coded or given
as alternatives in frameworks such as PbO.
to consumer plants under given constraints. The system suffers from
important uncertainties, using measurements and data reconciliation
methods for reliable estimation of all process variables combined with
plant-wide optimization to minimize operating costs.
2 - Development of a Multi-Objective Optimization Model
for the Integrated Management of Internal and External Production Resources
Javier Silvente, Antonio Espuña
This work addresses the integrated management of external (materials,
energy/water management) and internal resources (equipment units,
manpower) within the operation of a production plant, to determine
the production strategy to best fit a specified demand, optimizing the
use of resources through their integration and through the adaptation of
their consumption to their availability. This objective is met using an
extended mathematical formulation of the traditional integration approach to consider a generic view of common resources. Acknowledgements: DPI2012-37154-C02-01 and BES-2010-036099
3 - A Large Neighbourhood Search Combined with
Monte-Carlo Simulation for Coping with Airlines Operational Disruptions
Daniel Guimarans, Pol Arias, Miguel Mujica Mota
We propose a methodology combining simulation and optimisation to
tackle operational disruptions in the airline industry and increase solutions’ resilience. Operational disruptions are defined as a deviation
from originally planned operations and cause significant overheads to
airlines. By introducing Monte-Carlo simulation methods within the
solution acceptance mechanism in a Large Neighbourhood Search process, we can guide search towards more robust solutions. Advantages
of our proposed methodology will be assessed by different case studies
based on real data.
4 - Improvements in Multi-Objective Optimization for
Supply Chain Design Problem
Gonzalo Guillen Gonsalbez, Pedro Jesús Copado Méndez
In the recent past, supply chain management (SCM) and enterprisewide optimization (EWO) have been devoted to extend the boundaries
of the analysis in order to capture a broader range of business practices. Our work addresses the multi-objective optimization (MOO) of
supply chains (SCs) of enrivonmentally friendly fuels. In particular,
we present a comparison between four e-constraint based strategies
that expedite the overall search of optimal solutions in a smart manner
by eliminating redundant criteria. The performance of these strategies
is assessed by means of the hypervolume indicator.
TD-42
Tuesday, 14:00-15:30 - Room 215
OR in Systemic Risk, Credit Risk and
Rating
TD-41
Tuesday, 14:00-15:30 - Room 216
Stream: Big Data Analytics
Invited session
Enterprise-wide Optimization
Chair: Kasirga Yildirak
Chair: Mariana Funes
Stream: Simulation-Optimization in Logistics & Production
Invited session
Chair: A. Carlos Mendez-Aguirre
1 - Optimal Operation of a Petrol Refinery Hydrogen Network
Elena Gomez, Gloria Gutiérrez, Daniel Sarabia, Cesar
dePrada, Sergio Mármol, José Miguel Sola, Rafael González
Hydrogen H2 is an expensive utility employed in many refinery processes which has gained increasing importance in the economic balance. A model-based optimization tool for decision support has been
developed for on-line optimal operation of a petrol refinery network
involving 18 plants, aiming at a better H2 redistribution from producer
130
1 - Assessing the Effects of Spanish Financial Sector
Restructuring on Branch Rivalry
Martí Sagarra, Cecilio Mar Molinero, Frank M.T.A. Busing,
Josep Rialp
Spanish banks have been heavily affected by the banking crisis that
began in 2008. Many of them, especially the Cajas, had to merge with
other institutions or had to be rescued. We address the question of up
to what point the nature of competition in this sector has changed as a
result of the crisis. Our measure of interfirm rivalry is based on a geographical proximity measure that we calculate for the years 2008 and
2012. The technical approach is based on multidimensional unfolding,
a methodology which allows us to represent the asymmetric nature of
such rivalry through statistical maps.
IFORS 2014 - Barcelona
TD-44
2 - A Novel Application of Data Envelopment Analysis
for Efficiency Evaluation of Banking Sector Firms
Shamaila Ishaq
3 - Point and Interval Estimation for Weibull Regression
Model under Progressive Type-II Censoring
Coşkun Kuş, İsmail Kınacı, Tony Ng
This paper proposes a novel methodological application of production
trade-offs for efficiency evaluation of the banking sector. Although this
new methodology is somewhat similar to weight restrictions, it provides a different way of incorporating additional information such as
asset quality, regulatory requirements and bank specific characteristics
simultaneously into the DEA model. For empirical application realistic trade-offs have been identified in banking operations and incorporated in DEA model using VRS technology. Results show improved
discrimination of efficiency scores.
In this paper, the maximum likelihood estimators and Fisher information and asymptotic variance-covariance matrix based on progressive
censoring schemes are obtained for Weibull regression model. Some
simulation study are performed to investigate the bias’, variances and
MSEs of estimators. The coverage probabilities of approximate confidence intervals based on MLE are also considered. Finally, conclusions and discussions are provided.
3 - Credit Scoring Model with Additional Regression Parameters Taken from the Social Networks
Nataliya Soldatyuk, Michal Cerny
We present an experimental study of a credit scoring model based on
logistic regression where public data from social networks are included
as additional regression parameters. The main finding is that including
of the social network data in the model can significantly affect the predictive power of the model. Though this is a case study only, it exposes
that publicly available data from the social networks have an impact on
the debtor-creditor relationship between a (potential) client and a bank.
4 - Assessing Developing Countries Creditworthiness
Using the UTADIS Multicriteria Analysis Method
Mariana Funes, José Vargas
Since the globalization of capital markets, a higher number of developing countries governments are borrowing in international bond
markets. It is important to have information that allows differentiating good and bad credit quality countries. This application involves
the creditworthiness assessment of 98 developing countries previously
classified in 9 ordered groups according to the implementation of an
unsupervised classification method. Using UTADIS an additive utility
function was developed that reproduced the classification with satisfactory results in terms of the classification error.
TD-43
Tuesday, 14:00-15:30 - Room 217
Data Mining, Statistics and Reliability
Theory
Stream: Computational Statistics
Invited session
Chair: Pakize Taylan
Chair: Tony Ng
Chair: Coşkun Kuş
1 - Maximum Margin Multiple Kernel Clustering by Semiinfinite Optimization
Sureyya Ozogur-Akyuz, Gulnur Seichanoglou
4 - A Simulation Study to Compare the Estimators for
Several Discrete Distributions Under Type I Censoring
Yunus Akdoğan, Tony Ng, Coşkun Kuş, İsmail Kınacı
In this study, Discerete Chen distribution is considered. Maximum
likelihood, proportion, least squares and moment estimators based on
type I censored sample are obtained. These estimates ara also compared via Monte Carlo simulation study. Some numerical examples
are also provided.
TD-44
Tuesday, 14:00-15:30 - Room 218
OR Promotion among Academia,
Businesses, Governments, etc.
Stream: Initiatives for OR Education
Invited session
Chair: Gerhard-Wilhelm Weber
Chair: Liudmyla Pavlenko
Chair: Elise del Rosario
1 - Modeling Population Dynamics with Markov Chains
and Logistic Regression in Industrial Engineering
Faculty
Erick Orozco
This paper models the population dynamics of industrial engineering
students using a stochastic process as a Markov chain and a generalized linear model and the multinomial logistic regression. The results
obtained are useful for decision making in college, because, generate results desertion, retention and transfer students, which makes the
strategy of academic support programs more effective. Also a cost
model presented sets goals for admission of students, in order to use
economies of scale and make academic programs more sustainable, in
a dynamic environment such as the Colombian economy.
2 - Developing the Quantitative Curriculum in Business
and Accounting
Jon Warwick, Anna Howard
Maximum margin clustering (MMC) has recently become efficient
method in machine learning communities. As in the classification
problems, choice of the kernel function affects the success of MMC. In
this study, multiple kernel learning is adapted to MMC by using semiinfinite optimization. Kernel coefficients are constrained to L1 norm
to produce a sparse solution while the weight vectors are penalized to
L2 norm. Optimality conditions are analyzed for semi-infinite problem
derived from maximum margin multiple kernel clustering model.
Teaching Business decision support methods requires careful consideration of both what to teach and how to teach it. This paper summarises
previous research into curriculum development issues for students in
UK HE studying Business and Accountancy courses. Employers require that such courses ultimately deliver the correct blend of advanced
techniques and core skills but studies have found that this is not always
the case. Further, supporting and developing sometimes basic quantitative skills in diverse student cohorts presents particular pedagogic
challenges and these are also discussed.
2 - New Solution Methods for the Mean Shift Outlier
Model by M-Estimation Based on the Tikhonov Regularizaton and LASSO
Pakize Taylan, Burcu Bilgiç, Fatma Yerlikaya Ozkurt
3 - The Modelling as Art for Sustainable Development of
World (Fundamental Aspects in Engineering Education from the Viewpoint of a Nonlinear Analysts - OR)
Lyudmila Kuzmina
In statistical research, regression models base on data, play a central
role; one of these models is the linear regression model. However,
this model may give misleading results when data contain outliers. We
deal with the outliers problem in linear regression using the Mean Shift
Outlier Model (MSOM) and providing a new solution for it by Mestimation based on the Tikhonov regularization problem and LASSO.
We treat it using convex optimization techniques, permitting the use of
interior point methods. We present numerical examples and we compare performance measures for our new solutions.
Research is devoted to Fundamentals of Modeling, Higher Engineering Education problems. Modeling is Art, connected with level/quality
of Knowledge in areas of natural sciences, multidisciplinarity, with
problems in training-teaching of specialists in complex engineering
domains. The principles of subject teaching are discussed, which lead
to activating/governing methods for engineering education in all areas.
Modeling of systems thinking/system dynamics, applied to multidisciplinary objects, support a sustainable world. "The owning Knowledge,
own the World’ (Bernard Shaw)
131
TD-45
IFORS 2014 - Barcelona
4 - Is Big Data the New Sputnik? An Analysis of the
Skills Gap in the Analytics Job Market
Michael Mortenson, Stewart Robinson, Neil Doherty
Whilst many recent reports highlight a perceived shortage of candidates with training in analytics, this has not detailed certain aspects.
Specifically, it is unclear which skills are lacking and, as the training
of STEM subjects and graduates has been debated since the launch of
Sputnik in the 1950s, whether such shortages are indeed a new phenomenon. To address this issue, analyses of quantitative data and a series of interviews with practitioners working in analytics are presented.
The results create a better understanding of analytics and suggest new
directions for education and training.
Tuesday, 16:00-17:30
TE-01
Tuesday, 16:00-17:30 - Room 118
Robustness and Maintenance of Vehicles
and Infra
Stream: Railway and Metro Transportation
Invited session
Chair: Ángel Marín
TD-45
Tuesday, 14:00-15:30 - Room 219
Sustainable Development
Stream: Sustainable Development
Invited session
Chair: Zenonas Turskis
Chair: Tatjana Vilutiene
1 - Strategy Modelling for Hotel Facilities Management
Rasa Apanaviciene, Silvija Kapočien, Nerijus Varnas, Ala
Dauglien
In many countries hotels represent a significant part of real estate sector. Hotel competitiveness is influenced by effective business as well
as rational facility management solutions that allow reducing overhead
and direct operating costs. While analysing external/internal factors
and peculiarities of facilities management process, a theoretical model
for hotel facilities management solutions was developed, that combines
market, service supply chain, facilities management efficiency criteria,
as well as economic, expert and multicriteria evaluation methods.
2 - Integrated Group Fuzzy Multi-Criteria and CostEffective Model for Selection of Facility Management
Services for Commercial Premises
Zenonas Turskis, Edmundas Kazimieras Zavadskas, Tatjana
Vilutiene, Natalija Lepkova
This paper analyses the work peculiarities of facility management
companies’ in a fuzzy market situation. There is a developed fuzzy
multi-criteria group decision making model for similar problems solution, taking into account cost-effective management. The case study
presents the selection of rational set of the facilities management services applying the weighted cost-effectiveness analysis together with
the fuzzy multi-criteria decision making method ARAS. Such an analysis supports objective decision making: options considered in an objective way provide support for the final decision.
3 - Quality Management Improvement in Road and Highway Engineering
Jerzy Paslawski, Tomasz Rudnicki
Quality assurance is a critical problem in road and highway engineering. A new approach implemented in the last time is presented. An
open market, a new network of quality laboratory and a ranking list
of contractors are key elements of this conception. A value management and six sigma are discussed as steps for the future. Some case
studies (acoustic screens, park & ride parking, quality ranking list) for
illustration of implementation procedures are presented.
4 - Markov Switching Applied to the Evolution of GDP of
Argentina, Brasil, Colombia and Mexico, 1950 to 2004
Alfredo Russo, Hernan Ferrari, Carlos Martinez, Juan
Ledesma
Using the annual GDP series for Latin America countries (1950-2008)
in constant dollars of year 2000, we have calculated the transition probabilities for each Hidden Markov matrix and the respective mean times
for each regime since 1950 to 2008. Inter annual percent variations of
GDP’s for each country are used to simplify calculations. Parameters
have been calculated using the Maximum Likelihood method. A first
calculation has encompassed the whole period of 54 years and a second one encompassed periods of 10 years to verify time dependency
of transition probabilities.
1 - Long-Term Planning of Railway Track Maintenance
François Ramond, Bathilde Vasselle
For security reasons, maintenance has to be performed on railway
tracks, making some portions of them unavailable during operations.
For a given number of maintenance operations, maximum track availability is achieved by combining operations into single “track possessions”. We consider the associated scheduling problem where operational constraints have to be taken into account to minimize the number
of required possessions as well as the distance travel by maintenance
machines on the network. We present some results showing that significant gains can be achieved by optimization techniques.
2 - Interactive Rolling-Horizon Scheduling of Depot Visits and Condition based Maintenance Tasks
Bob Huisman, Cees Witteveen
The majority of train maintenance tasks is condition based. When
needed, vehicles have to visit maintenance depots within predetermined time windows. We propose schedules for depot visits and maintenance tasks taking into account the availability of routing options
while respecting job deadlines. The method proposed solves the problem to optimality in polynomial time and offers real-time interaction
with human planners. When used in a rolling horizon scenario with a
dynamic environment it enables the user to control economic optimality versus plan stability in a time-efficient way.
3 - Optimal Scheduling of Aircrafts’ Engines Repair Process
Isabel Cristina Lopes, Eliana Costa e Silva, J. Orestes
Cerdeira
We address a real world scheduling problem concerning the repair process of aircrafts’ engines by TAP Maintenance and Engineering (TAPME), which is the maintenance, repair and overhaul organization of the
Portuguese leading airline. A MILP model, based on the flexible job
shop scheduling, to determine the optimal sequencing of tasks within
workstations, minimizing the total weighted tardiness, is presented.
The model was tested on a real instance provided by TAP-ME from
a regular working week and also on benchmarking instances available
in literature.
4 - Scheduling of the train operation by a double track
railroad while segments are closed.
Nail Khusnullin, Alexander Lazarev
We consider a problem, namely, the optimal scheduling of the train operation by a double- track railroad when one of the segments is under
repair works. It is necessary for the set of trains available at the stations to determine time-scheduling and destination routing by railways
in order to minimize one of the regular objective function. We suggest
an exact algorithm. The idea suggested may be used for chosing the
time period when the closing segments are economically profitable.
TE-02
Tuesday, 16:00-17:30 - Room 111
Vehicle Routing Applications
Stream: Vehicle Routing
Invited session
Chair: Refail Kasimbeyli
132
IFORS 2014 - Barcelona
1 - Courier Routing for Hospital Labs
Krishna Teja Malladi, Snezana Mitrovic Minic, Arash Rafiey,
Ramesh Krishnamurti, Abraham Punnen
TE-04
1 - Continuous Multifacility Ordered Median Location
Problems
Víctor Blanco, Justo Puerto, Safae EL Haj Ben Ali
Larger hospitals have specialized labs to which the samples from
smaller hospitals have to be transferred for testing. A fleet of vehicles
is tasked with transporting the samples that are collected throughout
the day. The sample must reach the destination lab in time. Otherwise,
the patient will be subjected to the repeated sample draw which has to
be avoided at almost any cost. Thus, it happens every so often that a
cab is hired. We have researched this courier problem with the objective to minimize the courier transportation costs and potentially reduce
the number of cab calls.
We propose a general methodology for solving a broad class of continuous, multifacility location problems, in any dimension and with
l_tau-norms proposing two different methodologies: 1) by a new second order cone mixed integer programming formulation and 2) by formulating a sequence of semidefinite programs that converges to the
solution of the problem; each of these relaxed problems solvable with
SDP solvers in polynomial time. We apply dimensionality reductions
of the problems by sparsity and symmetry in order to be able to solve
larger problems.
2 - The Blended Milk Collection Problem using Collection Points
Germán Paredes-Belmar, Andres Bronfman, Armin
Lüer-Villagra, Vladimir Marianov
2 - A Modelling Framework for Solving Restricted Planar Location Problems with Forbidden Regions Using Phi-Object
Murat Oguz, Tolga Bektas, Julia Bennell, Joerg Fliege
We present the blended milk collection problem using milk collection
centers. Different qualities of milk are collected from farms, using
a heterogeneous truck fleet. Each farm produces single quality milk.
Milk is blended in the trucks, and the blend takes the quality of its
lower quality component. Collecting milk form the farthest farms
could have high costs, so collection centers are located for farthest
farms. Trucks visit some of the farms and the milk collection centers,
to which the remaining farmers have brought their milk. A model is
presented and solved using Branch and Cut.
We develop a general modelling framework for the planar location
problem with arbitrarily shaped forbidden regions, where the regions
are modelled using phi-objects. We show that the proposed modelling
framework can be applied to both the median and centre problems. All
instances from the literature on this problem type are modelled with
this framework and solved to optimality. We also introduce and solve
a multi-facility problem instance derived from an archipelago. This
problem is more complex than any instance described in the literature.
3 - Hybrid Metaheuristic for the Vehicle Routing and
Scheduling Problem Featuring Perishability and Capacity Restrictions
Verena Schmid, Alvaro Raul Espitia Rueda
We present a model for a setting to arise in the context of milk collection. Besides dealing with a perishable product, some customers may
only be accessed by vehicles below a maximum weight. Additionally
the capacity of the processing plant is limited. To solve the problem
we decomposed it in 2 parts: a metaheuristic is responsible for finding
promising routing. Any solution may then be post-processed ensuring
feasibility with respect to the plant’s capacity and the product’s life
time. We are able to provide favorable results for this problem variant,
as well as for benchmark instances.
4 - A Two - Objective Mixed Integer Mathematical Model
for the Capacitated Vehicle Routing Problem
Melis Alpaslan, Refail Kasimbeyli
In this study, the capacitated vehicle routing problem with different
types of vehicles is considered where each type has different number
of vehicles. To analyze different cases, a single objective and a twoobjective mathematical models are developed. The single objective
mathematical model deals with minimizing the total route costs while
the two-objective mathematical model also minimizes the total number of vehicle types used. To calculate efficient points of the second
model, different scalarization methods are applied. Both models are
demonstrated on test problems.
5 - Vehicle Routing and Scheduling with Cross-dock
Mohammad Yousef Maknoon, Pierre Baptiste, Gilbert
Laporte
Vehicle routing with cross-dock is a generalization of well-studied vehicle routing problem in which truck loads need to be synchronized.
In this problem, a set of request has to be transferred from an origin to a destination via cross-dock. Previous studies consider no restriction on capability of cross-dock on processing trucks which leads
to infeasible plan. In this problem, we investigate the case in which
cross-docks have limited capacity. We present an adoptive large neighborhood search to solve the problem.
TE-03
Tuesday, 16:00-17:30 - Room 001
Continuous Location (contributed)
Stream: Location
Invited session
Chair: Tsutomu Suzuki
3 - Cyclic Dynamics of Demand Distribution and Facility
Location
Tsutomu Suzuki
Traditional facility location models yields optimal locations of facilities, usually taking accessibility of users into account. Thus the optimal location changes corresponding to changes in demand distribution. This paper provides a spatiotemporal facility location model under cyclic dynamics of demand distribution. The model shows that the
larger range of fluctuation forces us frequent relocation of facilities,
and that the expensive relocation cost requires saving relocation, on
the contrary.
TE-04
Tuesday, 16:00-17:30 - Room 119
Urban Traffic Control
Stream: Traffic Flow Theory and Traffic Control
Invited session
Chair: Jack Haddad
Chair: Konstantinos Ampountolas
1 - Robust Signal-Controlled Road Network Design with
Equilibrium Flow
Suh-Wen Chiou
A robust design of signal-controlled road networked (RONET) system is considered with uncertain travel demand. A bi-level min-max
model is constructed and travel delay can be reduced. A trust-region
cutting plane projection approach (TCPP) is proposed to effectively
solve this problem. A computationally tractable solution scheme is
presented and numerical computations are conducted. Computational
results indicate that the proposed solution scheme TCPP can substantially enhance greater system performance for RONET when compared
to other alternatives while incurring less computational efforts.
2 - Optimizing Traffic Signals and its Consequences for
Traffic in Surrounding Areas
Martin Strehler, Dominik Grether, Theresa Thunig
The optimization of green waves between signalized intersections is
a challenging task as static traffic assignment cannot capture the dynamics required to model the problem. This work presents a cyclically
time-expanded network flow model for optimizing traffic signals and
traffic assignment simultaneously. Optimization results are applied to
a real-world scenario for the city of Cottbus, Germany and tested with
the multi-agent traffic simulation tool MATSim. The impact of the
optimized signals on the city traffic and the surrounding rural areas is
analyzed in detail.
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IFORS 2014 - Barcelona
3 - Analyzing the Shape of the Macroscopic Fundamental Diagram on Grid Urban Networks for Urban Planning Purposes
Javier Ortigosa, Monica Menendez
4 - Solving the Liner Shipping Network Design Problem
using Branch-and-Price
Kristian Thun, Henrik Andersson, Marielle Christiansen,
Magnus Stålhane
In this paper we emulate the dynamics of traffic in three urban grid
networks: two way streets, one way streets, and two way streets with
prohibited left turns. We pay particular attention to the shape (e.g.
height, width, area) of the Macroscopic Fundamental Diagrams (MFD)
obtained. We believe that the characteristics of the MFD can also reveal properties of the network to support urban planning and land use
policies in urban areas. Hence, we analyze in detail this relationship
between urban form and MFD shape and we discuss which should be
the optimal MFD shape in an urban network.
We solve the network design problem in liner shipping to optimality
using a branch-and-price algorithm. The subproblem of finding new
routes is solved using a set of simple heuristics, more advanced metaheuristics/matheuristics, and finally an MIP formulation. We present a
path flow model, discuss the quality of various route-generating procedures, and show results from applying our method to benchmark
instances.
4 - A Time-budget Surplus Maximisation
objective User Equilibrium Model
Judith Y. T. Wang, Matthias Ehrgott
Three-
We propose a three-objective user equilibrium (UE), considering the
three most important factors influencing route choice behaviour in a
road network: travel time, travel time reliability and monetary cost. We
introduce time-budget surplus (TBS) defined as the maximum travel
time budget minus the actual time budget required for a desired level
of travel time reliability. At equilibrium, for each origin-destination
pair, all individuals are travelling on the path with the highest TBS
value among all the efficient paths. This becomes a time-budget surplus maximisation three-objective UE model.
TE-06
Tuesday, 16:00-17:30 - Room 211
Stochastic Modeling in Health Care
Stream: Logistics in Health Care
Invited session
Chair: Jerrold May
Chair: Shannon Harris
1 - On Forecasting Outcomes of a Binary Time Series
Shannon Harris, Jerrold May
TE-05
Tuesday, 16:00-17:30 - Room 002
Optimization in Liner Shipping 1
Stream: Maritime Transportation
Invited session
Chair: Berit Dangaard Brouer
1 - Scheduling of Connections in a Liner Shipping Network Reducing Bunker Consumption while Minimizing Transit Times
Line Reinhardt, Christian Edinger Munk Plum, David
Pisinger, Mikkel M. Sigurd
Every couple of years a liner shipping company may do major changes
to the design of the network implementing new strategies to capture
market shares in upcoming markets. Given a network the scheduling
can be optimized. The scheduling of the network concerns the speed
and berthing times so that transfers are short and the transit time for the
demands are satisfied. We have developed two models for scheduling
minimizing bunker fuel consumption while still satisfying the connection and transit time restrictions of the demand. Results from the two
models are presented and compared.
2 - Liner Shipping Network Design with Transit Times
David Pisinger, Berit Dangaard Brouer, Christian Vad Karsten
The liner shipping network design problem is concerned with the design of a set of cyclic routes for container vessels to transport multiple
commodities. We will present a reformulation of the reference model
from Brouer et al. (2013) to consider transit times for each individual commodity as there is an inherent trade of between the design and
speed of the services (and thus the realized costs) and a competitive
transit time for each commodity in the network.
3 - Feasibility of Shuttle Services in Liner Shipping Networks
Judith Mulder, Rommert Dekker
The growth in container trade has led to substantial increases in ship
sizes, introducing diseconomies of scale in ports. On the other hand,
larger ships benefit from economies of scale at sea. This raises the
question whether container ships should reduce the number of port
calls on a string. In this research, we will investigate whether a shuttle service between two ports is to be anticipated. Thereto, a mixedinteger programming model to determine the joint cargo and ship allocation problem is solved with a shuttle service included in the initial
network.
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We consider forecasting the next outcome of a binary process generated by human behavior, based only on a limited number of its most
recent historical values. The forecast probability is generated using
a linear function whose coefficients are assumed to degrade exponentially through time. We illustrate our approach using data from patients’ attendance and non-attendance at VA outpatient clinics.
2 - RFID-enabled Modeling and Analysis of Care Coordination in Ambulatory Care
Rema Padman, Yi-Chin Lin
Care coordination, a process to manage dependencies between clinicians who provide care to a patient, has been proposed as a critical and
challenging step in improving care delivery and health outcomes. In
this study, we formulate a Markov decision process model to identify
best practice plans that improve care coordination and evaluate it using
a novel data collection strategy that employs RFID technology. 389 office visit records associated with 327 unique patients and 12 clinicians
and staff, collected over a 2-month period, are used to instantiate our
models and identify optimal policies.
3 - Modeling Non-punctual Patients in an Outpatient
Clinic
Luis Vargas, Jerrold May
Outpatient scheduling papers found in the literature, deal with patients
who are punctual. Those who consider the possibility of patients not
being punctual do not provide strategies to schedule early and late arrivals within the developing daily schedule. We consider three types of
patients, early, on time and late arrivals. All information about patients
arrivals and service time is probabilistic. We develop scheduling rules
for each type of patient to decide who should be serviced next when
the patients do not arrive in the order in which they were scheduled.
TE-07
Tuesday, 16:00-17:30 - Room 003
Dynamical Models in Sustainable
Development I
Stream: Dynamical Models in Sustainable Development
Invited session
Chair: Francois Guerrin
IFORS 2014 - Barcelona
1 - Sustainability Performance of Energy Supply Chains
Patricia Rogetzer
A conceptual model of energy supply chains from the perspectives
of electric utility companies and consumers of electricity will be discussed. To improve the carbon footprint, greenhouse gas emissions
(GHG) from the generation of purchased energy (Scope 2) are considered. For a transparent disclosure of sustainability measures taken in
this context, companies increasingly comply with regulatory dynamics following the reporting guidelines of the worldwide standard GRI
(Global Reporting Initiative). In this talk, sustainable operational practices of Austrian energy suppliers are illustrated.
2 - System-Dynamics Analysis of the Belgian Energy
Transition After the Nuclear Shut-Down
Pierre Kunsch
The nuclear phase-out law has been passed in 2003 in Belgium for
closing down between 2015 and 2025 nuclear power plants (NPPs)
producing today more than 50% of the domestic electricity. Green
parties argue that the phase-out would be stimulating renewable energy sources. A system-dynamics model brings rational elements to
the passionate debate, more pertinent than ever after the Fukushima
disaster in March 2011. It appears that the nuclear phase-out according to the foreseen schedule would benefit by priority to fossil energy
sources.
3 - Long-Term Sustainable Optimal Management of Multispecies Stochastic Fisheries
Diwakar Poudel, Leif Sandal, Stein Ivar Steinshamn, Sturla
Kvamsdal
Multispecies management accounts for a number of species and their
physical, biological, and economic interactions. This increases complexity in understanding stock dynamics and optimal catch. To address the issue of identifying optimal catch of stochastic multi stocks,
we have formulated and applied a time-continuous stochastic model.
The model, applied in prey-predator ecosystem, contributes to sustainable yet optimal management of multispecies fisheries. The findings
suggest that the optimal catch for stochastic stocks in a multispecies
ecosystem is different from the deterministic catch.
4 - Simulation Modelling of Human Activities in Agricultural Production Systems
Francois Guerrin
Simulation modelling allows one to assess management scenarios of
agricultural systems. Beyond representing biophysical processes (material flows stemming from crops, animals and the environment) it is
also crucial in such models to account for the farming activities to
which they are tightly coupled. With this aim, it will be presented the
representational features enabling human action to be simulated according to its two dimensions: time (based on Systems Dynamics) and
space (based on Multi-Agent Systems). Integrating both approaches in
a coherent modelling framework will be outlined.
TE-08
Tuesday, 16:00-17:30 - Room 120
Carbon Footprint and Climate
Stream: Energy Economics, Environmental Management and Multicriteria Decision Making
Contributed session
Chair: Jan Kersting
1 - Institutional Level, FDI and Pollution Tax
Salvador Sandoval, Rafael Salvador Espinosa
This work develops a model of environmental economics with corruption, to determine the optimal institutional level that should allow
the government to achieve economic balance of the country under an
oligopolistic pattern of FDI. In addttion, it calculates the optimal pollution tax, the values of which are derived from a series of strategic
environmental policies that aim to maximize the welfare of the domestic country, involving consumers, producers, government and the
dishonest agents working in the public sector. The model includes such
variables in a function of social welfare.
TE-09
2 - Methodology of the Carbon Footprint in the Logistics
Business Operations Applied for Food Manufacturing Companies
Juan Bermeo, Jaime Calderon
In recent years, we heard repeatedly about climate change, generated
by emissions of greenhouse gases to the environment as a result of human activities. This has created concern in companies, taking them to
measure the greenhouse gases emissions. This allow to the company
known as negatively impacting the environment for the greenhouse
gases generation. Under this new scenario, was developed a methodology and a reference model for food manufacturing companies allowing
in a friendly way identify the elements, make an inventory and measure
the basic criteria of the carbon footprint.
3 - Cooperation of Climate Clubs
Jan Kersting
In the search for a solution to the global climate change problem and
in light of the slow process under the UNFCCC, more attention has
recently been paid to the activities of "climate clubs", smaller consortia of countries like the G20 or the Major Economies Forum. We
analyse the question of whether a stable cooperative outcome in these
non-global fora exists. Therefore, we apply the concept of a subgame
of a cooperative game to the setup of Chander and Tulkens (1997) and
show how the existence of a core allocation in the subgame depends
on damage and abatement cost parameters.
TE-09
Tuesday, 16:00-17:30 - Room 121
Decision Dependent Stochastic Problems
and Day-Ahead Forecasting in Energy
Stream: Technical and Financial Aspects of Energy
Problems
Invited session
Chair: Georg Pflug
1 - Decision Dependent Stochastic Optimization Problems
Georg Pflug
We consider a decision problem, where the decision influences the
probability distributions of the stochastic parameters. Several methods of dealing with this problem are known and we review some of
them. Then we present a solution method which is based on the notion
of measure-valued derivatives. An application to a decision problem
in Energy is given.
2 - A Trust-Region Approach for Optimization under
Decision-Dependent Uncertainty
Eric Laas-Nesbitt
We present an algorithmic framework for optimizing stochastic systems with decision-dependent uncertainty. Our approach adapts trustregion methods from deterministic optimization, using the measuretheoretic differentiation concept known as measure-valued differentiation to compute derivatives by simulation. Convergence results will
be demonstrated and the method will be illustrated computationally.
Applications to energy will be discussed.
3 - Forecasting one Day-ahead Household Natural Gas
Consumption with Differently Sized Moving Datasets
using Multiple Linear Regression
Mustafa Akpinar, Nejat Yumusak
In our work, one day ahead forecasting household natural gas consumption is studied with differently sized data. Six models are prepared for this purpose. Each model is named with the number of weeks
included, meteorological data, subscriber amount and holidays. Forecasts have been made for the year 2012. For every new day, the rearmost realized day is removed from the dataset and the last realized day
is added. Multiple linear regression is applied on the data sets differentiating everyday. The fourth model included past four weeks and
shows the lowest mean absolute percentage error.
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IFORS 2014 - Barcelona
4 - New Approaches to Day Ahead Electricity Price Forecasting: MARS and CMARS Models
Gerhard-Wilhelm Weber, Ayse Özmen, Miray Hanım
Yıldırım
High volatility, high frequency and multiple seasonality structures of
the electricity prices are required a short-term and assumption-free
forecasting. Therefore, we used two approaches, multivariate adaptive regression splines (MARS) and conic multivariate adaptive regression splines (CMARS), to forecast day-ahead electricity prices. MARS
and CMARS model complex relationship between variables even for
large data sets without long training progress. These methods are compared with previous studies by using Spanish electricity market data
and yield similar results.
TE-10
Tuesday, 16:00-17:30 - Room 122
Energy Management and Modelling
Stream: Optimization Models and Algorithms in Energy
Industry
Contributed session
Chair: Mel Devine
1 - Techno Economic Model for Adopting Cogeneration
or Conventional Steam Boiler throughout Natural
Gas Penetration
Matan Shnaiderman
This research provides techno-economic model for resolving the
dilemma of adopting cogeneration system or converting diesel steam
boilers burners to natural gas. The profitability of cogeneration plant
depends on energy prices (electricity & natural gas), capital cost, operational strategy and maintenance costs. Optimized design and operational method of cogeneration can cause major differences between
significant energy saving and economic investment disaster. Using
stochastic dynamic programming, we solve this problem.
2 - PRIMES-TREMOVE: A Transport Sector Model for
Long-Term Energy-Economy-Environment Planning
for EU
Pelopidas Siskos
PRIMES-TREMOVE is an EU energy economic transport model combining modeling of microeconomic behaviors concerning distribution
of passenger and freight mobility across transport modes and vehicle
types until 2050. The model is policy and technology rich, while implementing an economic modeling approach. The model solves a complex dynamic equilibrium problem with equilibrium constraints using
a mixed complementarity programming algorithm. Policy assessment
illustrations are drawn from recent model use in the preparation of the
White Paper on Transport in 2011 by the European Commission.
3 - Incorporating Risk Aversion into the Specification of
Efficient Renewable Energy Feed-in Tariffs
Mel Devine, Niall Farrell, William Lee
Many governments incentivise renewable energy generation by offering Renewable Energy Feed-in Tariffs (REFITs). This work compares
the efficiency of a number of REFITs to identify under what conditions a given design may be preferred. This preference is identified by
incorporating both investor and policymaker exposure to risk into the
decision to implement a given tariff. The interactions between policymakers and investors are modelled using a bi-level nonlinear stochastic optimisation model. This talk shall present the methodologies employed, findings obtained to date, and further works.
TE-11
Tuesday, 16:00-17:30 - Room 113
Advances in Combinatorial Optimization
Stream: Combinatorial Optimization
Invited session
Chair: Silvano Martello
136
Chair: Paolo Toth
1 - The Biobjective Capacitated m-Ring Star Problem
Herminia I. Calvete, Carmen Galé, Jose A. Iranzo
The problem consists of finding a set of m simple cycles (rings)
through a subset of nodes of a network. Each ring contains the depot, a number of customers and some transition points. The customers
not in any ring are allocated to nodes in the rings. The rings must be
node-disjoint and are limited by their capacity. The aim is to minimize the ring cost (due to the ring links) and the allocation cost. A
hybrid evolutionary algorithm is proposed to approximate the Pareto
front. Chromosomes provide the nodes in the rings. Feasible solutions
of the problem are constructed by using heuristics.
2 - A Branch-and-Bound Method for Box Constrained Integer Polynomial Optimization
Claudia D’Ambrosio, Christoph Buchheim
We consider the problem of minimizing an arbitrary polynomial subject to box and integrality constraints. We propose a new class of
under-estimators composed of separable functions of the original variables and use it within branch-and-bound scheme to easily and quickly
compute lower bounds. Computational results on randomly generated
instances show good performance with respect to the ones of different
open-source solvers like Couenne, Gloptipoly, and SCIP.
3 - Models and Algorithms for Packing into the Smallest
Square
Silvano Martello, Michele Monaci
We consider the problem of determining the smallest square into which
a given set of rectangular items can be packed without overlapping. We
present an ILP model, an exact approach based on iterated execution of
a two-dimensional packing algorithm, and a randomized metaheuristic.
Such approaches are valid both for the case where the rectangles have
fixed orientation and the case where they can be rotated by 90 degrees.
We evaluate the average performance of the proposed approaches on a
large benchmark, for both cases above, and for the special case where
the items are squares.
4 - Generalized Intersection Cuts from Orthant Interval
Sets
Egon Balas
A new convexification paradigm for mixed integer programming
(Balas and Margot 2011) intersects the extended edges of the LP polyhedron with the boundaries of several lattice-free convex sets, and
uses the resulting intersection points to generate deep cuts in a nonrecursive fashion. In this context, valid cuts can also be generated from
certain nonconvex lattice-free sets. Given two parallel k-dimensional
positive orthants with origins at opposite vertices of the unit cube, the
interval between them is such a nonconvex lattice-free set.
TE-12
Tuesday, 16:00-17:30 - Room 004
Preemptive Project Scheduling and
Resource Leveling
Stream: Project Management and Scheduling
Invited session
Chair: Jürgen Zimmermann
Chair: Julia Rieck
1 - A Column-Generation Approach to Lower Bounds for
Resource Leveling Problems
Christoph Schwindt, Tobias Paetz
We present a method for computing tight lower bounds on the optimum objective function value of resource leveling problems arising in
project management and production scheduling. We consider leveling criteria which can be expressed as linear functions in the execution
times of the precedence order’s antichains. The problem can be stated
as a huge LP with side constraints, whose LP relaxation is amenable
to column generation. The pricing problem corresponds to a convexweight stable set problem on a comparability graph. We report on
computational experience on test sets from literature.
IFORS 2014 - Barcelona
2 - Models and Bounds for Preemptive Project Scheduling with Generalized Precedence Relationships
Tobias Paetz, Christoph Schwindt
We study a resource-constrained project scheduling problem where activities can be interrupted at any point in time and generalized precedence relationships between activities have to be taken into account.
A novel MILP formulation is presented, which encodes a schedule as
a sequence of time intervals with associated sets of activities that are
in progress during the respective interval. We report on the results
of an experimental performance analysis comparing upper bounds obtained by the MILP model and a priority-rule based method with lower
bounds that arise from solving an LP relaxation.
3 - Mathematical Formulations for RCPSP/max-cal
Stefan Kreter, Jürgen Zimmermann
In this talk we extend the RCPSP/max by the concept of calendars.
This problem is denoted by RCPSP/max-cal. Many practicians argue
that calendars have to be taken into account when considering real-life
project scheduling problems because resources like manpower or machines are not available in some time periods. We will present different MIP formulations for the RCPSP/max-cal that are based on timeindexed binary decision variables, methods to reduce the number of
decision variables, and the results of an extensive performance study.
4 - MILP Models for Resource Leveling Problems
Julia Rieck, Jürgen Zimmermann
We consider project scheduling problems subject to general temporal
constraints, where the utilization of a set of renewable resources has to
be smoothed over the planning horizon. In particular, we consider the
classical resource leveling problem, where the variation in resource utilization during project execution is to be minimized, and the overload
problem, where costs are incurred if a given threshold is exceeded. For
both problems, new MILP models and domain-reducing preprocessing techniques are presented. Furthermore, CPLEX is used to solve
instances with up to 50 activities.
TE-14
3 - Feasibility and Optimality Conditions for Setup
Schedule in Uncertain Manufacturing Systems Depend on the Interplay between Setup Logistics and
Perturbation Flow
Jean-Pierre Kenne, Vladimir Polotski, Ali Gharbi
The failure-prone manufacturing system producing two products and
requiring setups for changing the mode is considered. Various hypotheses about the interactions between failure-repair process and
setup logistics were previously used in the literature without clarifications of possible consequences. Both feasibility and optimality conditions are developed and shown to be dependent on the adopted hypothesis. Optimality conditions in the form of Hamilton-Jacobi-Bellman
equations are obtained. Solutions of HJB equations obtained numerically are compared and matched with underlying hypotheses.
4 - Optimal Lot-Sizing with Deterioration and Price Management
Natalia Stepanova, Anna Kitaeva
We consider single-product and single-period lot-sizing problem. The
demand is a steady process with a random batch size. Two models are
presented: 1) at the end of the inventory cycle T the remaining product
needs to be disposal; and 2) the product is to be completely used prior
to time T, and the demand’s intensity depends on the price, remaining
time and inventory. We use a diffusion approximation to the inventory
level process. In case 1) we also obtain the procedure for statistical estimation of the required parameters and design the adaptive algorithm
for multi-period lot-sizing model.
TE-14
Tuesday, 16:00-17:30 - Room 124
DEA Developments
Stream: DEA Applications
Contributed session
TE-13
Tuesday, 16:00-17:30 - Room 123
Handling Uncertainty in Scheduling and
Lot-Sizing 1
Stream: Scheduling
Invited session
Chair: Alexandre Dolgui
Chair: Mikhail Y. Kovalyov
1 - A Unified Modeling Approach for the Static-Dynamic
Uncertainty Strategy in Stochastic Lot-Sizing
Roberto Rossi, Onur A. Kilic, Armagan Tarim
We develop mixed-integer linear programming models to compute
near-optimal policy parameters for the non-stationary stochastic lot
sizing problem under Bookbinder and Tan’s static-dynamic uncertainty
strategy. Our models build on piecewise linear upper and lower bounds
of the first order loss function. We discuss formulations in which the
quality of service is captured by means of backorder penalty costs as
well as non-stockout probability and fill rate constraints. These models
can be easily adapted to operate in settings in which unmet demand is
backordered or lost.
2 - A General Lotsizing and Scheduling Problem with
Stochastic Product Returns
Guillaume Amand, Yasemin Arda
We consider a multi-product capacitated lotsizing and scheduling problem with sequence-dependent setups and stochastic product returns.
The returned products accumulate in an input inventory and can be
sold as new items after a remanufacturing process. The deterministic demand of end items can also be satisfied through a manufacturing
process that is fed by an unlimited source of raw materials. An approximate dynamic algorithm is developed to solve both single-item
and multi-items cases.
Chair: Jens Leth Hougaard
1 - Piece-Wise Linear Cost Efficiency Evaluation
Zohreh Moghaddas, Farhad Hosseinzadeh Lotfi, Mohsen
Vaez-Ghasemi
Following the concept of Cost Efficiency, input and Output quantity
data as well as exact knowledge of input prices at each decision making
units are required. In real-life markets the input prices are not exactly
defined for the DMUs. In this paper we emphasize that the fixed prices
assumption can not reflect the reality of situations because markets will
force lower prices if greater amounts of a product are purchased. This
means discounts are automatically considered. Thus, some modifications in the CE model have been made to consider the situations of real
life markets.
2 - Multi-Directional Program Efficiency: The Case of
Lithuanian Family Farms
Tomas Balezentis, Mette Asmild, Aiste Galnaityte, Jens Leth
Hougaard, Irena Krisciukaitiene
The agricultural sector is important in both economic and social terms,
because it provides inputs for food industry and supports the rural population. Therefore, it is important to develop new methodologies which
can support effective policy making. This paper suggests using Multidirectional Efficiency Analysis (MEA, see Asmild et al., 2003) in connection with estimation of so-called program efficiency (Charnes et al.,
1981). The proposed methodology is applied to analyse farm level data
on Lithuanian family farms.
3 - Likelihood Ranking of Decision Making Units
Markku Kallio, Merja Halme
For DMUs, we assume that the input-output vectors are a random sample of a given probability distribution. For efficiency analysis of the
DMUs, we employ common prices for all DMUs and choose them
based on maximum likelihood estimates. We define the profit based
ranking criterion for each DMU by the likelihood that the random
profit is at most the profit of that DMU. Return based ranking is defined
similarly. We compare both profit and return based ranking methods
with conventional DEA methods using five field studies.
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IFORS 2014 - Barcelona
4 - Technological Superiority
Jens Leth Hougaard, Mette Asmild
We develop a theoretical framework for analyzing technological possibilities. We consider fundamental properties of technology indexes and
demonstrate that previous approaches violate a central axiom dubbed
monotonicity in possibilities. From the axiomatic analysis emerge two
canonical types of indexes: one based on the volume, and one based
on the cardinality of the dominance set. We define a binary superiority
relation where both types of indexes have to point in the same direction
before concluding that one subset is superior to another.
TE-16
Tuesday, 16:00-17:30 - Room 127
Model Selection Methods
Stream: Intelligent Optimization in Machine Learning
and Data Analysis
Invited session
Chair: Ivan Reyer
1 - Multimodelling and Object Selection for Banking
Credit Scoring
Alexander Aduenko, Vadim Strijov
TE-15
Tuesday, 16:00-17:30 - Room 125
Revenue Management with Advertising
Applications
Stream: Revenue Management II
Invited session
Chair: John Turner
1 - Optimizing Online Advertising Budget Allocation
across Multiple Placements
Jian Yang, Pengyuan Wang
Big online advertisers are typically faced with a challenging problem in
campaign management: how to allocate advertising budget across multiple placements in order to maximize Return on Investment (ROI). We
develop a Multi-Touch Attribution (MTA) methodology based on both
observation and experimentation to measure ad effectiveness across
multiple placements. The MTA empowers a simulator that provides
advertisers with what-if analysis for budget allocation. We also build
an optimization model using the MTA results to maximize the total ad
effectiveness for advertisers, and hence their ROI.
2 - A Class of Nonlinear Allocation Problems with Heterogeneous Substitution
Huaxia Rui, De Liu, Andrew Whinston
We study the problem of efficiently allocating multiple types of goods
(workloads) to multiple agents when different types of goods (workloads) are substitutable and the rates of substitutation differ across
agents. We derive theoretical properties of such problems that enable
us to design an extremely fast algorithm called SIMS for solving such
problems. We expect the SIMS algorithm to work well for real-time
applications with time-constrained allocation problems such as the allocation of online advertisement.
3 - The Least Cost Influence Problem
Rui Zhang, Dilek Gunnec, S. Raghavan
We analyze the diffusion process of a product over a social network
while incentives are provided to the individuals. Such catalysation addresses the trade-off of minimizing the amount of incentives given and
reaching a greater number of buyers. This problem is NP-Hard for
general networks. However, we show that it is polynomially-solvable
on tree networks under the assumption that all neighbors of a node
exert equal influence. Next, we propose a totally unimodular integer
programming formulation based on the insight that the influence propagation network must be a directed acyclic graph.
4 - Foundations of Social Network Ad Optimization
John Turner
We introduce revenue optimization models for placing ads in social
networks, motivated by the connectivity structure of the underlying
graph. We discuss some pros and cons of the underlying models, and
illustrate our approach using real social graphs.
To construct a bank credit scoring model one must select a set of informative objects (client records) to get the unbiased estimation of the
model parameters. This set must have no outliers. The authors propose an object selection algorithm for mixture of regression models. It
is based on analysis of the covariance matrix for the parameters estimations. The computational experiment shows statistical significance
of the classification quality improvement. The algorithm is illustrated
with the cash loans and heart disease data sets.
2 - Comparison of Different Clustering Algorithms
Based PCF Classifiers
Emre Çimen, Gurkan Ozturk
In this study we dealt with generating different clustering algorithms
based polyhedral conic classifiers. The main purpose of using clustering algorithms to generate PCF based classifiers is to determine the
number of PCF’s and divide the sets to the smaller parts. By this
way stronger classifiers can be constructed. Expectation Maximization (EM) and k-Means based algorithms are implemented and tested
on well-known literature test problems.
3 - Multicollinearity: Performance Analysis of Feature
Selection Algorithms
Alexandr Katrutsa, Vadim Strijov
We investigate the multicollinearity problem and its influence on the
performance of feature selection methods. The paper proposes the testing procedure for feature selection methods. We discuss the criteria for
comparing feature selection methods according to their performance
when the multicollinearity is present. Feature selection methods are
compared according to the other evaluation measures. We propose
the method of generating test data sets with different kinds of multicollinearity. Authors conclude about the performance of feature selection methods if the multicollinearity is present.
4 - Data Mining Application with Decision Tree Algorithms for the Evaluation of Personal Loan Customers’ Repayment Performances
Aslı Çalış, Ahmet Boyacı, Kasım Baynal
Data mining techniques are used extensively in banking area such as
many areas. In this study, conducted in banking sector, it was aimed
to analysis of available personal loan customers and estimate potential
customers’ repayment performances with decision tree is one of the
classification methods in data mining. In the study, SPSS Clementine
was used as a software of data mining. An application was done with
C5.0 and C&RT algorithms for evaluation of personal loan customers
and the results were compared.
TE-17
Tuesday, 16:00-17:30 - Room 005
Conic Optimization and Applications
Stream: Interior Point Methods and Conic Optimization
Invited session
Chair: Tamás Terlaky
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1 - Hierarchical Cuts to Strengthen Semidefinite Relaxations of NP-hard Graph Problems
Miguel Anjos, Elspeth Adams, Franz Rendl, Angelika
Wiegele
3 - Nonlinear Multi-Objective Constrained Optimization:
Using Second Order Approximation of Pareto Frontier Local Geometry in Descent-Diffusion Approach
Alexis Pospelov, Fedor Gubarev
The max-cut problem can be closely approximated using the basic
semidefinite relaxation iteratively refined by adding valid inequalities.
We propose a projection polytope as a new way to improve the relaxations. These cuts are based on requiring the solution to be valid
for smaller cut polytopes. Finding new cuts creates a hierarchy that
iteratively tightens the semidefinite relaxation in a controlled manner.
Theoretical and computational results will be presented.
Local geometry of the Pareto front allows building efficient algorithms
to discover the frontier. However, in many applications it’s not sufficient to use only linear approximations to optimal variety. In this
work we propose to use second-order local approximation to the Pareto
frontier. Within the descent-diffusion algorithm, presented in supplementary talk, our approach allows efficient discovery of Pareto frontier
even in problems with singular Hessians, where linear approximations
perform poorly because of large number of very small steps.
2 - Specialized Interior Point Methods for Classes of
Random Network Problems
Stefano Nasini, Jordi Castro
The application of optimization based methods in the field of random
graphs represents a novel research area. We consider linear optimization (LO) models of different random graphs and provide procedures to
generate empirical probability distributions of network features. Those
distributions entail the generation of thousands of networks verifying
specific constraints. By exploiting the matrix structure of the resulting
LO problems, it is possible to use a specialized interior-point method
for block-angular problems. Computational results support the high
efficiency of the proposed methods.
3 - A Feasible Direction Algorithm for Nonlinear SecondOrder Cone Optimization Problems
Miguel Carrasco, Alfredo Canelas, Julio López
In this work we present a new feasible direction algorithm for solving
smooth nonlinear second-order cone programs. These problems consist of minimizing a nonlinear differentiable objective function subject
to nonlinear second-order cone constraints. Given an interior point of
the feasible set the proposed approach computes a feasible and descent
direction for the objective function. The search direction is computed
by using a similar formulation to the FDIPA algorithm for nonlinear
programming. We prove global convergence to stationary points of the
minimization problem.
4 - Exact Solutions of the Cell Formation Problem in
Group Technology
Julius Zilinskas, Boris Goldengorin, Panos Pardalos
The Cell Formation Problem (CFP) aims at identification of groups
of machines to form manufacturing cells. The objective function of
CFP is to minimize the intercell moves (exceptional elements in the
block-diagonalized matrix) and within-cell load violation. In this talk
we present our exact branch-and-bound algorithms to solve the CFP.
We report our computational study for solving some benchmark instances of CFP available on either Internet or other publications. Our
comparative analysis shows that our branch-and-bound algorithms are
competitive with many other counterparts.
TE-19
Tuesday, 16:00-17:30 - Room 128
Inventory Planning II
Stream: Demand and Supply Planning in Consumer
Goods and Retailing
Contributed session
Chair: Edward Fox
TE-18
Tuesday, 16:00-17:30 - Room 112
Nonconvex Multiobjective Optimization I
Stream: Multiobjective Optimization - Theory, Methods
and Applications
Invited session
Chair: Julius Zilinskas
Chair: Panos Pardalos
1 - On Optimal Algorithms for Multi-Objective Global
Optimization
Antanas Zilinskas
Theoretical assessment of the efficiency of algorithms for multiobjective global optimization is difficult. Best algorithms can be constructed only for specific classes of problems. In the present paper,
worst case optimal algorithms for univariate Lipschitz functions are
considered. Alternatively, the one variable multi-objective optimization algorithm, which is on the average optimal with respect to a statistical model, is considered. The applicability of the developed algorithms for construction of algorithms of multivariate multi-objective
problems is discussed.
2 - A Deterministic Method to Solve Constrained Multiobjective Optimization
Mikhail Posypkin, Yuri Evtushenko
In the talk we precisely define the notion of an approximate solution
with the given accuracy for constrained multiobjective optimization
problems. Then we present a deterministic method for obtaining an
approximate solution in a finite number of steps under quite natural restrictions on objectives and constraints. The constraints and objectives
are allowed to be non-linear and non-convex. The talk also discusses
some implementation issues and practical applications of the proposed
method.
1 - Joint Optimization of Maintenance and Spare Part Inventory Policies
Z. Pelin Bayindir, Pinar Bulbul, Ismail Serdar Bakal
In this study, we consider maintenance planning and spare part inventory planning problem simultaneously. Our main focus is the joint
optimization of preventive replacement and spare part inventory management. We propose an exact dynamic programming algorithm and
several heuristics for a finite planning horizon situation. In a computational study the heuristics are compared against the optimal solutions.
2 - An Enhanced Model for Integrated Replenishment
and Transportation Problem in a Dynamic Demand
Environment
He-Yau Kang, Amy H. I. Lee, Li-Hao Huang
This research considers an integrated replenishment and transportation problem, and the objective is to minimize total costs under the
requirement that no inventory shortage is allowed in the system. The
integrated replenishment and transportation problem is formulated as
a mixed integer programming model. An efficient genetic algorithm
model is constructed for solving large-scale lot-sizing problems. The
results demonstrate that the proposed two models are effective and accurate tools for determining the replenishment of high-tech industries
from multiple suppliers for multi-periods.
3 - Inventory Models with Non-Stationary Transition
Probabilities to Determine the Optimal Mix of Owned
and Rented Items
Leonardo Epstein, Eduardo González-Császár
Inventory models with rental items help plan operations that involve
rental items, such as trucks to ship containers or telephone lines to
carry calls. A service provider who plans to buy an inventory of items
for rental may find that the cost of the number of items to buy is too
high to meet demand with certainty. Thus a smaller inventory, insufficient to meet demand, may be preferable if the service provider can
obtain items by renting them from another provider. Typically, rented
items have a larger operational cost than owned items, but do not require the investment to purchase them.
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4 - A General Approximation to the Distribution of Count
Data with Applications to Inventory Modeling
Edward Fox
1 - Gas Transport Network Simulation and Optimization
Ángel Manuel González Rueda, Alfredo Bermúdez, Julio
González-Díaz, Francisco José González-Diéguez
We derive a general approximation to the distribution of count data
based on the first two moments of the underlying interarrival distribution. The resulting variant of the BISA distribution is similar to the
lognormal, but fits simulated and empirical data better than the lognormal in many applications. Moreover, although the BISA can be fit to
count data, it can also be fit directly to interarrival data. In numerical experiments involving dynamic inventory models, we compare the
BISA distribution to other commonly-used distributions and show that
it leads to improved stocking decisions.
Reganosa is a company that manages a regasification plant into the
Spanish gas transport network and, thus, its main function is to supply
natural gas to the network. It is important to manage the gas network in
an efficient way to minimize the consumption in compressor stations.
This is one of the main optimization problems that we have studied
in this field, typically ensuring the security of supply. We have developed a software, called Ganeso, to solve this kind of problems that has
allowed Reganosa to improve its strategic positioning in the gas sector.
TE-20
Tuesday, 16:00-17:30 - Room 129
Stochastic Optimization in Energy
Infrastructure Planning
Stream: Stochastic Optimization in Energy
Invited session
Chair: Yueyue Fan
1 - A Stochastic Programming Model for Renewable Energy Infrastructure Planning Considering Oligopolistic Competition
Yueyue Fan
This paper presents a mathematical model that supports renewable energy infrastructure planning under uncertainties. The interdependency
between different stakeholders in the system is captured in an energy
supply chain network. Competition between different renewable energy investors, who compete for resources, transmission capacities,
and demand markets, is modeled using variational inequalities. Creative solution algorithm is developed by establishing similarity between the energy problem and the traffic network equilibrium problem
that has been well studied in transportation literature.
2 - Impact of Electricity Pricing Policy on the Investment
of Renewable Energy
Safak Yucel, Gurhan Kok, Kevin Shang
We study the effect of time-based pricing policies on renewable energy investment. In contrast with the expectations of policy makers, we
show that flat (time-invariant) pricing policy leads to a higher level of
renewable energy investment for utility firms and independent power
producers.
3 - Stochastic Project Scheduling for Wind Farm Installation
Diclehan Tezcaner Ozturk, Euan Barlow, Kerem Akartunali,
Matthew Revie, Sandy Day, Evangelos Boulougouris
The installation process of an offshore wind farm involves several tasks
to be scheduled in advance. However, planned schedules are affected
by many external uncertainties such as weather conditions and vessel
availability. In this study, we develop a stochastic rolling horizon optimisation model to plan the installation schedule, where the installation
process is based on the input from three industry partners. Our model
yields a robust project schedule considering all the uncertainties and
revises the schedule at predetermined times to minimise the deviation
from the baseline schedule.
TE-21
Tuesday, 16:00-17:30 - Room 006
Lessons from Industrial Collaboration
Stream: OR Consultancy and Case Studies
Invited session
Chair: John Ranyard
140
2 - Computing Stoichiometric Matrices in Chemical Reactions. An MINLP Problem
Emilio Carrizosa, Rafael Blanquero, M. Asuncion
Jimenez-Cordero, Boglárka G.-Tóth
We consider the problem of determining the coefficients of a stoichiometric matrix and rates so that the concentrations of a series of species
give a best-possible fit to empirical concentrations. Finding the fit
amounts to solving an MINLP, in which nonlinear differential equations appear in the constraints. A heuristic is proposed, and its behavior
is tested in benchmark data sets.
3 - Simulation Tools for Railway Planning
Ricardo Garcia-Rodenas, Jose Luis Espinosa-Aranda
This work presents the experience in the collaboration between the
UCLM, UPM and US universities of Spain and RENFE (the main
Spanish railway provider) participating in the PT-2007-003-08CCPP
project granted by the Ministry of Development of Spain. This collaboration led to successful results developing various models, research
papers and software tools focused on the robust planning and the management of railway transport in case of emergencies, but failed in the
final objective of implementing all this new knowledge in the railway
company for reasons outside of control of the research group.
4 - Logistic Report on the Location of an Agricultural
Processing Plant
María José Ginzo Villamayor, Julio González-Díaz, Balbina
Casas-Méndez
Biocen is dedicated to the reuse of wood ash produced by wood industry as organic fertilizers, which are used in forest crops, organic farming and traditional farming. The problem was on finding the place for
the plant keeping in mind the transport needs of the wood ashes from
the suppliers to the plant and the later distribution of fertilizer to customers. The Weiszfeld algorithm was used to solve the problem. We
got a logistic map that provides the optimal location of a production
plant based on the location of suppliers and customers of the company
Biocen.
TE-22
Tuesday, 16:00-17:30 - Room 007
Cooperation and Competition in
Operations Management
Stream: Game Theory and Operations Management
Invited session
Chair: Alf Kimms
Chair: Ana Meca
Chair: Igor Kozeletskyi
1 - Retailer Assortment Strategies to Induce Manufacturer Competition
Sebastian Heese, Victor Martínez de Albéniz
We compare different assortment planning strategies that differ in how
much information the retailer passes on to the manufacturers. We find
that it is usually best to pre-announce the assortment breadth but not
to declare which manufacturers are included, as opposed to requesting
bids from all candidates selected in the assortment. Compared to the
assortment breadth that a centralized system would choose, a retailer
that announces just the assortment breadth might benefit from artificially limiting the assortment to increases manufacturer competition.
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2 - Quality Gatekeeping at the Retail Level: Implications
for the Role of Retailers in Quality Assurance
Mingming Leng
3 - From Community Concerns to Societal Risk Perception
Xijin Tang
We investigate a manufacturer-retailer channel to explore the role of a
retailer in assuring the quality of a manufacturer’s product as a quality
gatekeeper. We show that any increase in the manufacturer’s penalty
payment to the retailer may not be helpful in encouraging the manufacturer to decrease his defective rate. The retailer’s gatekeeping activity may not induce the manufacturer to reduce his defective rate,
which depends on the two firms’ relative market powers, their penalty
costs incurred when consumers return defects, and their quality control
costs.
In current China social stability is emphasized to develop a harmonious
society by the government. A number of social indicators contribute
to measure the societal state. Most of them require conducting timeconsuming surveys on social attitudes. As search queries, BBS posts
and even microblogs reflect the community concerns timely and more
truly, we explore to correspond the hot search words, BBS posts or
even microblogs with societal risks, and then to measure the on-line
societal risk levels every day. Such an approach provides additional
measures toward societal states.
3 - A Multi-Objective Allocation Problem in the Cooperative Traveling Salesman Problem with Rolling Horizon
Igor Kozeletskyi, Alf Kimms
4 - Driver Attention for Information Display on Variable
Message Signs with Graphics and Texts
Chien-Jung Lai, Chi-Ying Wang
In this presentation a case of horizontal cooperation among salesmen is
considered, where besides the minimization of total costs every salesman aims to maximize his own utility from assigned orders. The goal
is to find a stable allocation of costs and orders. We present a gametheoretic approach using the core concept for the allocation problem
and a solution procedure for arising optimization problems. The solution procedure is based on methods of multi-objective optimization in
combination with mathematical programming techniques and its performance is tested using a computational study.
4 - Revenue in Contests with Many Participants
Arieh Gavious
We show that in a contest with a single prize, the expected effort made
by the kth highest valuation participant bounds the sum of the expected
efforts made by all of the participants with valuations less than the
kth highest valuations.Wealso show that in the limit case of a contest
withmprizes, the expected effort made by the kth highest valuation participant when the bidders are risk-neutral is greater than the expected
effort in the risk-averse case.
The purposes of this study were to discuss response effect and driver attention for information display and position on Variable Message Signs
(VMS) with graphics and texts. A 234 within-subjects design using a
simple driving simulator was conducted. The independent variables
were Changeable Graphic Sign (CGS) information, VMS information,
and position of VMS. The results showed that CGS information, VMS
information, and position of VMS were significant for most of the participants’ response time, fixation time and fixation frequency.
TE-24
Tuesday, 16:00-17:30 - Room 212
Operations Finance Interface 2
Stream: Operations Finance Interface
Invited session
Chair: Anne Lange
TE-23
Tuesday, 16:00-17:30 - Room 008
Analysis of Human Behavioural Data and
Knowledge
Stream: Behavioural Operational Research
Invited session
Chair: Chien-Jung Lai
1 - Analysis of an Artemisia-Based Malaria Medicine
Supply Chain
Scott Webster, Burak Kazaz, Prashant Yadav
Artemisinin Combination Therapy, the most effective malaria treatment today, is manufactured from an agriculturally derived starting
material. We present a model of the supply chain that captures the
effects of such factors as available farm space, manufacturer capacity, farmer’s self-interest, volatility in crop yield, and volatility in the
malaria medicine market on such measures as the level and volatility
of medicine price and supply.
1 - A Decision Framework for Using Mood as Context in
Recommender Systems
Sanjog Ray
2 - Franchise Contracting with Debt Financing and
Bankruptcy Risk
Vlad Babich, Christopher Tang
We provide a framework based on two dimensions to help recommendation engine designers select the appropriate domains for integrating
mood as contextual data. The two dimensions are time to consume
[TTC] and familiarity [FAM] required to effectively consume the product. Both dimensions have two levels high and low, resulting in four
quadrants. We propose that only domains that fall into the first quadrant, i.e., where both TTC and FAM is low should use mood as contextual data in their recommendation systems algorithms. We also show
results of experiment to validate the framework.
We study how franchise contract should account for the entrepreneur’s
financing need, the bankruptcy probability, and bankruptcy costs, using
a stochastic dynamic game among the franchisor, the entrepreneur, and
the banks. The franchisor chooses contract terms. The entrepreneur
dynamically decides when to open a franchise store (obtaining debt financing). The bank determines competitive equilibrium loan rates, accounting for bankruptcy risk. The ramifications of ignoring financing
considerations are delays in a store opening and higher entrepreneur’s
bankruptcy probability.
2 - Analysis of Commercial Vehicle Operation Data for
Driving Safety Enhancement
Kwang-Jae Kim, Minjun Kim, Chiehyeon Lim, Kyungim
Choi, Jinwoo Jeon
3 - Wine Futures and Advance Selling under Quality Uncertainty
Burak Kazaz, Tim Noparumpa, Scott Webster
Digital tachograph (DTG) is a device installed on a vehicle that records
its operation data. The Korean government maintains a database (DB)
which contains the operation data of commercial vehicles. We are conducting a research project for driving safety enhancement using this
DTG DB. In this presentation, we discuss the analysis of the DB to
extract the relationship between driving patterns (such as speed, rapid
accelerations and decelerations, breaks on or off) and accident rates.
The analysis results can be used in developing service models for driving safety enhancement.
We examine the use of wine futures as a form of operational flexibility
to mitigate quality risk in wine production. While aging in the barrel, wine receives a barrel score indicating its potential quality. The
winemaker then determines (1) the percentage of its wine to be sold as
futures and (2) the price of wine futures. When wine is bottled, it receives another review called a bottle score. Using data from Bordeaux
wineries, our study provides insights into how barrel scores, consumer
preferences and the winemakers’ preferences influence the allocation
and pricing decisions.
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TE-25
Tuesday, 16:00-17:30 - Room 009
Data Mining via Pattern Analysis and
Recognition
Stream: Data Mining
Invited session
Chair: Onur Seref
1 - Urban Bus Transit Boarding Pattern Analysis and
Route Planning for the Disabled
Deniz Türsel Eliiyi, Uğur Eliiyi
We focus on planning exclusive bus routes for the disabled users of
a multimodal transportation system, where bus passengers comprise
about 66% of the overall 1.5 million average daily boardings. Passenger demand is analyzed via a route-based alighting point estimation
model, based on smart card boarding data of the disabled users and
their attendants. Trip patterns are investigated for the purpose of determining new fixed routes and their schedules, as well as special fleet
capacities of paratransit service requests. Model results are analyzed
in comparison with registered passenger database.
2 - Causal Inference with Simultaneous Outlier Detection and Removal
Erhun Kundakcioglu, Mohammad Poursaeidi
This study presents a novel pattern recognition framework where we simultaneously detect and remove outliers, and perform regression. Our
goal is to draw causal relations and identify relevant features in cases
where outliers are most abundant such as and multiple-instance and
time-series data. We propose an integer programming formulation that
eliminates effects of outliers on the regression loss function, prove that
the problem is NP-Hard, and propose a heuristic solution approach that
outperforms available forecasts on a time-series data set.
3 - Rule Mining in Critical Node Detection
Dionne Aleman, Mario Ventresca
The critical node detection problem (CNDP) is the problem of identifying nodes in a graph whose deletion causes the network to be maximally disconnected, and has several applications. While CNDP is NPHard, algorithms with reasonable performance exist. However, implementation of CNDP results can be challenging as nodes in the graph
may imperfectly represent the real word. We therefore investigate mining CNDP results to obtain rules that can be followed to remove nodes
without requiring exact graph structure knowledge. Results are shown
for a 5 million-node contact network for vaccine planning.
4 - A Computational Rhetoric Framework for Mining Online Stock Commentaries
Onur Seref, Michelle Seref, Alan Abrahams
We develop a computational rhetoric methodology that combines data
mining, machine learning, and natural language processing to analyze
rhetorical moves in online stock pitch arguments of players from an
online investment game. We derive predictive models to determine
a player’s stock prediction accuracy and the influence of their stock
prediction in their online community. We compare our framework to
conventional text mining methods to highlight the contribution of our
computational rhetoric approach.
1 - A New Bundle Method for Nonsmooth DC Optimization
Kaisa Joki, Napsu Karmitsa, Marko M. Mäkelä
In nonsmooth nonconvex optimization, functions do not need to be
differentiable. These types of problems arise for example in computational chemistry and biology. At the moment, bundle methods are
considered to be efficient and reliable methods for these problems. I
will introduce a new bundle method for the unconstrained nonsmooth
nonconvex minimization of a function which can be presented as a difference of two convex functions. The benefit of DC functions is that
we can still utilize convex analysis and optimization to some extent.
Some numerical experiments will also be presented.
2 - Numerical Methods for Solving Nonsmooth Optimization Problems with Known Structures
Adil Bagirov
In this talk, we present numerical methods for solving nonsmooth
nonconvex optimization problems with given structures. These problems include the minimization of difference of (nonsmooth) convex
functions and problems where the objective function is represented
as a smooth composition of nonsmooth functions. The proposed algorithms use different generalizations of a subdifferential. We report
results of numerical experiments using well-known nonsmooth optimization test problems.
3 - Piecewise-Concave Minimization via Nonconvex
Bundle Local Searches
Giovanni Giallombardo, Manlio Gaudioso, Giovanna
Miglionico
We focus on the numerical solution of minimization problems where
the objective function is the maximum over finitely many concave
functions, not necessarily differentiable. We present a tailored bundlelike method whose termination at a point satisfying an approximate
stationarity condition is guaranteed. Next we discuss on how to embed
such a local-search method into heuristic approaches for escaping from
local minima, and provide numerical results on some sample problems.
4 - A New Bundle Method for Sparse Problems
Napsu Karmitsa
Many practical optimization problems involve nonsmooth functions
with thousands of variables. Fortunately, these functions often have
some underlying structure that can be utilized to better solve these
problems. In this talk, I describe a new bundle method for large-scale,
possible nonconvex, nonsmooth minimization. The method combines
the limited memory bundle method with sparse updating of matrices.
The preliminary numerical experiments to be presented confirm the
effectiveness of the method.
TE-27
Tuesday, 16:00-17:30 - Room 213
Pricing Decisions
Stream: Operations/Marketing Interface
Invited session
Chair: Mualla Gonca Yunusoglu
TE-26
Tuesday, 16:00-17:30 - Room 010
Nonconvex Nonsmooth Optimization
Methods
Stream: Nonsmooth Optimization and Variational Analysis
Invited session
Chair: Napsu Karmitsa
142
1 - Strategic Pricing Decisions for Competing Suppliers
Basak Altan, Ali Ekici, Okan Ozener
We study a duopolistic market of capacitated suppliers competing for
the business of a single retailer for a single product with a synergy in
joint procurement. We study this market under two settings: asymmetric and symmetric information. We show that a supplier might set a
"threshold price" to capture the entire market if its per unit fixed ordering cost is sufficiently small. We establish that there exists a joint-order
Nash equilibrium only if the suppliers set identical prices low enough
to make the retailer order full capacity from both.
IFORS 2014 - Barcelona
2 - Pricing Warranty for Online Retailers
Lei Guan
Nowadays, many online retailers provide extended warranty for 3C
products. The price for the extended warranty is according to the
length of the warranty. In this article, we study how to pricing the warranty for online retailers by introducing the consumers’ choice. We
first consider the case that there is only one period of warranty and
show the optimal result. Then we extend the basic model by considering two periods or jointly optimizing the retail price and the warranty
price. In addition, we provide some numerical experiments to give
more insights on our model.
3 - Dynamic Pricing for Perishable Products in the Presence of Customer Behaviour
Elif Dogdu, Derya Eren Akyol
In recent years, there has been an increasing interest in using dynamic
pricing policies in various industries, where the capacity is fixed in
the short-term and perishable. However, there have been limited studies that consider the impact of purchasing behavior of customers on
the seller’s pricing decisions. In this study, we review the literature
on dynamic pricing in perishable inventory systems and propose a dynamic pricing strategy for inventory management of perishable products. Then, we present the simulation results for different scenarios
with different customers behaviour.
4 - A Dynamic Pricing Strategy under Supplier Disruptions
Mualla Gonca Yunusoglu, Derya Eren Akyol, Gokalp Yildiz
In this study, a dynamic pricing strategy is proposed to prevent possible stockouts during supplier disruptions. We consider a single retailer
that replenishes its inventory from two vulnerable suppliers. The retailer uses a base stock policy to control its inventory level and a dynamic pricing strategy to effectively satisfy customer demand during
disruptions. The effectiveness of the proposed strategy is tested via a
simulation model under different cost and disruption scenarios. The
results reveal that the proposed pricing strategy performs better compared to static pricing strategy.
TE-29
3 - A Mean-Risk Model for the Stochastic Traffic Assignment Problem
Nicolas Stier-Moses, Evdokia Nikolova
We explore how stochastic travel times and risk aversion transform the
traditional traffic assignment problem and its equilibrium concepts. In
this setting, even computing user best responses has unknown complexity. This talk focuses on equilibrium existence and characterization in the settings of infinitesimal vs. atomic users and fixed vs.
congestion-dependent variability of travel times. We show that equilibria always exist in most of those combinations. Although paths are
necessary to describe them, we see that few paths suffice. Finally, we
estimate the cost imposed by risk-aversion.
4 - Dynamics in Composite Congestion Games
Cheng Wan, Sylvain Sorin
In a network composite congestion game, two types of players
(nonatomic ones of weight zero and atomic splittable ones with positive weight) coexist. This work considers dynamical aspects, i.e. the
evolution of the strategies at disequilibium states. Players adjust strategies in a selfish and myopic way. The evolution of the strategy profile is
described by a continuous-time dynamical system. One shows that several dynamics well-known in the framework of population games can
well be adapted to this general framework with heterogeneous players.
Their asymptotic properties are analysed.
TE-29
Tuesday, 16:00-17:30 - Room 011
Multiple Criteria Decision Making and
Optimization 5
Stream: Multiple Criteria Decision Making and Optimization
Contributed session
Chair: Evangelos Grigoroudis
TE-28
Tuesday, 16:00-17:30 - Room 130
Congestion Games: Dynamics and
Algorithms
Stream: Dynamic and Repeated Games
Invited session
Chair: Cheng Wan
1 - A Lemke-Like Algorithm for the Multiclass Network
Equilibrium Problem
Thomas Pradeau, Frédéric Meunier
We consider a nonatomic congestion game on a connected graph, with
several classes of players. Each player wants to go from its origin vertex to its destination vertex at the minimum cost and all players of a
given class share the same cost functions on each arc. The computation
of an equilibrium in the multiclass case is an open problem for general
functions. We consider the case where the cost functions are affine and
propose an extension of Lemke’s algorithm able to solve this problem.
At the same time, it provides a constructive proof of the existence of
an equilibrium in this case.
2 - Risk Measures and Shortest Paths in Network Games
Roberto Cominetti, Alfredo Torrico
Modeling risk-aversion in routing games using mean-stdev, VaR and
CVaR, has significant drawbacks: high computational complexity, lack
of monotonicity, dynamic inconsistency. We show that the only measures that avoid these limitations are the "entropic risk measures". For
independent link travel times, entropic-optimal paths reduce to standard shortest paths which can be computed efficiently and allow to
study atomic and non-atomic routing games. We discuss some open
questions on travel time correlations, heterogeneity in risk perceptions,
and adaptive dynamics.
1 - Elicitation of a Model of Map Comparison Taking into
account Geographic Aspects
Valérie Brison, Marc Pirlot
We have developed several models to help a decision maker to compare maps representing the state of a region at different stages of its
evolution. One of these allows taking some geographic aspects into
account. This model combines additive value function and expected
utility models. In this work, we provide an interactive elicitation process to determine all the parameters of the model. For this purpose, we
transpose the method of lotteries comparison. We interpret lotteries
as maps and we formulate questions to the decision maker in terms of
comparisons of well-chosen maps.
2 - Fuzzy Multi-Criteria Group Decision Making: A Case
of Art Students’ Placement in Undergraduate Art Programs
V. Alpagut Yavuz
Selecting art students from a number of competing candidates is a decision making process that requires a group of decision makers evaluating a two-stage performance exam. Fuzzy Analytic Hierarchy Process (FAHP) is one of the methods suggested for multi-criteria decision making (MCDM) involving group decisions and fuzziness. In this
study, art students’ placement process in undergraduate art programs is
modeled as MCDM problem and FAHP method is used in determining the decision makers’ weights of criteria. Rankings of the candidate
students are determined by TOPSIS method.
3 - Towards a Multi-Objective Capital Allocation within
Data Centres
Takfarinas Saber, Anthony Ventresque, Xavier Gandibleux,
Liam Murphy
Data Centre Capital Allocation is often based on different combinations of distinct objectives, hence it can be defined as a multi-objective
optimisation problem. In this paper, we present different techniques
for addressing this problem, and an experimental evaluation on different sized data centres. Our results show that PLS provides many
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localised solutions while NSGA-II provides few solutions, and is sensitive to the quality of the initial set of seed solutions. We propose a
modified version of GRASP that addresses these deficits by offering a
large number of distinct solutions.
4 - Modeling Additional Information in the MUSA
Method: A Robust Extension
Evangelos Grigoroudis, Nikolaos Matsatsinis, Nikolaos
Matsatsinis
The MUSA method is a collective preference disaggregation approach
following the main principles of ordinal regression analysis under constraints using linear programming techniques. This study presents an
extension of the MUSA method based on desired properties of the inferred preference system, as well as additional customer preferences.
The main aim of the study is to show how incorporating these additional constraints in the linear program of the original MUSA method,
the robustness of the estimated results may be improved.
TE-30
Tuesday, 16:00-17:30 - Room 012
Recent Models on Emerging Optimization
Problems
Stream: Allocation Problems in Game Theory
Invited session
Chair: Takako Yamada
1 - An Ant Colony Optimization Algorithm for the Daily
Photograph Selection Problem of Earth Observation
Satellites
Sezgin Kilic
This paper proposes an ant colony optimization (ACO) algorithm for
the daily photograph selection problem (DPSP) of earth observation
satellites (EOSs). DPSP is an NP-hard optimization problem related
to management of EOSs. Each photograph related to a customer order
generates a profit but not all of the requests can be satisfied due to various constraints. The proposed algorithm inherits the hyper-cube framework of ACO metaheuristic. Realistic instances are used as benchmark
problems. Computational results demonstrate that the proposed algorithm is capable of generating competitive solutions.
2 - A Fuzzy-QFD based Mathematical Model for Sustainable Supplier Selection
Zeynep Gergin, Fadime Üney-Yüksektepe, Nur Nazlı Şen,
Gökhan Kılıç
This study is an integration of sustainability concept with supplier selection activities in a dairy products manufacturing company. Initially
expectations from the suppliers are identified. Then, based on the sustainable supplier selection criteria of related literature, evaluation factors are determined. These factors are correlated with the expectations,
and ranked by using Fuzzy-Quality Function Deployment methodology. Finally, the data obtained from the House of Quality is input to a
mathematical model, and optimum suppliers with respect to their sustainability performances are proposed.
3 - Characteristic Analysis and Modeling of User Tweet
Behavior on a Consumer-Insight Rating Website
Takako Yamada, Masashi Taguchi
We analyzed 170000 tweets data obtained from a web site’s
(https://www.uranokao.jp) visitors. At this web site, the users are classified into 17 types according to their response patterns to 35 questionnaires where each user type suggests consumer insight.We explored
user site access process over 6 months and how users are induced to the
website via their follow-follower networks. By observing user tweets,
we found a specific user cluster exists in an intensive access-period.
Based on our findings, we propose an user influence model on social
networks.
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Tuesday, 16:00-17:30 - Room 013
Topics in Decision Processes
Stream: Decision Processes
Invited session
Chair: Manel Baucells
Chair: Antonio Jiménez-Martín
Chair: Walter Gutjahr
1 - Expected Utility and Narrow Framing
Manel Baucells, Rakesh Sarin
We examine conditions under which monetary decisions made in isolation provide an optimal strategy. We offer a direct proof that only
logarithmic utility permits narrow framing in the presence of learning.
Without learning but allowing for probabilities to vary from period to
period, we provide a direct proof that only CRRA utility is robust to
narrow framing. The class of linear risk tolerance, which includes exponential utility, is robust to narrow framing when the payout distribution is identical in all periods and there is no risk of bankruptcy.
2 - Selecting Preventive, Palliative and Fault Transmission Safeguards for Risk Management of Information
Systems: A Fuzzy Approach
Antonio Jiménez-Martín, Eloy Vicente, Alfonso Mateos
We focus on the selection of safeguards in fuzzy risk analysis and management for information systems (IS). Preventive, palliative and fault
transmission safeguards have to be identified to reduce risks in the IS
and a safeguard selection process has to be performed since safeguards
have associated costs. The aim could be to select the safeguards that
minimize costs while keeping the risk within acceptable levels or minimizing the maximum risk for a given budget. We propose a dynamic
programming-based method and the use of metaheuristics to tackle the
corresponding optimizations problems.
3 - A Competitive Covering Tour Problem in Disaster Relief
Christian Burkart, Walter Gutjahr, Pamela Nolz
We consider the problem of designing the logistic system for distribution of relief aid in a drought disaster. The beneficiaries do not relocate
and walk to distribution centers. A competitive, multi-objective Covering Tour Problem aims at minimizing (i) uncovered demand and (ii)
costs. A competitive location model models the beneficiaries decision
on where to go to (if at all), so demand can be met in the right places
and quantities. We use a genetic algorithm and compare the solutions
to the exact Pareto front with the Hypervolume Indicator, using data
from Gaza, Mozambique.
4 - Decision making in the chaotic environment of first
response to disasters
Kate Hughes
Decision making in chaotic contexts is difficult and requires exploratory investigation for preliminary identification and understanding of the issues before more positivist methods can be employed. This
study of decision making supply chain managers takes an interpretivist
approach in order to gain contextual understanding of the elements
that help - and those that hinder — the ability to make assessments and
evaluate action in the emergency phase of disaster management. This
information can then be extended for further research using methods
that employ quantitative data for analysis.
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Tuesday, 16:00-17:30 - Room 014
Data Mining Applications and Applied
Probability
Stream: Data Mining, Knowledge Discovery and Artificial Intelligence
Contributed session
Chair: Rosangela Villwock
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1 - What Drives Strategic Deviance in a Nascent Industry? Evidence from Big Data
Kyung Min Park, Bokyung Lee
Utilizing big data accumulated on social media such as twitter and
blogs, we investigate public opinions on a nascent industry such as
daily deal shopping industry. This study demonstrates how the industry level legitimacy and performance feedback-based learning affect
the degree of firms’ strategic deviance. We describe key properties of
industry legitimization and de-legitimization process through analyzing public discourse and social comparison among firms. An analysis
of daily deal sites in Korea supports our main theoretical expectations.
2 - Diagnosis and Prediction of Equipment Fault using
the Probability Model
Inseok Lee, Sung-Shick Kim, Jun-Geol Baek
To reduce manufacturing cycle time and production costs, predicting
the abnormal state of the equipment is highly important. Causes of
fault are various and complicated. We defined these hazard factors as
each probability model. Through these probability models, we make
the probability model to predict and diagnose the equipment fault. To
calculate the probability by using the time event data, we propose survival analysis. This method is statistical data analysis by using time
until an equipment fault occurs. Throughout the experiment, we expect a better diagnosis and prediction.
3 - How to Use Regression Method Properly
Syed Shahabuddin
Forecasting is a critical tool for making sound futuristic decisions.
Forecasters can use time series or regression methods to forecast. Regardless of the method, one must follow the required rules of the
method to make an accurate forecast. Unfortunately, some forecasters
do not know the rules, ignore the rules, or implement them partially.
Thus, most forecasts are inaccurate. Instead of blaming themselves,
they blame the method. My paper discusses the required rules associated with regression and shows quantitatively the consequences of
ignoring, violating, or partially implementing them.
4 - Dynamic Pricing and Demand Learning for an Online
Retailer
David Simchi-Levi
We present an implementation of dynamic pricing strategy for an online retailer. The challenge facing the retailer is that most products
have short sales windows and high demand uncertainty. To address this
challenge, we develop a two-stage pricing strategy: first, a clustering
method identifies several potential demand functions; then, a dynamic
pricing algorithm learns demand and adjusts price on the fly. We show
a theoretical performance guarantee and numerical experiments of the
algorithm.
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Tuesday, 16:00-17:30 - Room 015
Defence and Security Applications IV
Stream: Defence and Security Applications
Invited session
Chair: Ana Isabel Barros
1 - The Framework of the Decision-Making Support System for Joint Operations
Chifei Zhou
A new decision-making support system (DMSS) is researched for joint
operations. The DMSS is focused on the proceeding of joint operations
to support user’s decision making process in the large-scales, complex
and dynamic environment. The DMSS consists of geographical interfaces, analyses tools and an assistant plan, that helps users solve issues
quickly.
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2 - Creating Real Time Intelligence
Ana Isabel Barros, Jeroen Wevers, Bob van der Vecht, Hans
van Dalen
In order to produce reliable and up to date intelligence in support of
current military operations there is a need for (near) real time analysis of threat. This presentation addresses a framework to support intelligence analysts and operators in collecting, processing information
from different sources, in order to constantly carry out (near) real time
prediction of the likelihood of threats over space and time.
3 - Information Retrieval Customized for Intelligence
Collection
Ned Dimitrov
Intelligence processors are faced with a glut of information. Typically,
their job consists of sifting through thousands of intelligence reports,
to compile the data relevant to their query. We create custom information retrieval algorithms for the intelligence collection setting. Unlike
the algorithms used by modern search engines, our algorithms exploit
knowledge of the interest, experience, and organization of the user to
guide their search for relevant information.
4 - Development of Terrorist Threat Prediction Model in
Indonesia by using Bayesian Network
Hilya Arini, Nur Masruroh, Budi Hartono
There are more than 20 terrorist threats from 2002 to 2012 in Indonesia. However, study to build preventive solution to counter terrorist
has not been conducted. This study aims to build prediction model
of terrorist threat in Indonesia by using Bayesian network. This study
finds several significant findings. First, news and the readiness of terrorist group are the most influent factor for conducting terrorist threat.
Second, according to several scenarios of the news portion, it can be
concluded that the higher positive news proportion, the higher probability of terrorist threat will occur.
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Tuesday, 16:00-17:30 - Room 016
Risk Analysis and Management
Stream: Decision Making Modeling and Risk Assessment in the Financial Sector
Invited session
Chair: Shin-Yun Wang
1 - Support Vector Regression for Loss Given Default
Modelling
Xiao Yao, Jonathan Crook, Galina Andreeva
In this paper support vector regression models are applied to predict
loss given default of corporate bonds, where improvements are proposed to increase predictive accuracy by modifying the SVR methods
to account for heterogeneity of bond seniorities. Our paper has the following contributions: At an aggregated level the proposed improved
versions of SVR techniques outperform other methods significantly;
At a segmented level LS-SVR models show significantly better predictive abilities compared with the other statistical models; Standard
transformations of LGD do not improve predictive accuracy.
2 - Modelling Operational Risk Using Skew t-Copulas via
Bayesian Inference and Extreme Value Theory
Betty Johanna Garzon Rozo, Jonathan Crook, Fernando
Moreira
Operational risk losses are heavy tailed and are likely to be asymmetric and extremely dependent among business lines/event types. We
propose a new methodology to assess, in a multivariate way, the asymmetry and extreme dependence between severities, and to calculate the
capital for Operational Risk. This methodology simultaneously uses
extreme value theory and the skew t-copula. The former to model the
loss severities more precisely; the latter to effectively model asymmetry and extreme dependence in high dimensions. The paper analyses
an update data set, SAS Global Operational Risk Data.
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3 - Comparative Analysis of Multinomial and Conditional Logistic Regression Approaches to Credit
Card Holders Behaviour Modelling
Denys Osipenko, Jonathan Crook
Because of variety of the card holders’ behaviour patterns and income
sources each consumer account can move to a number of states. The
estimation of the transition probability between statusesat the account
level helps to avoid the memorylessness of the MDP approach. The key
question is which approach gives more accurate results: multinomial
logistic regression or decision tree with conditional binary logistic regressions. This paper investigates the approaches to credit cards profitability estimation at account level based on multistates conditional
probability.
4 - Executive Compensation and Excessive
Taking: A Quantile Regression Analysis
Shin-Yun Wang
Risk-
We test the relation between firm’s risk and executive compensation.
Differ from previous studies and examine the relation at the tails of the
risk distribution using quantile regression. Traditional analysis of such
relation using OLS method reveals only the conditional means of the
estimates, which cannot answer the question if executive compensation encourages excessive risk-taking. We also partition firm risk into
systematic and idiosyncratic levels as literature suggests that CEO option compensations create incentive to increase systematic risk, but not
necessary idiosyncratic risk.
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Tuesday, 16:00-17:30 - Room 131
Airline Optimization
Stream: Stochastic Modeling and Simulation in Engineering, Management and Science
Invited session
Chair:
Chair:
Chair:
Chair:
Silja Meyer-Nieberg
Erik Kropat
Goran Mihelcic
Alexandre Jacquillat
1 - A Multi-Period Airline Seat Inventory Control Model
Sang Won Kim
Airlines sell similar seats on an air flight at different fares and demand is affected by customer buying behaviors when customers buy
other fare class tickets if the originally requested fare were unavailable
and wait in anticipation of reopening of the same fare class. We consider an extension of the two-fare, two-period seat inventory allocation
model to multi-period, multi-fare airline seat inventory allocation decisions. We develop heuristic models for multi-period, multi-fare airline
seat inventory allocation and an efficient computer algorithm to reduce
computation time.
2 - Measurement of Efficiency Using Data Envelopment
Analysis: An Application in Airline Industry
Burak Keskin, Efehan Ulas, Mert Aktan
The aim of this study is to present an application of Data Envelopment Analysis (DEA) to measure the efficiency of 28 airline companies
which are members of the star alliance organization. The first step is to
quantify the level of efficiency based on the real data which acquired
from the annual reports of airlines and then, the ways to improve the
efficiency of their works are recommended for the inefficient ones.
3 - Toward an Equitable and Collaborative Mechanism
for Schedule Coordination at Congested US Airports
Alexandre Jacquillat, Vikrant Vaze, Amedeo Odoni
Small scheduling changes could achieve large delay reductions at US
airports. But schedule coordination studies do not fully integrate airline scheduling preferences. We solve a tradeoff between reducing
delays and satisfying airline preferences. First, we formulate equity
constraints to fairly balance schedule changes among airlines. Second,
we design a collaborative mechanism between a coordinator and the
airlines based on non-monetary transfers. This combines stochastic
queue dynamics, a Dynamic Programming model of capacity utilization and an Integer Programming model of flight scheduling.
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Tuesday, 16:00-17:30 - Room 132
Agrifood Industry
Stream: OR in Agriculture, Forestry and Fisheries
Invited session
Chair: Concepcion Maroto
Chair: Javier Ribal
1 - The Analytical Hierarchy Process in the Choice of
Cocoa Post-Harvest Technology in Ecuador
Amparo Baviera-Puig, Lenin Vera-Montenegro, José María
Garcia-Alvarez-Coque
We define a cocoa post-harvest technology selection model to assist
small producers in Ecuador by using the Analytical Hierarchy Process
(AHP) to assess the following criteria: quality, processing cost and
technology adoption capability. Although quality is the highest-valued
single criterion, it is not necessarily the decisive factor in the selection of the best technology because the high scores attributed to some
technologies in the other two criteria offset the quality criterion score.
Thus, processing cost and technology adoption are also relevant for
small producers.
2 - Old and new diet Formulation Models in the Swine
Industry
François Dubeau, Jean-Pierre Dussault, Émilie Joannopoulos,
Candido Pomar
We present several new diet formulation models that can be applied
to the swine industry. We explain the classic and multiphase feeding models. We introduce two formulations, called respectively fixed
and free. The free premix model departs from the traditional linear
programming formulation in tackling simultaneously the diet’s premix
contents and the daily proportions, resulting in a bi-linear formulation.
We also present the unfixed energy rate model and show how it is related to the previously presented models. Cost improvements of some
new models are presented.
3 - Selecting a Healthy, Environmentally Friendly and Affordable Diet
Javier Ribal, M. Loreto Fenollosa, Purificación
García-Segovia, Gabriela Clemente, Neus Sanjuan
Due to the high degree of personal choice, food represents a good opportunity for consumers to influence their personal carbon footprint.
However, health, environmental effects and food cost are not always
convergent. This study develops a goal programming model to select
a 30-day sustainable diet choosing out of 256 daily menus considering nutritional, environmental and economic aspects. The results can
make it possible to analyze the trade-offs between these aspects and to
quantify how budget constraints can determine an unhealthy or environmentally unfriendly diet.
4 - New Methodology for Evaluating and Classifying
Suppliers based on an Outranking Approach
Concepcion Maroto, Dennise Alos, Jordi Cuartero, Salvador
Giner, Marina Segura, Baldomero Segura
Establishing the most appropriate relationship with the suppliers is a
main issue for companies. We propose a methodology to evaluate suppliers in order to support these decisions. We define specific criteria
of the products and those related to the suppliers, as well as their indicators. A criticality index and a strategic index of suppliers have been
calculated by using PROMETHEE and AHP. These indices have been
implemented in an agrifood company to classify their suppliers according to the most interesting relationship (partners, long term contracts,
market policies or elimination).
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Tuesday, 16:00-17:30 - Room 017
Indoor Localization
Stream: Multiobjective Optimization
Invited session
Chair: Marta Pascoal
Chair: José Santos
IFORS 2014 - Barcelona
1 - Multilateration for Indoor Localization
Ana Rita Pereira, José Augusto Ferreira, José Santos, Manuel
António Vicente
Multilateration is a usual technique to localize a mobile device in an
indoor environment. In this talk we describe different strategies to deal
with multilateration. The use of previous positions of the mobile device to increase the accuracy of this procedure will be also considered.
Numerical studies will be presented that lead to a ranking of the different approaches.
2 - Indoor Localization with Multi-Criteria Optimization
José Santos, Pedro Jorge
This communication approaches the problem of locating a mobile device in an indoor environment using the wireless network at disposal,
where the most common locating services such as GPS are not available. Several strategies are shown based on a multi-criteria approach,
each one aims to solve the problem efficiently. Afterwards, they are
compared with a usual localization strategy (the k nearest neighbours
algorithm), by presenting some computational results.
3 - Shortest Paths on Indoor Localization
Cátia Santos, Marta Pascoal
Indoor positioning systems are often affected by inaccuracy due to various reasons, like changes in the environment or noise resulting from
signal propagation errors. In this talk we address the problem of calculating distance lower bounds between two sites in a building, in order
to validate (or discard) consecutive locations of a mobile device identified by localization algorithms. Methods for solving this problem in
real time will be discussed and comparative computational results will
be reported.
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Tuesday, 16:00-17:30 - Room 214
Regularization Methods
Stream: Convex Optimization Methods and Applications
Invited session
Chair: Yaxiang Yuan
Chair: Xin Liu
1 - A Gauss-Newton Method for Low-Rank Matrix Approximation
Yin Zhang
Data dimensionality reduction problems typically rely on eigenvalue
calculations. For large-scale data, classic eigenvalue algorithms, although well-developed, can become unnecessarily costly. In this work,
we propose and analyze a Gauss-Newton method for computing lowdimensional principal subspaces. The algorithm is simple, low-cost
and parameter-free. We present theoretical convergence and numerical
results showing that the proposed algorithm can be up to several time
faster than SVD-based algorithms.
2 - Regularization Methods for Retrieval of Magnetic Parameters with Full Tensor Gradient Data
Yanfei Wang
Retrieval of magnetization parameters using magnetic tensor gradient
measurements received attention in recent years. Determination of
subsurface properties from the observed potential field measurements
is referred to as inversion. Little regularizing inversion results using
gradient tensor modeling so far has been reported in the literature. In
this paper, we solve the inverse problem of identifying the magnetic parameters with the magnetic gradient tensor data using optimization and
regularization theory of ill-posed problems. Numerical experiments
are performed.
3 - Acquire More for Less: Applications of Compressive
Sensing on Seismic Data Acquisition
Chengbo Li, Charles Mosher, Joel Brewer
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Compressive sensing (CS) is a novel sampling methodology representing a paradigm shift from conventional schemes. Conoco Phillips has
successively applied CS to seismic data acquisition. The field trial
shows significant improvement of the data resolution compared to conventional survey. Simultaneous sources provide us with another novel
scheme for acquiring better seismic data more quickly at lower total
cost. We rely on inversion procedure to deblend and regularize data.
The inversion method we developed is based on the nonmonotone alternating direction method.
TE-39
Tuesday, 16:00-17:30 - Room 018
Fuzzy Optimization in Supply Chain
Management
Stream: Discrete and Global Optimization
Invited session
Chair: Turan Paksoy
Chair: Nimet Yapıcı Pehlivan
1 - Multi-Criteria Decision Making for Recycling Planning in the Automotive Industry
Abdullah Yıldızbaşı, Turan Paksoy, Hadi Gökçen, Nihat
Yüzügüllü
This paper proposes a recycling planning model for automotive shredders to make short-term tactical decisions regarding to what extent
to process and to reprocess materials through multiple passes. The
mixed-integer programming model determines whether to combine
materials for shipment. In addition, the AHP method is used for obtaining the weights of some constraints. The model involves shreddering facilities, sorting, transportation, and disposal centers. Finally,
accuracy and applicability of the model is illustrated via a hypothetical
example.
2 - A Novel Interactive Fuzzy Programming Approach
based on MultiMOORA Method for Closed Loop Supply Chain Network Optimization under Fuzzy Environment
Nimet Yapıcı Pehlivan, Ahmet Çalık, Turan Paksoy
This paper presents a novel interactive fuzzy programming approach
based on a MultiMOORA method which is a multi-criteria decision
making method for closed loop supply chain (CLSC) network optimization under fuzzy environment. The general CLSC network members can be classified into two groups (Zhu et al.2008): (i) forward
logistics chain members, including raw material suppliers, manufacturers, retailers, and consumers; (ii) reverse logistics chain members,
including consumers, collection centers, recycling centers, and manufacturers or suppliers.
3 - A Closed-Loop Supply Chain Network Design: A New
TOPSIS Based Interactive Fuzzy Programming Approach
Ahmet Çalık, Turan Paksoy, Nimet Yapıcı Pehlivan
This paper presents a novel interactive fuzzy programming approach
based on crisp and fuzzy TOPSIS (Technique for Order Performance
by Similarity to Ideal Solution) for closed-loop supply chain (CLSC)
network design problem including manufacturers, suppliers and collection centers. The aim of the proposed problem is the integration of
TOPSIS and fuzzy TOPSIS methods into the development stage for
usage of Interactive Fuzzy Programming approach. A numerical example is applied and tested for the proposed model
4 - Testing for Non-linear Relationship in Structural
Equation Modeling
Ilkay Altindag, Aşır Genç
Structural equation modeling (SEM) is a multivariate statistical
method, with the integration of factor analysis and multi-regression
analysis. Recently, it is recognized that nonlinear relations among the
variables are important in establishing more meaningful and correct
models for some complex situations. In this study, we indicate a nonlinear structural equation model which can accommodate covariates in
the measurement equation, and nonlinear terms of covariates and exogenous latent variables in the structural equation.
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Tuesday, 16:00-17:30 - Room 019
Innovations in Meta-Analytics II
Stream: Meta-Analytics: A Marriage of Metaheuristics
and Analytics
Invited session
Chair: Jin-Kao Hao
1 - A Tabu Search Algorithm for Cohesive Clustering
Problems
Buyang Cao, Fred Glover
A Tabu Search algorithm for a new problem class called cohesive clustering which arises in a variety of business applications is presented.
The class introduces an objective function to produce clusters as pure
as possible, to maximize the similarity of elements in each given cluster. Our algorithm generates clusters of a specified number or can
determine this number adaptively — which can be useful for unsupervised data mining. Tabu Search intensification and diversification
strategies produce enhanced outcomes and we show the effectiveness
of the algorithm by computational experiment.
2 - Distance-Guided Local Search
Daniel Porumbel, Jin-Kao Hao
In Local Search (LS), the concept of distance between solutions has
been generally used less often than in other areas (e.g, multimodal
evolutionary algorithms, crowding or niching). We present DistanceGuided Local Search (DSLS): a platform of using distances on top
of a given LS, so as to avoid unique local optima and global looping
(looping among a few distinct local optima). DG-LS has been already
implemented on the max-clique problem (vector space) and tests are
under considerations for graph coloring (partition space) and an arcrouting formulation (permutation space).
3 - MO-Mine_Clust: A Generic Platform for MultiObjective Clustering
Clarisse Dhaenens, Laetitia Jourdan, Benjamin Fisset
Clustering is a very popular data mining, which is by nature a multiobjective. Therefore, it seems interesting to provide a generic platform that is able to deal with different combinations of measures and
propose several multi-objective algorithms. Such a generic platform
could offer the opportunity to compare several of them. The objectives
of the platform are: - Propose to use several mono and multi-objective
models for clustering, - Execute several multi-objective metaheuristic
schemes, - Compare statistically results obtained.
4 - Tabu Search with Global Exploration for Machine Reassignment Problem
Michel Vasquez, Saïd Hanafi, Koji Nonobe, Mutsunori
Yagiura, Hideki Hashimoto
We propose a tabu search with global exploration for solving the machine reassignment problem (ROADEF challenge 2012). The exploration uses shift and swap moves and the reverse elimination method,
proposed by F. Glover, manages the tabu list to avoid the trap of local
optimality. Evaluating the neighborhood of the current solution is cpu
time expensive regarding the fact that only one move will be choose at
the end. To compute quickly the "best" matching, we use an improved
version of the path growing algorithm for weighted matching in graph
proposed by Drake and Hougardy.
1 - Operations Research for Health Care: Simulating
Blood Inventory Management
Alex Grasas
Banc de Sang i Teixits (BST) aims to ensure the supply and proper use
of blood and tissues in Catalunya. BST manages blood inventory for
all hospitals in Catalunya considering that blood has a maximum shelf
life (MSL) of 42 days; that is, blood can only be transfused within 42
days after donation. Recent studies have shown, however, that blood
in its last week may lose some properties causing rejection problems
among patients. In order to improve health care quality, we simulate
the blood inventory system at BST to study the impact of reducing the
MSL to 35 days.
2 - Algorithm for Bicriteria Scheduling in Parallel Machines with Eligibility
Manuel Mateo, Jacques Teghem, Jordi Camps
The scheduling of parallel machines with eligibility is a very common
problem. A set of n jobs has to be scheduled on m parallel machines
distributed among p levels. The previous and the following operations
also introduce release and delivery times. Particularly, we study the
case of p=3. Any machine has the same processing time for a job. We
consider two objectives: minimize the makespan and a penalty function if the jobs are not assigned to top machines. The problem is solved
considering different kinds of exploration. To check their performance,
a computational experience is conducted.
3 - Solving Non-Smooth Flow-Shop Problems with
Failure-Risk Penalties Using a Biased Randomized
Local Search
Albert Ferrer, Daniel Guimarans, Helena Ramalhinho
Lourenco, Angel A. Juan
We present a variant of the flow-shop problem with a non-smooth objective function that takes into account maintenance and operations
costs. We propose a randomized Iterated Local Search algorithm that
employs non-uniform probability distributions. A biased random behavior is considered in the NEH heuristic to generated initial solutions.
The algorithm generates a large number of alternative good solutions
without a complex configuration. This characteristic is particular useful in presence of non-smoothness or non-convexity functions.
4 - SimILS: Solving Stochastic Combinatorial Optimization Problems by Combining Iterated Local Search
with Simulation
Helena Ramalhinho Lourenco, Angel A. Juan, Alex Grasas
The combination of Simulation with Optimization can be a powerful
tool to solve complex decision real problems. One important research
area is the combination of Simulation with Heuristics and Metaheuristics, SimHeuristics. In this talk we will describe a special case of the
SimHeuristics, the combination of Simulation with the Metaheuristisc
known as Iterated Local Search. We will describe the scheme to combine Simulation and ILS and the potential application to Stochastic
Combinatorial Optimization Problems.
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Tuesday, 16:00-17:30 - Room 215
TE-41
Tuesday, 16:00-17:30 - Room 216
Simulation-Optimization in Logistics &
Production
Stream: Simulation-Optimization in Logistics & Production
Invited session
Chair: Albert Ferrer
Chair: Angel A. Juan
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Applications in Decision Making &
Decision Analysis
Stream: Decision Support Systems
Invited session
Chair: Fatima Dargam
Chair: Shaofeng Liu
1 - A Decision Support System for Estimating the Scale
of Using Renewable Sources of Energy and Storing
Electricity in a Regional Electrical Grid
Alexander Belenky
IFORS 2014 - Barcelona
A game-theoretic approach to making decisions on the scale of using
renewable sources of energy and storing electricity in a regional electrical grid under both the existing and expected prices for electricity from
all the sources of the electric power in the gird is proposed. Solving a
game with a finite (more than three) number of players on polyhedra
of connected player strategies underlies the decision making process,
and the use of proposed verifiable sufficient conditions of equilibria
in this game reduces finding the equilibria to solving three auxiliary
linear programming problems.
2 - A DSS for Resolving Evaluation of Criteria by Interactive Flexible Elicitation on Supplier Selection Problems
Adiel Teixeira de Almeida, Jonatas Almeida, Adiel
Almeida-Filho, Ana Paula Costa
The paper presents a DSS for elicitation of weights of multicriteria
additive models. This is one of the most relevant issues in additive
models. The tradeoff elicitation procedure is considered to have the
strongest theoretical foundation, although experimental studies have
found inconsistencies when applying that procedure. The DSS uses the
concept of flexible elicitation so as to overcome some concerns about
the tradeoff elicitation procedure. The use of the DSS is illustrated by
the application on two different supplier selection problems.
3 - Learning Non-Monotonic Preferences, a New Algorithm
Mohammad Ghaderi, Francisco Ruiz, Nuria Agell
Capturing preferential system of the Decision Maker (DM), given a
ranking of alternatives, is a challenging research question in preference disaggregation field. UTA methods are well-known in the literature, addressing this question by a linear programming model. In most
of the UTA-based methods, a monotonic value function has been applied, which limits the applicability of the method. Non-monotonic
UTA-based methodologies, on the other hand, are computationally intensive. In this paper we introduce a faster and simpler model, capable
of learning additive non-monotonic utility functions.
4 - Support decision in soccer football
Silvely Néia, Vilma Tachibana, Pedro Castro
The soccer has experienced increased competition among clubs. The
sport has become a business and the use of techniques of management
is essential for survival of these companies, so globalized . This work
uses the variables involving football through statistical techniques, envolving multivariate analysis tools with its techniques of cluster and
principal components, and space and descriptive statistics. It is possible to obtain results and numbers that can qualify and quantify the
performance of the players individually and collectively, qualify and
quantify their performances.
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2 - Understanding Different Online Gamer Retention Behaviours: A Data Mining Approach
Xin Fu, Yutong Shi, Shun Cai, Di Xu
This work proposes an innovative player segmentation model based on
their in-game behaviour data, for the first time, to support player retention analysis. In this manner, the retention behaviour patterns of each
player segment would be modelled and analysed respectively. In particular, a new similarity metric (which is driven by player’s "stickiness"
to the game) and an improved fuzzy K-means clustering algorithm is
developed herein to cluster players. The applicability and utility of this
work are illustrated by means of experiments that are conducted on a
realistic MMORPG dataset.
3 - A Business Intelligence Framework Using Web and
Time Series Data Mining for Agriculture-based Markets
Hector Flores, Rene Villalobos
The ability to correctly foresee future events based on historic information is key for any analytical setting. Traditional time series forecasting
methods are based on stationary and ergodic assumptions that are often
not adept to handle complex market information not adhering to these
assumptions. In this study, we aim to develop a framework that incorporates web and time series data mining techniques to identify changing trends and patterns in agriculture-based markets. This framework
enhances farmers’ decision-making by improving their strategic and
tactical planning capabilities.
4 - Truthful Auction Mechanisms for Value-Maximizing
Bidders
Salman Fadaei, Martin Bichler
We discuss auction design for bidders which maximize valuations
rather than quasi-linear utility functions. We will refer to such bidders as value-maximizing bidders or short value bidders. Examples
are markets for TV ads sold by a TV station, where bidders are media
agencies who are given a budget by clients describing their value for
different allocations. The budgets are considered as sunk cost and they
are devoted to a particular campaign or package of slots. The bidder’s
goal is to win the highest valued package. The environment is different
from mechanism design without money.
TE-44
Tuesday, 16:00-17:30 - Room 218
Multiobjective Linear Programming
Stream: Multiobjective Linear, Integer, and Combinatorial Optimisation
Invited session
Chair: Matthias Ehrgott
TE-43
Tuesday, 16:00-17:30 - Room 217
Data Mining, Economic Models and
Games
Stream: Computational Statistics
Invited session
Chair: Pakize Taylan
Chair: Martin Bichler
1 - Ordered Weighted Average Combinatorial Optimization: Formulations and their Properties
Miguel Angel Pozo, Elena Fernandez, Justo Puerto
In this paper, Ordered Weighted Average optimization problems are
studied from a modeling point of view. Alternative integer programming formulations for such problems are presented and their respective
domains studied and compared. In addition, their associated polyhedra
are studied and some families of facets and new families of valid inequalities presented. The proposed formulations are particularized for
two well-known combinatorial optimization problems, namely, shortest path and minimum cost perfect matching, and the results of computational experiments are presented and analyzed.
1 - The Application of Data Mining Technique to Bookstore Customer Relation Management
Hong Tau Lee, Sheu-Hua Chen
2 - Primal and Dual Methods for Linear Optimization
over the Nondominated Set of a Multi-objective Linear Programme
Zhengliang Liu, Matthias Ehrgott
This research applies data mining technique on the transaction data of
book chain-store to figure out the consumers’ favorites of the relationship between the categories of books they bought. Different favorite
relationships were found in different type of book stores which locates
in different districts. Specific promotion activities were provided based
on the patterns found. The results show that there have significant advantages of profit, advertisement expense, and consumer’s response
rate.
This article presents two new algorithms for the maximization of a linear function over the nondominated set of a multiobjective linear optimization problem. A primal method is developed based on a revised
version of Benson’s outer approximation algorithm in objective space.
A dual method derived from the dual variant of the outer approximation algorithm is proposed. We compare the two new algorithms with
several algorithms from the literature on a set of randomly generated
instances.
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IFORS 2014 - Barcelona
3 - Multiobjective Column Generation Using Revised
Normal Boundary Intersection: An Application to Radiotherapy Treatment Planning Optimization
Kuan-Min Lin, Matthias Ehrgott, Andrea Raith
We propose a column generation (CG) approach to solve multiobjective linear programs. The method implements CG within the revised
normal boundary intersection (RNBI) framework to compute a representative set of nondominated points. The CG process adds non-basic
variables to the restricted master problem, which move a current objective point towards nondominance. A reference subsimplex optimization method is used to eliminate reference points that lead to infeasibility. Numerical tests on a radiotherapy treatment problem demonstrate
the uniformity of the points generated by the CG RNBI method.
4 - Data Envelopment Analysis Without Linear Programming
Matthias Ehrgott, Maryam Hasannasab, Andrea Raith
Data Envelopment Analysis for the efficiency assessment of decision
making units (DMUs) traditional requires the solution of one linear
programme per DMU. In this paper we investigate data envelopment
analysis from a multi-objective optimisation point of view and show
that, by applying primal and dual outcome space algorithms for multiobjective linear programming, data envelopment analysis can be performed without solving any linear programmes. We demonstrate the
advantage of this technique for practice on a number of DEA instances.
TE-45
Tuesday, 16:00-17:30 - Room 219
Analysis of Customer-Based Data
Stream: Business Analytics Optimization and Big Data
Invited session
Chair: Nuria Agell
1 - Making Sense of Online Customer Reviews
Alexandra Medina-Borja
Published tourist destination data for the Caribbean Islands and online
reviews left by visitors were used to extract customer’s online opinions. We used sentiment analysis and semantic orientation to extract
the data, and on fuzzy logic to quantify the results into representative
metrics of service quality. Triangular fuzzy numbers were used to represent the linguistic scale behind customer online comments that reflect
their evaluation of the service. We then use Data Envelopment Analysis (DEA) to quantify the performance of comparable service units.
2 - Group Consensus Mining based on Extended Tournament Matrices
Li-Ching Ma
Group consensus mining is to find out a maximum consensus sequence
which is the longest ranking lists of items that the majority agrees with
and the minority disagrees with. This study tries to develop a novel
approach for group consensus mining problems. First, each decision
maker’s preferences are transformed into an extended tournament matrix. A rank tracking algorithm is then developed to obtain a maximal
consensus sequence. Compared to previous methods, the proposed approach can efficiently discover maximum consensus sequence without
generating and filtering lots of candidates.
3 - Exploring the Role of Consensus Measures in Decision Science: An Experience Towards Summarizing
Users’ Opinions
Nuria Agell, Soumya Banerjee, Monica Casabayó
Internet has changed consumers’ decision-making process in several
ways. Consumers have the possibility to search for more and better
information about products and services. Moreover, consumers are
likely to influence other peers; even they do not know them. The aim
of this paper is to build a new mining approach which is able to filter
customer’s feed-back automatically using text summarization. We define a new model, based on two consensus criteria. On the one hand
a consensus based on a proximity measure, and on the other hand a
consensus based on consumers preferences.
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4 - 1 Million Regressions in 30 Seconds: An Airbnb
Case Study of Distributed Big Data Mining
Lukasz Dziurzynski
The purpose of this talk is to discuss scalable statistical techniques
through case studies of analytics projects at Airbnb. You will learn
how to overcome analytical challenges at scale–TB-sized datasets–via
concrete examples. We built a daily process that uses browsing activity to predict how likely each user-session is to contact or book. We
used collaborative filtering to improve our search-to-book rate. We
enhanced our price-suggestions, in particular for the upcoming World
Cup in Brazil. This talk will show how Airbnb integrated Mahout,
Hive, R, and Python to solve these problems.
IFORS 2014 - Barcelona
HA-03
Thursday, 8:30-10:00
HA-02
HA-01
Thursday, 8:30-10:00 - Room 118
Time-dependent Vehicle Routing and
Scheduling
Scheduling and Rescheduling Railways
under a Dynamic Environment
Stream: Vehicle Routing
Invited session
Stream: Railway and Metro Transportation
Invited session
Chair: Luis Cadarso
1 - The Influence of Dwell Times on Rail Service Planning
Antonio Placido, Luca D’Acierno, Marilisa Botte, Simone
Campora, Bruno Montella
Due to the constant increase in travel demand, rail systems are more
and more dense and service providers have the difficult task of planning a timetable which has to be robust and stable. Moreover, in order
to increase customers’ satisfaction, it is necessary to provide sufficient
transport capacity avoiding train and platform congestion and guaranteeing a good level of service quality. To reach this target, in this
framework we provide an appropriate timetable evaluation which considers the dynamic effect of dwell time at station on the service in the
case of metro networks.
2 - A Fast and Effcient Adaptive Large Neighborhood
Search Heuristic for the Passenger Train Timetabling
Problem with Dynamic Demand
Eva Barrena, David Canca, Leandro Coelho, Gilbert Laporte
We study the design and optimization of train timetables adapted to a
dynamic demand environment. The objective is to minimize the average passenger waiting time at the stations, thus focusing on passenger
welfare. We first propose two mathematical programming formulations. We then analyze the properties of the problem before introducing a fast adaptive large neighborhood search metaheuristic in order to
solve large instances of the problem within short computation times.
The algorithm yields timetables that may not be regular or periodic,
but are adjusted to a dynamic demand behavior.
3 - A Macroscopic Railway Timetable Rescheduling Approach for Handling Large Scale Disruptions
Lucas Veelenturf, Martin Kidd, Valentina Cacchiani, Leo
Kroon, Paolo Toth
Relatively large daily disruptions require infrastructure managers and
railway operators to reschedule their timetables and rolling stock and
crew schedules. This research focuses on timetable rescheduling at a
macroscopic level. An integer programming model is formulated for
solving the timetable rescheduling problem, minimizing the number
of cancelled and delayed trains while adhering to infrastructure and
rolling stock capacity constraints. The results of the computational
tests of the model on the Dutch railway network are promising.
4 - A Model for Readjusting Public Transport Services
on Short Time Periods
Esteve Codina, Lídia Montero, Ángel Marín
A mathematical programming model described to assist with the
rescheduling of services for a set of auxiliary bus lines (a bus-bridging
system) during disruptions of metro and rapid transit lines during a
short time period is presented. The model is formulated as a classical
event scheduling problem combined with flow balance constraints in
order to take into account time-dependent information regarding trip
demands between the stations of the auxiliary bus system. Both, the
complete version of the model and a conveniently simplified formulation are presented.
Thursday, 8:30-10:00 - Room 111
Chair: Christian Bierwirth
1 - Synchronization in Vehicle Routing Problems — An
Overview
Dorota Slawa Mankowska, Christian Bierwirth, Frank Meisel
One of the currently established extensions of the VRP is synchronization of vehicles, which is required if, e.g., two vehicles must visit
the same location. In this talk, we present VRPs with synchronization
where vehicles can visit a transferring point to exchange cargo without
having to go back to the depot for replenishment. Also the temporal
aspect is considered, i.e., vehicles that provide cargo must visit a transferring point earlier than receiving vehicles. We present mathematical
formulations for different types of synchronization requirements and
heuristic solution approaches.
2 - Time Inconsistency of Heuristics in Multi-Period VRP
Alexander Shchegryaev, Victor Zakharov
In our talk we discuss and demonstrate the effect of time inconsistency
of vehicle routing plans constructed by some heuristic algorithms in
multi-period VRP. Results of evaluating level of the heuristics time inconsistency are presented. An approach and methods to decrease level
of heuristics time inconsistency are proposed. To increase level of time
consistency of optimal routing plan of grand coalition in multi-period
cooperative vehicle routing game and improve values of characteristic function we propose to apply iterative coalition induction algorithm
(ICIA).
3 - The Multi-period Collection Scheduling Problem with
Balancing Constraints
Cristina Nuñez, Elena Fernandez, Jörg Kalcsics, Stefan
Nickel
This periodic collection problem determines the joint visiting calendar of a set of companies to a set of customers minimizing the total
number of vehicles. There are storage limitations at the customers and
balancing constraints on the total amount collected by the companies.
Two alternative collection policies are studied. Linear integer formulations are presented. Numerical experiments show the reduction in
number of vehicles when the second collection policy is considered.
The difficulty of the problem when balancing constraints are imposed
is evidenced. A solution algorithm is proposed.
4 - Column Generation for a Class of Bi-Objective Vehicle Routing Problems
Christian Artigues, Nicolas Jozefowiez, Boadu Mensah
Sarpong
We present a generalized column generation scheme to compute bound
sets for bi-objective integer linear programs. We also present different
strategies for implementing the generalized algorithm and refinements
for the case where one of the objectives is a min-max objective. We
apply the proposed method to extended formulations for bi-objective
vehicle routing problems, such as the bi-objective multi-vehicle covering tour problem. The results show that good lower and upper bounds
are obtained in reasonable times if columns are efficiently managed.
HA-03
Thursday, 8:30-10:00 - Room 001
Discrete Location and Routing
Stream: Location
Invited session
Chair: Alfredo Marín
Chair: Justo Puerto
151
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IFORS 2014 - Barcelona
1 - Analysis of the Solution Permutations for the Asymmetric Traveling Salesman Problem
Mercedes Landete, Justo Puerto, Javier Alcaraz, Juan
Francisco Monge, Eva M. García-Nové
In this work we consider the situation in which the optimal route, the
solution of the Asymmetric Traveling Salesman Problem, needs to be
modified because of unexpected events. All the nodes require service
but some of them modify their position on the route. Instead of probabilities of failing, each permutation has a penalty and the goal is to
minimize the weighted addition of the cost of the permutations of the
solution we choose. We present several formulations for the problem
and we compare them. Computational experiments illustrate the performance of each formulation.
2 - A Further Study of Location Facilities with Failure
Foresight
Inmaculada Espejo, Alfredo Marín, Antonio Manuel
Rodriguez-Chia
This work introduces a variation of the classic capacitated p-center
problem which takes into consideration the possibility of facility failures due to external disruptions. If the closest center to a given demand point fails, the point must be reallocated to its second closest
center. The aim is to minimize the maximum distance between a demand point and its second closest center. Moreover, the capacity of
each center must suffice to serve the demand of its closest customers
and the demand of the customers that would be assigned to it in case
of failure of their first closest center.
3 - A Parallel Implementation of the Volume Algorithm to
Solve the p-Median Problem
Mourad Baiou, Francisco Barahona, Jean-Christophe Gay
It is known that solvers like Cplex cannot solve huge instances of the
p-median linear relaxation and that it is much appropriate to solve it
by method based on Lagrangian relaxation as the volume algorithm.
Even if we can solve huge instances with a sequential implementation
it remains time consuming, so this is why parallel implementation is
evoked. We use a trick in the implementation of the greedy heuristic
to provide an upper bound. The trick is to reduce the greedy algorithm
to a local search algorithm where a powerful implementation is known
and due to Resende and Werneck (AOR, 2007).
4 - The Discrete Ordered Median Problem: A Tour of Perspective
Justo Puerto
This talk presents old and new formulations for the ordered median
problem comparing the rationale behind them. In addition, we revisit
the application of this type of objective function to different combinatorial objects identifying common properties that help in solving the
problems. Preliminary computational results show the powerfulness
of this approach to model and solve complex combinatorial problems
as ordered median hub-location problems, capacitated ordered median
location problems or multiobjective ordered weighted average shortest
path problems, among others.
HA-04
Thursday, 8:30-10:00 - Room 119
Network Traffic Modelling I
Stream: Traffic Flow Theory and Traffic Control
Invited session
Chair: Nikolas Geroliminis
Chair: Ludovic Leclercq
1 - A Network Model for Capped Distance-Based Tolls
Michael Florian
Toll road operators require analysis tools to estimate the ridership and
projected income for an increasing variety of tolling schemes. Some
tolling schemes commonly considered include distance-based tolls as
well as charging a maximum toll (or cap) for the use of the facility
or minimum toll. In order to meet these requirements a new model
formulation and algorithm for distance-based toll modelling is developed. This new method is illustrated with a small example and a case
of capped distance-based toll modelling on a network originating from
practice.
152
2 - Extensions of the Macroscopic Fundamental Diagram to Multimodal Traffic
Nicolas Chiabaut
This paper aims to extend the concept of Macroscopic Fundamental
Diagram (MFD) to combine different transportation modes. Especially, we propose a unified relationship that account for cars and buses
because the classical MFD is not sufficient to capture traffic flow dynamic of a multimodal traffic. The concept of passenger fundamental diagram is introduced. With this new relationship, efficiency of
the global transport system, i.e. behaviors of cars and buses, can be
assessed. Then, this relationship can be used to identify the optimal
domains of applications for different transit strategies.
3 - A Mathematical Proof for the Optimal Perimeter Control Policy at an Urban Region
Jack Haddad, Ilya Ioslovich
Recent works show that a perimeter controller can manipulate transfer
flows across a region border to maximize the total exit flow of the urban region. The macroscopic fundamental diagram (MFD) is utilized
to model the traffic flow dynamics in the homogenous region. In this
paper, we provide the explicit formulation of the optimal feedback control policy and a mathematical proof of optimality. The proof is based
on the modified Krotov-Bellman sufficient conditions of optimality,
where the upper and lower bounds of state variables are calculated.
4 - Modeling and Control of Large Scale Multimodal Urban Networks
Nikolas Geroliminis, Konstantinos Ampountolas, Nan Zheng
Recent research has studied the properties of a macroscopic fundamental diagram (MFD) for urban areas. The MFD should not be universally
expected as high scatter or hysteresis might appear for some type of
networks. We investigate if aggregated relationships can describe the
performance of urban bi-modal networks with buses and cars sharing
the same infrastructure and identify how this performance is influenced
by the interactions between modes and the effect of bus stops. We also
introduce simple perimeter control strategies to maximize passenger
flows.
HA-05
Thursday, 8:30-10:00 - Room 002
Maritime Routing and Scheduling 2
Stream: Maritime Transportation
Invited session
Chair: Henrik Andersson
1 - A General Short Sea Inventory-Routing Problem
Ahmad Hemmati, Lars Magnus Hvattum, Marielle
Christiansen, Gilbert Laporte
In this work a general short sea inventory routing problem is considered. To solve the problem an iterative metaheuristic is proposed based
on the idea of converting the inventory-routing problem to a ship routing and scheduling problem. Using inventory limits and production
and consumption rates, we generate a set of cargoes with time windows which are be updated based on the information gained during the
interaction with an adaptive large neighborhood search which solves
the ship routing problem. Computational results will be presented, discussed and compared with exact solutions.
2 - A Branch-and-Cut Method for the Routing and
Scheduling of Vessels in a Brazilian Oil Industry
Maria Gabriela Furtado, Pedro Munari, Reinaldo Morabito
We address a pickup and delivery problem faced by a Brazilian industry involving vessels that transport oil from offshore platforms to the
terminals. In addition to the standard features of vehicle routing problems we incorporate additional constraints that take into account the
requirements of the company. As the resulting mathematical formulation become intractable to be solved by optimization softwares, we
propose a mathematical formulation and a branch-and-cut method that
exploit special characteristics of the problem. This enables us to solve
practical instances in reasonable time.
IFORS 2014 - Barcelona
3 - Exact and Heuristic Methods for Creating Annual Delivery Program for LNG Producer
Mohamed Kais Msakni, Fatih Mutlu
The producer of liquefied natural gas (LNG) has to fulfill the demand of its customers all around the world. This demand is specified in a long-term contract between the producer and the client that
has been negotiated in advance and containing windows deliveries and,
early/late and over/under delivery fees. The LNG is transported to customer with heterogeneous fleet of vessels that may differ in capacity,
speed and operations cost. The goal is to establish an annual delivery program (ADP) for the producer that specifies deliveries for the
customers at minimum costs while maximizing revenue.
4 - Order Management in the Brazilian Oil Industry
Henrik Andersson, Martine Hagen, Eirik Fernández Cuesta,
Kjetil Fagerholt
The transportation of material, tools and waste to and from platforms
is a challenging problem within logistics. In this presentation we look
at a problem arising at the platforms in the Campos Basin, outside the
coast of Brazil. Today, the system is operated using a set of fixed routes
repeated on a weekly schedule. Of special concern is the problem of
deciding which orders to load on board the platform supply vessels
each departure. We discuss the pros and cons of fixed routes and analyze different ways to make them more flexible.
HA-06
Thursday, 8:30-10:00 - Room 211
Network Economics
Stream: Social and Economic Networks
Invited session
Chair: Azarakhsh Malekian
1 - The Spread of Epidemics on Random Graphs: A
Modified Bass Model for Product Growth in Networks
Vahideh Manshadi, Ramesh Johari, Sidhant Misra
We study the diffusion of innovation and the product adoption process
in networks with limited interactions. We model the adoption process
by a simple epidemic model, and study the evolution of the epidemic
on random k-regular graphs. First, we show that for complete graphs,
our model is equivalent to the well-known Bass model. Then we analyze the adoption timing for k-regular random graphs and present the
limit results for the time it takes for a fraction of the population to
adopt. Further, we provide the timing of early adoptions at finer scales,
e.g., logarithmic in the population size.
2 - The Spread of Epidemics on Random Networks: The
Effect of Quarantine and Isolation
Azarakhsh Malekian
We introduce a theoretical model of the security investments and network formation and characterize the impact of quarantine and isolation
on the spread of infection in the equilibrium.
3 - Trading Networks with Bilateral Contracts
Alex Teytelboym
We consider general networks of bilateral contracts that include supply
chains. We show that there exists a stable contract allocations whenever agents’ preferences satisfy full substitutability. These stable contract allocations may not be immune to group deviations, efficient, or
in the core. We also show that competitive equilibrium exists in these
networked markets even in the absence of transferrable utility. The
competitive equilibrium contract allocation is also stable.
4 - Mechanism and Network Design with Loss-Exposed
Agents
Sasa Pekec, Alexandre Belloni, Changrong Deng
A revenue-maximizing monopolist is selling a good to buyers who face
a loss if a rival obtains it. The rivalry is modeled through a network
(edge between two buyers who are rivals). We characterize optimal
solutions to this joint network optimization & mechanism design problem. The revenue-maximizing rivalry networks are independent of distributional assumptions on buyers’ private loss values (with virtuals
HA-07
bounded from zero). The structure of optimal networks depends on
whether rivalry is (a)symmetric: optimal undirected networks are rare,
yet none are among many optimal directed networks.
HA-07
Thursday, 8:30-10:00 - Room 003
Dynamical Models in Sustainable
Development II
Stream: Dynamical Models in Sustainable Development
Invited session
Chair: Jean-Sébastien Tancrez
1 - Development of a Preliminary Model for the Kinetic
Behavior of Main Pollulants in the City of Puebla
Maria Osorio
An analysis of the corresponding behavior of the concentrations of carbon monoxide, sulfur dioxide, nitrogen dioxide and ozone recorded in
the database of REMA in Puebla city is described. The correlations between these pollutants are established, and a preliminary kinetic model
which represents the evolution of pollutants in a characteristic "average day" is generated. The model consists of three ordinary differential
equations which solution is obtained with the Runge-Kutta-Fehlberg
procedure in combination with the least-squares values for the kinetic
parameters.
2 - Modeling Network Supply and Distribution of Perishable Products using Systems Dynamics
Oscar Mayorga Torres
The following research presents the modeling of the supply network
and distribution of perishable products using system dynamics, which
took place at Bogota (Colombia), the whip effect for information and
product was analyzed along the structural links of the chain: producers, transporters, wholesalers and retailers. The research components
conceived reverse logistics and inventory management, incorporated
in the analysis of the costs and time delays of the network elements.
Finally, formulated policies improvement focused on retailer seeking
to minimize the negative impact of time delays.
3 - Improving Pest Control Strategies for Eldana Saccharina Walker
Linke Potgieter, Jan van Vuuren, Desmond Conlong
There has been a global shift towards improving the efficiency of
pest control programs such that they are long-term, environmentally
friendly and cost-effective. A reaction-diffusion model of Saccharina,
an insect indigenous to Africa feeding on sugar crop, population dynamics in a temporally variable and spatially heterogeneous environment has been formulated and utilised to identify cost-efficient control
strategies for the insect, which includes the sterile insect technique and
harvesting. The model and its use in decision making, as well as numerical results obtained will be presented.
4 - Designing the Supply Chain Network to Reduce Carbon Emissions
Jean-Sébastien Tancrez, Joana M. Comas Marti, Ralf W.
Seifert
In this work, our goal is to investigate how companies should modify
their supply chain network to cost-effectively reduce their carbon emissions. For this, we propose a supply chain network design model that
simultaneously considers the emissions and costs related to both facility location and transport mode decisions, while taking into account
the product characteristics (e.g., innovative or functional) through the
explicit consideration of demand uncertainty and inventory costs. The
model is illustrated using numerical experiments and managerial insights are derived.
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IFORS 2014 - Barcelona
HA-08
Thursday, 8:30-10:00 - Room 120
Carbon Emissions and Remanufacturing
Problems
Stream: Energy Economics, Environmental Management and Multicriteria Decision Making
Contributed session
Chair: Matthias Garbs
1 - The State of Scope 3 Carbon Emissions Reporting in
Supply Chains
Charles Corbett, Christian Blanco, Felipe Caro
For most firms, the main opportunities for reducing carbon footprint
lie upstream in their supply chain. We use CDP (formerly Carbon Disclosure Project) data on Scope 3 emissions (those embedded in products and services purchased) for 374 US firms to assess to what extent
they measure their supply chain carbon footprint. We use the breakdown of emissions into Scope 1, 2 and 3 from Huang et al. (2009) as
a benchmark, and estimate that firms who disclose to CDP currently
under-report Scope 3 emissions by 492 million tonnes of CO2-e, 60%
of their total estimated Scope 3 emissions.
2 - What Online Trading and Web Search Sites Data can
tell us about Demand for Remanufactured and used
Products?
Marta Jakowczyk, Joao Quariguasi, Andy Gibson, Luk Van
Wassenhove
In spite of the interest this topic draws from academics and practitioners alike, little is known about the demand for used and remanufactured
products. This paper illustrates how secondary data can be used to fill
this important gap in the literature. More specifically, we use data
drawn from (i) online search traffic, (ii) product specific data collected
from various other online sources and (iii) sales data for remanufactured products to test the hypotheses that overall interest and purchase
intention are moderated by product-specific determinants.
3 - Purchase Intention of Spanish Consumer: Results
from an Experiment about Remanufactured Laptops
Beatriz Jiménez-Parra, Sergio Rubio, Azucena
Vicente-Molina
The aim of this work is analysing the behaviour of consumers of remanufactured products. To this end, we conducted an experimental
simulation of a purchase situation, in which potential buyers had to decide which their preferences were, considering original and remanufactured laptops in different price scenarios. The results of this experiment
can provide some useful insights regarding the consumer behaviour of
remanufactured products, and contribute to the development of new
researching issues in the field of the Closed-Loop Supply Chain.
4 - System Dynamic Modelling of Carbon Storage by
Wood Products
Matthias Garbs, Jutta Geldermann, Martina Hesse
Wood products as a carbon storage delay the emission of carbon to
the atmosphere. The material wood utilization is already increasing in
Germany, but it is difficult to estimate the savings of carbon emission.
Moreover it is unclear how much a reinforced utilization or an extension of the life span of wood products could increase these savings.
Therefore a dynamic model based on system dynamics was been developed to estimate the development of the stored carbon in the future
and to analyze different scenarios for Germany.
1 - An Affinely Adjustable Robust Optimization Approach to the Operation of Heat and Power Systems
Marco Zugno, Juan Miguel Morales, Henrik Madsen
We consider the short-term operation of heat and power systems comprising heat production units, CHP plants as well as heat storages. This
is a multi-stage optimization problem under uncertainty, as heat demand and power prices are unknown at the time of making decisions
on the unit commitment and schedules. We cast the problem as a multistage robust optimization model where the decision is immune to deviations of the heat consumption within a budgeted uncertainty set.
Optimal recourse decisions as functions of the uncertainty are approximated via linear decision rules.
2 - Evaluating the Impacts of Priority Dispatch in the European Electricity Market
Giorgia Oggioni, Frederic Murphy, Yves Smeers
This paper compares the efficiency of the Nodal Pricing and European
Market Coupling organizations with and without priority of wind dispatch in the power system. The effects of these two wind policies are
measured by developing models that consider cases with different wind
penetration levels, existing capacities and endogenous investments, as
well as assumptions on the EU-ETS. Our analysis shows that Nodal
Pricing is more efficient than Market Coupling independently of the
wind policy applied. Priority dispatch may cause the collapse of Market Coupling when wind penetration is very high.
3 - Short-Term Effects of Optimal Wind-Pumped Hydro
Storage Energy offers in Day-ahead Electricity Markets
Agustín Alejandro Sánchez de la Nieta López, Javier
Contreras, João P. S. Catalão
This paper models an optimal joint offer of wind and pumped hydro
storage in a day-ahead market considering the imbalance penalty market. The problem is modeled as a stochastic mixed integer linear one,
whose objective function is to maximize the expected profit of the daily
operation. In this way two types of offers are analyzed: 1) optimal separate wind and pumped hydro storage offering and 2) optimal single
wind-pumped hydro storage offering. A risk measure will be calculated and a case study will be solved to see the solution in terms of
imbalances and profits.
4 - Strategic Offering for a Wind Power Producer: An
MPEC Approach
Luis Baringo, Antonio J. Conejo
Wind power producers have grown in some jurisdictions to clearly
dominant positions in the market. Under this context, we propose a
mathematical program with equilibrium constraints (MPEC) approach
for the offering strategy of a wind power producer that participates in
the day-ahead market, where it behaves as a price-maker, and in the
balancing market, where it buys/sells its production deviations. Uncertainties pertaining to wind power production and balancing market
prices are represented through a set of scenarios. The model is efficiently solved using available optimization software.
HA-10
Thursday, 8:30-10:00 - Room 122
DEA Theory I
Stream: Theoretical Developments in DEA
Invited session
Chair: Dimitris Despotis
HA-09
Thursday, 8:30-10:00 - Room 121
Dealing with Uncertainty and Renewable
Sources in Electricity Markets
Stream: Technical and Financial Aspects of Energy
Problems
Invited session
Chair: Luis Baringo
154
1 - Solving Small LPs to Determine Productive Efficiencies of Big Data
Wen-Chih Chen
This work presents a computation strategy to determine productive efficiency by solving small-size LP problems. The proposed strategy can
"control" the size of problems, e.g., no larger than 100 data points each
time, while it maintains the solution quality. The proposed strategy
can compute different measures, including radial and non-radial, and
different models based on different returns to scale assumptions. The
empirical results show that the proposed strategy can converge within
a reasonable number of iterations.
IFORS 2014 - Barcelona
2 - Resource Allocation Based on the Global Efficiency
and Pure Technical Efficiency
Meng Zhang, Jinchuan Cui
Data envelopment analysis has been successfully used in resource allocation problems. However, there are no allocation models that consider both the global and technical efficiency. Hence, our model aims
at maximizing the overall global efficiency of a DMU (Decision Making Units) set while maintaining each DMU’s pure technical efficiency.
To this purpose, we first discuss the optimal resources required by each
DMU. We prove that the DMU with the optimal resources is actually
a MPSS (Most Productive Scale Size). Based on this, the allocation
model is proposed and illustrated to be effective.
3 - Applied Cost Allocation: The DEA-Aumann-Shapley
Approach
Aleksandrs Smilgins, Jens Leth Hougaard, Jens Leth
Hougaard
In this paper we use the Aumann-Shapley rule to allocate costs of joint
production. Empirical application is often hampered by the two facts:
estimation of the cost function and production at non-efficient production costs. We solve the first problem by using convex envelopment of
data points. For the second problem we suggest to allocate the inefficiency in proportion to Aumann-Shapley prices. Finally, we show how
to overcome problems of infinite Aumann-Shapley prices, which may
occur at some specific points of the cost function.
4 - A Study on Two-Stage Network DEA Models with
Some Improvements
Gregory Koronakos, Dimitris Despotis
In this paper we provide a critical review of the two-stage network
DEA models proposed for the efficiency assessment of serial production processes by spotting a number of drawbacks. We focus on
processes that assume external inputs entering exclusively the second
stage beyond the intermediate measures. Then we provide adequate
modifications that remove the observed deficiencies. We illustrate our
models with numerical examples.
HA-12
3 - Comparing a Nondominated and a Scalarising Solution Approach for a Nonlinear Combinatorial Multiobjective Optimization Problem given a Limited Budget
Evert B. Schlünz, Pavel M. Bokov, Jan van Vuuren
The in-core fuel management optimisation problem refers to a problem of designing fuel assemblies loads for a nuclear reactor core. This
problem is typically multiobjective, nonlinear and combinatorial in nature. A limited computational budget is available for optimisation due
to expensive function evaluations performed by a reactor core calculation system. We compare a nondominated and a scalarising solution
approach, given this limited budget, using the cross-entropy method for
optimisation. The motivation behind the approach is discussed, along
with our results.
4 - On a Scheduling Problem with Sequence-Dependent
Setup Times
Jan van Vuuren, Alewyn Burger
In this talk we consider a scheduling problem in which the setup times
for jobs depend on the sequence in which the jobs are performed. We
show that the problem can be modelled as the well-known tool switching problem, which is tractable for small instances only. The problem
can, however, also be solved rather effectively in heuristic fashion by
decomposing it into two subproblems: a job grouping problem (which
can be modelled as a unicost set covering problem) and a group sequencing problem (which is a generalisation of the celebrated travelling salesman problem).
HA-12
Thursday, 8:30-10:00 - Room 004
Project Scheduling: Applications and
Generalizations
Stream: Project Management and Scheduling
Invited session
Chair: Karl Doerner
HA-11
Thursday, 8:30-10:00 - Room 113
Combinatorial Optimization: Applications
Stream: Combinatorial Optimization
Invited session
Chair: Jan van Vuuren
1 - The Application of the Economic Order Quantity and
Osmosis Methodologies to Self-Organising Traffic
Control
Mark Einhorn, Jan van Vuuren, Alewyn Burger
If one considers the green time afforded to an approach of a signalised
intersection as a commodity, then it is possible to apply the theory of
the Economic Order Quantity model to determine the optimal amount
of green time to be "ordered" by each approach as well as when it
should be ordered. A second traffic control strategy presented here is
inspired by the process of osmosis whereby the intersection acts as a
permeable membrane, and the movement of vehicles through the intersection depends on the "osmotic potential" on either side of the intersection.
2 - A Multi-Objective Approach
Dependent Facility Location
Andries Heyns, Jan van Vuuren
towards
Terrain-
The placement of facilities such as radars, watchtowers and solar farms
requires careful planning and is done according to very specific facility
and terrain-related requirements such as (inter)visibility and solar exposure. When placed in a networked environment (which may include
different facility types), multiple terrain-dependent and environmental
objectives and additional constraints magnify the model complexity
due to the conflicting nature of the objectives. The problem is solved
within a generic framework that includes geographical processing and
metaheuristic procedures.
1 - Strategic Construction Planning of Underground
Gas and Oil Storages with the Flexible ResourceConstrained Multi Project Scheduling Problem
Torben Schramme, Leena Suhl
The resource-constrained project scheduling problem (RCPSP) with
multiple projects and flexible resources was used to model a long-term
planning problem for building underground gas and oil storages. We
will show how that practical problem was mapped to that extended
RCPSP with the start times and durations of activities and the resource
allocation per time period as decision variables. A genetic algorithm
for solving that model under multiple objectives will be outlined. The
talk will be concluded with computational results and an outlook about
the general applicability of that method.
2 - Solution Approaches for a Close to Real-World Variable Profile Task Scheduling Problem
Roland Braune, Karl Doerner
We consider a special type of resource constrained project scheduling
problem arising from a real world scenario as found in a chemical research laboratory. Resource allocation of a task may vary over time
within a predefined range and thus implies non-constant execution duration. Multiple parallel resources are available for processing and the
tasks are subject to out-tree precedence constraints with min / max time
lags. Given a custom objective function, we propose both a MIP formulation and an advanced list scheduling heuristic for the problem at
hand and perform an experimental comparison.
3 - GRASP based Algorithms for Dynamic Job-Shop
Scheduling with Sequence-Dependent Setup Times
Fatma Selen Madenoğlu, Adil Baykasoğlu, Alper Hamzadayi
In this study, we consider DJSSP with release dates, due dates,
sequence-dependent setup times under machine failure, new job arrival by making use of GRASP. To the best of our knowledge this
is the first attempt to use GRASP for the DJSSPs. In GRASP based
scheduling procedure, we constructed active schedules by making use
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of G&T algorithm along with dispatching rules. SA algorithm and a
greedy search mechanism are used as local search procedures within
GRASP. The results have proven that GRASP based dynamic scheduling algorithm is an effective mechanism and able to handle dynamic
scheduling.
4 - A Complete View of the Scheduling Problem of
Chemotherapy Production with Expensive and Perishable Raw Materials
Jean-Charles Billaut, Thibault Drevon, Jean-François
Tournamille
The production of injectable chemotherapy preparations (requiring expensive and perishable cytotoxic drugs) is presented in details. Objective functions are of two types: one related to tardiness of production
and one related to waste of drugs. A greedy heuristic is proposed (figuring the schedule performed by the production center) and a Tabu
search. This study is based on a real production context, tested with
realist data sets. Results show that the use of the Tabu leads to a significant improvement, with non-negligible impact, both from the patient
and from an economic points of view.
4 - Solving the FMS Uncertainty by Deadlock Prevention
with a Critical Siphon Theory
Johannes Chiang
The main tasks of a FMS include process routing, selection of an operation sequence, etc.. For effective FMS operations, the use of resources among various competing jobs must be carefully controlled.
Deadlocks, which are undesirable in a FMS, may occur during its operation, i.e., under uncertainty. For general S3PGR2 is no longer valid,
mixed-integer programming (MIP) has to be modified to determine the
net is live. The paper develops a Critical Siphon theory and proposes a
revised MIP to fix the uncertainty that arose with deadlock.
HA-14
Thursday, 8:30-10:00 - Room 124
Advances in Nonlinear Optimization:
Theory and Applications I
Stream: Nonlinear Programming
Invited session
HA-13
Thursday, 8:30-10:00 - Room 123
Handling Uncertainty in Scheduling and
Lot-Sizing 2
Stream: Scheduling
Invited session
Chair: Alexandre Dolgui
Chair: Mikhail Y. Kovalyov
Chair: Goran Lesaja
1 - Second-Order Methods for Sparse Signal Reconstruction
Kimon Fountoulakis, Jacek Gondzio
In this talk we will discuss efficient second order methods for a family of l1-regularized problems from the field sparse signal reconstruction. The problems include total-variation, l1-analysis and the combinations of those two. Although first-order methods have dominated
these fields, we will argue that specialized second order methods offer
a viable alternative. We will provide theoretical analysis and computational evidence to illustrate our findings.
1 - Handling Uncertain Demands in the Dynamic Dial-aRide Problem
Samuel Deleplanque, Alain Quilliot
2 - An Optimization Approach to Model Selection for
Support Vector Regression
Andreas Fischer, Gerd Langensiepen, Nico Strasdat, Klaus
Luig, Thorsten Thies
The vehicle schedulings in the on demand transportation are made by
solving the Dial-a-Ride problem (DARP). This type of problem needs
a solution in a very short time once it is adapted to the dynamic context. We refine an insertion algorithm solving the dynamic DARP. It is
based on constraint propagation which handles all the time constraints:
time windows, the maximum ride and route times. We focus on an Insertability value which takes into account the impact of one insertion
on the future ones. We use it on the uncertain demands to allow the
possibility for these demands to be inserted.
For a good regression quality of Support Vector Regression (SVR)
models it is necessary to optimize a set of model parameters. To this
end, a bilevel program can be defined, where the upper level minimizes
an error on a subset of training samples and the lower level is the SVR
model based on the remaining training samples. However, such bilevel
problems can become large and are often treated by means of a certain
grid search over the model parameters. We suggest an optimization approach leading to tractable problems even for more than 2 parameters.
Moreover, performance results are presented.
2 - Analysis of the Role of Price Negotiations and Uncertainty in the Optimization of Coordinated Supply
Chains
Kefah Hjaila, Miguel Zamarripa, Antonio Espuña
3 - Improved Full Newton-Step Interior-Point Methods
for LO and LCP
Goran Lesaja, Kees Roos
This work aims to coordinate customers and suppliers SCs, and to apply a Multi-Objective optimization approach to the resulting network
considering the uncertain behavior of suppliers and markets (now: internals) associated with their characteristics and policies (pricing, efficiency, internal costs, internal recipes). Pricing and resources availability negotiations will be held to avoid any disruptions in the internal
suppliers caused by the uncertain behavior of the internal markets. Acknowledgements: AGAUR FI DGR-2012 and DPI2012-37154-C0201
An improved version of an infeasible full Newton-step interior-point
method for linear optimization is considered. In the earlier version,
each iteration consisted of one infeasibility step and a few centering
steps while in this version each iteration consists of only an infeasibility step. This improvement has been achieved by a much tighter estimate of the proximity measure after a feasibility step. However, the
best iteration bounds known for these types methods are still achieved.
Next, generalizations of the improved method to linear complementarity problems are considered.
3 - A Risk-based Approach to Robust Scheduling of a
Single Machine
Marcello Urgo, József Váncza
4 - Mixed-Integer Bilevel Programming with Upper-Level
Decision Variables that Appear at the Lower-Level
Objective but Not in Any of the Lower-Level Constraints
George Kozanidis, Eftychia Kostarelou
Robustness in scheduling addresses the capability to devise a schedule
with a given level of insensitiveness with respect to the disruptive effects of unexpected events. Facing the uncertainty entails the need of
optimizing a mean performance but also being prepared to the rare occurrence of very unfavourable events causing heavy losses. We present
a branch-and-bound approach to solve a single machine scheduling
problem aiming at optimizing a risk measure related to the distribution
of the maximum tardiness. The proposed approach is applied to an
industrial case in the machining tools sector.
We consider a class of mixed-integer bilevel programs whose upperlevel decision variables appear at the objective of the lower-level problem, but not in any of its constraints. We present a novel methodology
for generating valid inequalities to suitable relaxations of these problems, in which the so-called bilevel feasibility of the obtained solution
is not guaranteed. We develop an exact cutting plane solution algorithm that utilizes these valid inequalities, and we conclude with experimental results demonstrating its computational capabilities under
alternative problem formulations.
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HA-15
Thursday, 8:30-10:00 - Room 125
Revenue Management Application and
Theory
Stream: Revenue Management II
Invited session
Chair: Darius Walczak
1 - Challenges in RM & Pricing Optimization of ProductResource Networks
Darius Walczak
We review optimization challenges in product-resource networks
found in revenue management and pricing applications. Average network consists of thousands of products where each product consumes a
finite number of resources, and the objective is to select one of several
price points for each product so that expected revenue is maximized.
Due to dimensionality and stochasticity in the problem, real-life software has to rely on near-optimal controls. We present some of these
approaches. We also revisit calculating other business metrics, such as
expected demand, for a given solution.
2 - Shaping Demand to Match Anticipated Supply
Anant Balakrishnan, Sifeng Lin, Yusen Xia
Firms can exploit their information on inbound supplies to better match
demand with anticipated supply through dynamic pricing. We develop
an economic model to address short-run demand shaping decisions for
vertically differentiated products, i.e., to determine the prices for high
and low quality products in each period so as to dynamically segment
the market and maximize profits. We identify properties of the optimal
price and sales trajectories, and assess the benefit of dynamic pricing
versus myopic or sequential pricing approaches.
3 - An Efficient Pricing Method to Determine the Network Value of Influentials in Social Networks
Evren Guney, Volkan Çakır, Irem Düzdar, Abdullah Ozdemir
Companies use social networks to benefit from word-of-mouth marketing by influentials. Most of the previous studies focus on how to
maximize the number of individuals reached starting from an initial
set of influentials. However, many companies are focused on the total revenue. Hence, a modified objective function that maximizes total
revenue, instead of the number of individuals, is proposed. An efficient
pricing method to determine the network value of customers is developed and influence maximization is studied from the aspect of revenue
maximization and tested on certain real-life data.
4 - A Model for Competition in Network Revenue Management
Nishant Mishra
We study a model of competition in network revenue management
where multiple risk-averse players compete to satisfy uncertain consumer demand. For a linear inverse demand function, and for a symmetric game, we can come-up with closed form expressions for equilibrium quantities and prices, and we also establish some monotonicity
properties. We then numerically study asymmetric competition to generate further insights. For instance, we find that asymmetry with respect to risk aversion has the same effect as higher demand uncertainty
for the more risk averse competitor.
HA-16
Thursday, 8:30-10:00 - Room 127
Categorical Data Analysis and Preference
Aggregation
Stream: Intelligent Optimization in Machine Learning
and Data Analysis
Invited session
Chair: Michael Doumpos
HA-17
1 - Partial Orders Combining for the Object Ranking
Problem
Mikhail Kuznetsov, Vadim Strijov
We propose a new method for the ordinal-scaled object ranking problem. The method is based on the combining of partial orders corresponding to the ordinal features. Every partial order is described with
a positive cone in the object space. We construct the solution of the object ranking problem as the projection to a superposition of the cones.
To restrict model complexity and prevent overfitting we reduce dimension of the superposition and select most informative features. The
proposed method is illustrated with the problem of the IUCN Red List
monotonic categorization.
2 - An Interactive Approach for Multicriteria Selection
Problem
Anil Kaya, Ozgur Ozpeynirci, Selin Ozpeynirci
In this study, we work on multiple criteria selection problem. We assume a quasiconcave utility function that represents the preferences
of the decision maker (DM). We generate convex cones based on the
pairwise comparisons of DM. Then, we build a mathematical model
to determine the minimum number of pairwise comparisons required
to eliminate all alternatives but the best one. Using the properties of
the optimal cones and the pairwise comparisons, we develop an interactive algorithm. We conduct computational experiments on randomly
generated instances.
3 - Data-Driven Robustness Analysis for MCDA Preference Disaggregation Approaches
Michael Doumpos, Constantin Zopounidis
Preference disaggregation (PD) is involved with inferring multicriteria decision models from decision examples. The robustness of models and recommendations obtained through PD methods, has attracted
much interest. Previous research has mostly focused on uncertainties
related to preferential parameters of decision models. In the context
of PD, however, the data used to infer the model also affect the robustness of the results. In this presentation we discuss this issue and
present ways to enhance existing robust MCDA techniques in a datadriven context.
HA-17
Thursday, 8:30-10:00 - Room 005
Second-Order Conic Optimization
Stream: Interior Point Methods and Conic Optimization
Invited session
Chair: Jacek Gondzio
1 - Mixed-Integer Second-Order Conic Optimization
(MISOCO): Disjunctive Conic Cuts and Portfolio Models
Tamás Terlaky
The use of integer variables naturally occurs in Second Order Conic
Optimization problems, just as in linear and nonlinear optimization.
Thus, the need for dedicated MISOCO algorithms and software is evident. This talk gives some insight into the design of Disjunctive Conic
Cuts (DCCs) for mixed-integer CLO problems, and into the complexity of identifying disjunctive conic cuts. The novel DCCs may be used
to develop Branch-and-Cut algorithms for MISOCO problems. Preliminary computational experiments by solving classes of MISOCO
Portfolio Selection problems show the power of the DCC approach.
2 - Interior-Point Methods within Algorithms for MixedInteger Second-Order Cone Programming
Hande Benson
Second-order cone programming problems (SOCPs) have been wellstudied in literature, and computationally efficient implementations of
solution algorithms exist. In this talk, we study an extension: mixedinteger second-order cone programming problems (MISOCPs). Our
focus is on designing an algorithm for solving the underlying SOCPs as
smooth, convex NLPs, while using primal-dual regularization to introduce warmstarting and infeasibility detection capabilities. We present
numerical results obtained using the Matlab-based optimization package, MILANO.
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3 - On the Convergence Properties of the Central Path
for Second-Order Cone Optimization
Zhouhong Wang, Tamás Terlaky
4 - A New Visualization Technique for Enhancing Interactive Methods of Multiobjective Optimization
Ernestas Filatovas, Olga Kurasova, Dmitry Podkopaev
In this talk, we will discuss the limiting behaviors of the central path
when the barrier parameter goes to zero for Second-Order Cone Optimization (SOCO) based upon the optimal partition proposed by Bonnans and Ramirez (2005). First we will show that the optimal partition
for SOCO can be identified along the central path when the barrier parameter is small enough. Then some numerical examples are presented
to illustrate the convergence order of the central path of SOCO.
Interactive methods repetitively derive Pareto optimal solutions based
on Decision Maker’s (DM’s) feedback. The accumulation of obtained
solutions increases DM’s cognitive load. We propose to enhance interactive methods with a graphical tool which visualizes solution outcomes using dimensionality reduction. Our technique presents an intuitive map of the solution set and provides new interaction mechanisms
improving the capabilities of the DM to analyse the solution set and
navigate through it. We demonstrate our technique integrated it into an
interactive method of multiobjective optimization.
4 - The Second-Order Cone Programming Solver in the
Fico-Xpress Optimization Suite
Csaba Mészáros
In the talk we describe the design of the barrier solver in the FicoXpress Optimization Suite. The new feature of the optimization engine
implements a primal-dual interior point algorithm to solve large-scale
second-order cone programming problems. We outline the details of
the implemented algorithm and discuss topics related to the sparsity
and numerical features. We also outline the modeling tools that assist
the users to use the new solver feature.
HA-19
Thursday, 8:30-10:00 - Room 128
Advances on Demand and Supply
Planning in Consumer Goods and
Retailing
HA-18
Stream: Demand and Supply Planning in Consumer
Goods and Retailing
Invited session
Nonconvex Multiobjective Optimization II
Chair: Heinrich Kuhn
Chair: Winfried Steiner
Chair: Michael Katehakis
Thursday, 8:30-10:00 - Room 112
Stream: Multiobjective Optimization - Theory, Methods
and Applications
Invited session
Chair: Panos Pardalos
Chair: Julius Zilinskas
1 - Solving a Tri-Objective Location Problem via Evolutionary Algorithms
Pilar M. Ortigosa, Jose Fernandez, Aranzazu Gila Arrondo,
Juana López Redondo
In this work, the problem of locating a single semi-desirable facility
in the plane is considered. Three objectives are taken into consideration for the first time in literature. Two recent general-purpose multiobjective evolutionary algorithms, MOEA/D and FEMOEA, are suggested to obtain a discrete approximation of its Pareto-front. A computational study shows that both algorithms are suitable to cope with the
problem, although FEMOEA seems to obtain slightly better results,
especially for larger instances.
2 - Solution of Bi-Objective Discrete Competitve Facility
Location Problems
Algirdas Lančinskas, Pascual Fernandez, Blas Pelegrin, Julius
Zilinskas
We deal with solutions of the bi-objective discrete Competitive Facility Location Problem (CFLP) which is aimed at selection of locations
for a set of new facilities subject to (i) the maximization of their market share, and (ii) the influence to the facilities already in the market.
We present a heuristic algorithm, based on ranking of given candidate
locations, suitable for efficient approximation of the Pareto front of
the problem. We discuss the performance of the algorithm, evaluated
by solving different instances of the problem with different models of
customers’ behavior.
3 - Visualization of Pareto Sets in Multi-Objective Optimization Problems
Audrius Varoneckas, Antanas Zilinskas
Visualization of Pareto sets is of especial importance for the integration
of multi-objective optimization methods into interactive optimization
and optimal design systems. Recently several papers have been published on visualization of Pareto sets in objective space. We focus on
visualization of Pareto sets in the space of decisions. A method is developed to visualize a set of efficient points, e.g. which are found by
an investigated algorithm, as points in the two-dimensional space. The
proposed method is based on ideas of multidimensional scaling.
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1 - Pricing and Rebate Strategy in Retail Platforms with
Revenue Sharing
Hongyan Li, Shiming Deng
Given the intensive competition in retailing industries, all kinds of promotion are almost constantly running in various retailing platforms
such as department stores and online retailers etc. However, given the
complex operational context of large retailing platforms, many questions regarding promotion management remain unsolved. In this study,
we address a pricing and rebate optimization problem in a retail platform which consists of multiple suppliers. The analytic results show
the incentives of the system players. The optimal rebate strategies of
the retail system is addressed in details.
2 - Cyclic Joint Replenishment with Total Volume Discounts
Guoqing Wang
We study the multiple item joint replenishment problem in which all
items are ordered in cyclic manners and discounts dependent on the
total order volume are involved. We develop a heuristic to deal with
the problem and provide computational results.
3 - A Tractable Inventory Model with Random Lead
Times
Michael Katehakis, Laurens Smit, Flora Speksma, Dwi
Ertiningsih
We present a model for computing the stationary distribution of the
on-hand inventory in a continuous review system with Poisson demand
and Phase Type distributed lead time. We consider several additional
scenarios such as lost sales and unreliable suppliers. It is shown that
these models are successively lumpable. This leads to explicit analytical expressions for expected cost computations and minimization.
4 - Collaborative Supply Chains: A Case Study
Nicolas Danloup, Hamid Allaoui, Gilles Goncalves
Collaborative supply chains have become an important element for
recent years for many companies to improve their supply chain efficiency. Moreover, to be competitive in industrial world, the implementation of collaborative supply chain should give positive effect that can
be related to sustainable development. We first present several models
of collaboration. Then we present a case study about the collaboration
between several British retailers and some initial results.
IFORS 2014 - Barcelona
HA-20
Thursday, 8:30-10:00 - Room 129
Demand Response and Smart Grid
Infrastructure
Stream: Stochastic Optimization in Energy
Invited session
Chair: Vineet Goyal
1 - Pricing Mechanisms for Control
Desmond Cai, Adam Wierman
We propose a mechanism for a principal to purchase the right to control
the amount of consumption by a group of agents. Such a mechanism
could be applicable when the principal is more efficient at managing
the consumption of the agents than the agents themselves. We provide socially optimal and incentive compatible pricing schemes for
the principal. Our scheme has applications in demand-side management, where a utility company could manage the power consumption
of its end-use customers in conjunction with wholesale prices, to reduce overall energy costs of its end-use customers.
2 - Smart Homes with Price-Responsive Thermostats
Daniel Adelman, Canan Uckun
We develop a framework for a smart home’s thermostat to respond
optimally to dynamic electricity price signals, and for assessing the resulting market price equilibrium in a large service region. We develop
two mathematical models for smart price-responsive thermostats: a
"price-only" model which is not aware of home occupancy, and an
"occupant-aware" model. We present extensive numerical results
on ComEd’s residential customers’ prospective responses to dynamic
prices through air conditioners during a hot summer month, both in
isolation and in equilibrium.
3 - Stochastic Optimization and Risk Management for an
Efficient Planning of Buildings’ Energy Systems
Emilio L. Cano, Javier M. Moguerza, Antonio Alonso-Ayuso
Energy systems planning is becoming a big challenge for decision
makers at the building level. In addition to inherent systems complexity, several types of uncertainties arise. Through the appropriate
energy systems modeling, Decision Support Systems (DSS) based on
stochastic optimization models aid to reach optimal strategic decisions.
In this work, a Risk Management strategy is presented combining conflictive objectives, such as minimization of cost or emissions, with the
minimization of risk, applying the Conditional Value at Risk (CVaR)
approach beyond the classical portfolio scope.
4 - Optimal Price Rebates for Demand Response under
Power Flow Constraints
Vineet Goyal, Garud Iyengar, Quique Schwarz, Shuangyu
Wang
Demand side participation is essential for a real-time energy balance
in today’s electricity markets. We consider a price rebate approach
for demand response where the electric utility company offers price
rebates to consumers to reduce load. We study the problem of computing price rebates under AC power flow constraints that allows us to
model savings from the transmission losses. This is a non-convex optimization problem and we present a SDP based iterative heuristic. Our
computational study shows that the AC power flow based heuristic is
significantly better than other approaches.
HA-22
1 - Two-Dimensional Bin Packing Problems with
Irregularly-Shaped Pieces: Constructive Algorithms
Ramon Alvarez-Valdes, Julia Bennell, Antonio Martinez
Sykora, Jose Tamarit
We deal with a 2-Dimensional Bin Packing Problem (2DBPP) in which
bins are rectangular but the pieces to be cut from them have irregular
shapes. The problem arises in many practical situations, in the steel,
glass, or textile industries. We propose constructive algorithms consisting of two phases. In a first phase, a subset of the pieces still to be cut is
assigned to a new bin. Then, in a second phase, the pieces of this subset
are placed into the bin, one at a time, without overlapping. The computational experiments show that these constructive procedures obtain
high quality results
2 - A Constructive Heuristic for the Three-Dimensional
Bin Packing Problem with Transportation Constraints
Célia Paquay, Michaël Schyns, Sabine Limbourg
The aim of this work is to propose a Relax-And-Fix heuristic to build
a good initial solution to the 3D BPP. First, a mathematical formulation has been developed taking into account several types of constraints
such as the stability and fragility of the boxes to pack, their possibility to rotate, the weight distribution inside the bins and their special
shapes. Since this model contains a lot of integer variables, we have
decided to apply the Relax-and-Fix method. We have selected several
sets of variables to be the branching variables and carried out some
tests.
3 - An Algorithm for a Container Loading Problem with
Static Mechanical Equilibrium Conditions
António Ramos, José Fernando Oliveira, José Fernando
Gonçalves, Manuel Lopes
The container loading problem is a real-world driven, combinatorial
optimization problem that addresses the optimization of the spatial arrangement of cargo inside containers for maximizing the containers
space utilization. We propose an algorithm that combines a parallel
multi-population biased random-key genetic algorithm and a constructive heuristic algorithm responsible for decoding the chromosome,
generate a solution and evaluate its fitness considering a static stability
approach based on the static mechanical equilibrium conditions applied to rigid bodies.
4 - A MIP-Based Dual Bounding Technique for the Irregular Nesting Problem
Ryan J. O’Neil, Karla Hoffman
Optimal placement of irregular shapes with no overlap in a minimized
bounding box is a common manufacturing problem. Exact techniques
solve this problem using Integer Programs built from geometric data
of the shape pairs. These models use constraints based on the No-Fit
Polygon to eliminate overlap, but convergence time can be excessive,
due to loose primal-dual bounds. We present a new technique to compute dual bounds by allowing small amounts of overlap. This uses
fewer binary variables than NFP-based models and can be used iteratively to find optimal layouts.
HA-22
Thursday, 8:30-10:00 - Room 007
Competitive and Cooperative Games
Stream: Game Theory and Operations Management
Contributed session
Chair: Greys Sosic
HA-21
Thursday, 8:30-10:00 - Room 006
Cutting and Packing 1
Stream: Cutting and Packing
Invited session
Chair: Antonio Martinez Sykora
1 - The Role of Operations in New Product Development
Alliances
Niyazi Taneri, Arnoud De Meyer
In this paper we show that operational constraints coupled with resource allocation decisions have an impact on which of two possible
games two potential partners will prefer to play when engaging in product development efforts. We test and find support for the predictions
of the models with data from the pharmaceutical industry.
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IFORS 2014 - Barcelona
2 - Sequential Inspection Games
Boaz Golany, Yael Deutsch
We consider a sequential two-person non-zero sum game between an
inspector and an inspectee where both parties decide on their actions in
multiple sites. The inspector distributes a finite amount of inspection
resources across the entire horizon and across the sites. The Inspectee
determines the intensity of violation in each site in each period and its
total violation is constrained. We develop an efficient method to compute a Nash Equilibrium for this game and show that in each period the
inspector faces at most two options in allocating the budget across the
periods.
3 - Openshop Sequencing Games
Pedro Calleja
An openshop scheduling problem consists of n jobs (players), each of
them formed by m operations that have to be processed by m different
machines. By assuming that there is an initial schedule on all machines we associate to any openshop scheduling problem a TU game.
An openshop sequencing game assigns to every coalition the maximal
cost savings the coalition can obtain by means of admissible rearrangements. We study the class of unit time openshop sequencing games,
and we show that this class of games is balanced by providing a particular core allocation.
4 - Solution Concepts in Influence Games
Fabián Riquelme, Xavier Molinero, Maria Serna
We consider influence games, a cooperative simple game based on the
linear-threshold model of influence spread. In these games, a team
of agents or players forms a winning coalition if it is able to convince enough agents to participate in a task. We study the complexity of computing several solution concepts in such class of simple
games, among other ones, Banzhaf and Shapley-Shubik power indices,
core, least-core, kernel, nucleolus. This work was partially supported
by 2009SGR1137, MTM2012—34426, BecasChile (CONICYT), and
TIN2007—66523.
HA-23
Thursday, 8:30-10:00 - Room 008
Applying Analytics to Big Data for Driving
Big Outcomes
Stream: Analytics Application and Practice
Invited session
Chair: Arnab Chakraborty
1 - Multi-Channel Customer: Predicting the Next Best
Action with our Customers
Athina Kanioura
This topic delves into the realm of applying advanced analytics and Big
data for driving real time personalized customer interactions across
multiple touch points that improves customer intimacy, loyalty and
profitability.
2 - Rise of Intelligent Machines: Applying Analytics on
Machine to Machine Data (M2M) for Making Better Decision
Arnab Chakraborty, Jai Advani
This topic will touch upon the application of analytics on machine generated Big Data to drive innovative solutions and impactful outcomes.
3 - Solving Large-Scale Marketing Campaign Problems
Sebastien Lannez, Susanne Heipcke, Shalini Raghavan
This paper presents how FICO Xpress Optimization Suite has been
used to develop an optimization engine capable of solving large-scale
marketing campaign problems using a distributed, cloud-based solution that explores millions of decision alternatives. The presented system is FICO Analytic Offer Manager, AOM, a management system
that lets marketing campaign managers design, optimize and follow up
on the impact of his campaigns.
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4 - An integrated QFD framework linking quality management with marketing efforts
Konstantina Kamvysi, Katerina Gotzamani, Andreas
Andronikidis, Andreas Georgiou
The purpose of this paper is to provide a methodological framework
that integrates quality management and marketing efforts towards customer satisfaction. Specifically, this paper discusses the development
of a three-phased QFD process for planning strategic marketing activities by aligning customer requirements with the banks’ positioning
strategy and marketing mix tactics. Moreover, the utilization of QFD
in conjunction with LP-GW-Fuzzy-AHP fosters the capturing and prioritization of customers’ subjective judgments.
HA-24
Thursday, 8:30-10:00 - Room 212
Dynamics and Learning in Games
Stream: Dynamic and Repeated Games
Invited session
Chair: Panayotis Mertikopoulos
1 - Two-Timescales Game-Theoretical Learning with
Continuous Action Spaces
David Leslie
In this talk, I will present a framework for learning in games with continuous actions sets, and introduce the necessary stochastic approximation theory with which such processes can be analysed. I will then
demonstrate how this theory can be extended to a two-timescales system in which the values of actions can be estimated, and strategies
adapted, without any player actually observing the actions or rewards
of any other. This results in a system where ’individual learners’ can
converge successfully to Nash equilibrium, in zero-sum games and potential games.
2 - Inertial Game Dynamics and Applications to Constrained Optimization
Rida Laraki
We derive a class of inertial game dynamics by building on the wellknown "heavy ball with friction" optimization method. The dynamics
are generated by endowing the game’s strategy space with a Hessian—
Riemannian structure and then deriving the equations of motion for
a particle moving under the influence of the problem’s objective. By
specifying an explicit Nash embedding of the simplex, we study the
well-posedness of the dynamics and establish an inertial variant of the
folk theorem of evolutionary game theory, showing that strict Nash
equilibria attract all nearby strategy profiles.
3 - Large Deviations and Stochastic Stability in Games
Mathias Staudigl
Stochastic stability theory in games is concerned with understanding
the long-run behavior of learning dynamics in games under small perturbations. Various notions of stochastic stability have been introduced
in the literature. In this talk I present a new and general analysis for
stochastic stability in the small noise and the large population limit.
Our approach combines ideas from large deviations and optimal control theory to give a unified and robust definition of stochastic stability
in games with large player sets and general noisy best-response dynamics.
4 - A Continuous-Time Approach to Online Optimization
Panayotis Mertikopoulos
We consider a family of learning strategies for online optimization in
continuous time and we show that they lead to no regret in this context. This approach allows us to derive the no-regret properties of a
large class of discrete-time algorithms including as special cases the
exponential weight algorithm, online mirror descent and (vanishingly)
smooth fictitious play. In so doing, we obtain a unified view of many
classical regret bounds, and we show that they can be decomposed into
a continuous-time regret bound and a term which measures the difference between discrete and continuous time.
IFORS 2014 - Barcelona
HA-25
1 - Multiple Subgradient Descent Bundle Method for
Nonsmooth Multiobjective Optimization
Outi Wilppu, Napsu Karmitsa, Marko M. Mäkelä
Thursday, 8:30-10:00 - Room 009
Structuring Big Data
Stream: Data Mining
Invited session
Chair: Peter Gritzmann
1 - Sampling-Based Johnson-Lindenstrauss
dings
Felix Krahmer, Dustin Mixon
Embed-
A typical quality measure of randomized Johnson-Lindenstrauss (JL)
embeddings is that for arbitrary point clouds, the mutual distances are
approximately preserved with high probability. In this talk, we consider the scenario that only a part of the point cloud to be projected is
arbitrary and unknown and most points are known before hand. For
this setup, it is particularly useful to consider JL embeddings that arise
by randomly sampling from a not too large set of possible rows. Our
result has applications in fast approximate matrix multiplication.
2 - String Kernels for Financial Time Series Prediction
Blaz Zlicar, Simon Cousins
In this paper we present a novel application of string kernels: that is
the problem of financial time series prediction. Financial time series
are renowned for being extremely noisy. To overcome this we map
the recent price trajectories and trading volumes of an instrument to
a behaviour alphabet and use this alphabet to create strings representative of the underlying market conditions. We show that the string
representation of market conditions, coupled with the kernels ability to
generalise across non-contiguous substrings, can remove some of this
noise and deliver performance improvements.
3 - On Data Segmentation and its Applications
Peter Gritzmann, Andreas Brieden
We present a new algorithm for segmenting data and show some of
its recent benchmark and real world applications. Our method produces strongly feasible power diagrams, certain specific cell complexes, whose defining polyhedra contain the clusters, respectively.
Also we show that it can be performed efficiently. We close the talk
by indicating applications to various questions of predictive analytics
including risk prediction. (Joint work with Andreas Brieden, and, in
part, with Steffen Borgwardt)
4 - Predictive Analytics by Means of Constrained Clustering
Andreas Brieden, Peter Gritzmann, Michael Öllinger
In many different applications the precise prediction of a target value
based on a large amount of historical data is of crucial importance.
One natural approach is to determine homogenous subsets of data and,
given some cardinality constraints, to do the prediction by using the
law of large numbers for each of the subsets. Of course, the method
can be finetuned by applying more sophisticated stochastical methods
instead of the latter. This talk reports on several applications where
this approach outperforms well-known benchmarks. (Joint work with
Peter Gritzmann & Michael Öllinger)
HA-26
Thursday, 8:30-10:00 - Room 010
Nondifferentiable Optimization: Theory,
Algorithms and Applications I
Stream: Nonsmooth Optimization and Variational Analysis
Invited session
Chair: Manlio Gaudioso
HA-27
Many of the existing methods for multiobjective optimization use
scalarization instead of treating the objectives as they are. I will present
a new descent method, called Multiple subgradient descent bundle
method (MSGDB), where scalarization is not utilized. The MSGDB
method generalizes the well-known steepest descent method for unconstrained nonsmooth multiobjective optimization problems combining the ideas of the multiple-gradient descent algorithm and the proximal bundle idea. In this presentation, the idea of the MSGDB method
will be described and some numerical results are considered.
2 - Iterative Schemes to Solve Nonconvex Variational
Problems
Messaoud Bounkhel
In this work, we suggest and study the convergence of some new iterative schemes for solving nonconvex equilibrium problems in Hilbert
and Banach spaces. Many existing results have been obtained as particular cases, especially some recent results for solving equilibrium
problems involving convex sets.
3 - Generalized Cutting Plane for Convex Nonsmooth
Optimization
Manlio Gaudioso
We generalize the cutting plane model for convex optimization by allowing vertical shifting of the affine pieces. We provide some heuristic
rules to tune shifting parameters, and prove convergence of the method
in a bundle framework.
4 - A Levenberg-Marquardt Method with Approximate
Projections
Alfredo Iusem, Roger Behling, Andreas Fischer, Yinyu Ye
We present a version of the projected Levenberg-Marquardt method for
solving a system of nonlinear equations with additional convex constraints where the orthogonal projections onto the feasible convex set
are replaced by approximate and easily computable ones. We establish
an R-linear convergence rate for the method under certain reasonable
error bound conditions.
HA-27
Thursday, 8:30-10:00 - Room 213
Emerging Applications of Decision
Support Systems
Stream: Decision Analysis, Decision Support Systems
Contributed session
Chair: Marion Penn
1 - Optimum Periodic Inspection Interval and Replacement Policies for a One-Shot System with Minimal
Repair
Tomohiro Kitagawa, Tetsushi Yuge, Shigeru Yanagi
We analyzed maintenance and inspection polices for a one-shot system, considering the inspection interval and the limitation on the number of minimal repairs. We assume a system that consists of m units in
series. The system is inspected periodically to check units and minimal
repairs are carried out instantly when a unit failure is detected at the inspection. When totally n-th failure is detected, all units in the system
are replaced and become "as good as new". We optimize the number
of repairs until replacement and the inspection interval that minimize
the cost rate.
2 - Fast Timetable Generation for Railway Capacity Planning in Norway
Leonardo Lamorgese, Carlo Mannino
In a recent project we developed a timetable generation system to assist
Norway’s railway capacity planning department to evaluate the effect
of potential infrastructural decisions. Given a demand of trains for every line, a railway network is feasible if a conflict-free timetable exists
for all trains. To this end, a fast and possibly exact method is required.
The algorithm extends techniques which we have successfully applied
to real-time train dispatching and follows the so called "micro-macro"
approach which has recently drawn much attention in the literature.
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IFORS 2014 - Barcelona
3 - Evaluating Path-Dependencies in Networks: A Realoption Approach
André Mangelsdorf
So far path-dependency in interfirm-networks has not been covered in
literature in depth and we lack in the evaluation with realoptions in
this field of interest at all. Thereby, path-dependency can alter the optimal decision sequence by narrowing available action alternatives. Especially in networks with resource specialization this phenomena may
arise and thereby may influence the decision to enter a network. For the
determination of change in value of a network-entrance by emerging
path-dependency, a binomial-realoption model will be used for evaluation and thus giving decision support.
4 - Applying Decision Analysis to Public Policy Decisions: Case Study on Banning Neonicotiniods
Marion Penn, Lyn Thomas, Ian Rowley
Exploring the applicability of Decision Analysis to public policy decisions, via a case study on the recent banning of Neonicotiniods by the
EU to avoid harm to bees. This project combines time lines, decision
trees and layered influence diagrams to explore the issues considered
and the decision criteria employed. Providing insight into the problem itself and the public positions presented by a variety of interested
groups.
HA-29
Thursday, 8:30-10:00 - Room 011
OR in Mining
Stream: OR in Petrochemicals and Mining
Invited session
Chair: Eduardo Moreno
1 - A Network-Flow based Algorithm for Scheduling Production in Multi-Processor Open-Pit Mines Accounting for Metal Uncertainty
Amina Lamghari, Roussos Dimitrakopoulos
We consider a variant of the open-pit mine production scheduling problem, accounting for metal uncertainty and multiple destinations for the
mined material. The problem is formulated as a two-stage stochastic
problem with recourse, and a heuristic based on network flow techniques is developed to solve this formulation. Numerical results are
provided to indicate the efficiency of the proposed solution method to
generate good solutions in relatively short computational times and its
superiority over recent algorithms from the literature.
2 - Using Direct Optimisation Methodologies for Deterministic and Stochastic Open Pit Production
Scheduling
Eduardo Moreno, Daniel Espinoza, Marcos Goycoolea,
Orlando Rivera
Given a block-model of an open cut mine, a production schedule defines which blocks should be extracted, when to extract them, and what
to do with them once extracted. Recent developments have made the
IP formulation of this problem computationally viable in real-sized instances. We compare the performance of the IP and the conventional
nested pit (NP) approaches on 5 publicly available block models. We
also present how this IP approach can be adapted to consider grade and
prices uncertainties, allowing to solve two-stage stochastic problem up
to near-optimality on real-sized problems.
3 - Stochastic Programming applied to Mine Planning
under Geological Uncertainty with Differents Levels
of Information
Gonzalo Nelis, Nelson Morales, Julian Ortiz
Production scheduling in mining involves decisions like extraction periods and destination of mine material to maximize value. However, information about the deposit is limited when these decisions are made,
hence they risk being suboptimal because they are based on estimations of grades and others. It follows that considering variability in the
scheduling process may lead to better decisions for the industry. In this
work, we use geostatistical tools to produce geological scenarios and
stochastic programming in order to evaluate their impact on schedule
for different levels of information.
HA-30
Thursday, 8:30-10:00 - Room 012
Recent Models on Cooperative Games
and Integer Programming
Stream: Allocation Problems in Game Theory
Invited session
Chair: Osman Palancı
Chair: Mehmet Onur Olgun
1 - Model for Evaluating Strategies for Overload Relief in
Oversubscribed Clouds
Merve Unuvar, Salman Baset
To maximize revenue and fully utilize available capacity in a data center, the cloud providers oversubscribe physical resources such as CPU,
memory, disk and network, which, if not managed carefully, can lead
to overload. In this work, we are proposing a Mixed-Integer Programming (MIP) model to relieve the overload by migrating or terminating
user applications on an overloaded host, while meeting the Quality of
Service is guaranteed. We solve the proposed MIP model by using a
relaxation induced local search algorithm and compare our results with
a default ILOG MIP solver.
2 - On the Grey Shapley Value
Serap Ergun, Osman Palancı, Sirma Zeynep Alparslan Gok
The Shapley value is one of the most widespread concepts in cooperative game theory. This paper focuses on the Shapley value for cooperative games where the set of players is finite and the coalition values
are interval grey numbers. The grey Shapley value is characterized
with the aid of the properties of additivity, efficiency, symmetry and a
dummy player, which are straightforward generalizations of the corresponding properties in the classical cooperative games.
3 - Cooperative Grey Games with Allowing for Stock
Outs
Mehmet Onur Olgun, Gultekin Ozdemir
Inventory management studies to minimize the total costs per unit time
and to determine the quantity of the stocked material to be ordered. A
system on which the information is partly known and partly unknown
is called the grey information. In this work, we extend the results of
Meca et al. (2004) depending on the grey information revealed by the
individual firms. We introduce cooperative grey games with allowing
for stock outs, and focus on sharing ordering cost rule (SOC-rule) to
distribute the joint cost.
4 - Cooperative Games and Bubbles
Osman Palancı, Sirma Zeynep Alparslan Gok,
Gerhard-Wilhelm Weber
The involvement of uncertainty in cooperative game theory is motivated by the real world where noise in observation and experimental
design, incomplete information and further vagueness in preference
structures and decision-making play an important role. In this study, a
new class of cooperative games namely the cooperative bubbly games,
where the worth of each coalition is a bubble instead of a real number
is presented. Further, a new solution concept the bubbly core is defined. Finally, the properties and the conditions for the non-emptiness
of the bubbly core is given.
HA-31
Thursday, 8:30-10:00 - Room 013
Network Design
Stream: Telecommunications and Networks
Invited session
Chair: Markus Leitner
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IFORS 2014 - Barcelona
HA-33
1 - The Capacitated Minimum Spanning Tree Problem
with Non-Homogeneous Capacities
Efrain Ruiz, Maria Albareda Sambola, Elena Fernandez
2 - Application of Inequality between Arithmetic and Geometric Mean to Optimization of Economic Functions
Zrinka Lukac, Vedran Kojic
In this work we present an extension of the capacitated minimum spanning tree problem (CMST) in which the capacities of the subtrees are
not homogeneous. Such capacities depend on the vertices, and therefore are defined by the vertices that are selected to be directly connected to the root vertex. A formulation and a solution algorithm are
proposed, and results over test instances are presented.
Differential calculus is a powerful technique commonly used to solve
optimization problems in economics. However, its implementation is
not always simple. In this paper the application of inequality between
arithmetic and geometric mean (AGM inequality) is considered as an
alternative way to optimize certain economic functions. The paper emphasizes the advantage of AGM inequality over the differential calculus technique in the calculation of stationary points and the optimal
values of the observed functions.
2 - The Node-Quadratic Prize-Collecting Steiner Tree
Problem
Markus Sinnl, Markus Leitner, Ivana Ljubic
We introduce the node-quadratic prize-collecting Steiner tree problem:
We are given a graph with node revenues, edge costs and interaction
costs between pairs of nodes. The goal is to find a subtree, s.t., the
difference between revenues and cost is maximized. The problem has
applications in bioinformatics. We model the problem as quadratic
program and transform it into an integer program (IP). We investigate
the polytope associated with this IP to derive valid inequalities and
show that some of them are facet-inducing. A computational study to
complement our theoretical work is also done.
3 - A Polyhedral Study of the Diameter Constrained Minimum Spanning Tree Problem
Markus Leitner, Luís Gouveia, Ivana Ljubic
We consider the diameter constrained minimum spanning tree problem (DMSTP) on a graph. Given an edge-weighted undirected graph,
the objective is to find a minimum-weight spanning tree such that the
number of edges on the path between any two nodes does not exceed a
given diameter D. In this work, we study integer programming models
for the DMSTP in the natural space of variables, i.e., in the space of
undirected edge design variables. We introduce several new classes of
facet-defining inequalities that are based on so-called jump inequalities.
4 - Mathematical Programming Models for Traffic Engineering in Ethernet Networks Implementing the Multiple Spanning Tree Protocol
Martim Joyce-Moniz, Bernard Fortz, Luís Gouveia
The Multiple Spanning Tree Protocol (MTSP), used in Ethernet networks, maintains a set of spanning trees that are used for routing the demands in the network. Each spanning tree is allocated to a pre-defined
set of demands. We present mixed-integer programming models for the
Traffic Engineering problem of optimally designing a network implementing MTSP, such that link utilization is minimized. This is the first
approach that focuses on using exact methods to solve this problem.
We also propose a binary-search algorithm that efficiently produces
near-optimal solutions for the problem.
3 - Changing Production Chain by using 3D-Printing
Maria Mavri
Production chain is the procedure of transforming raw materials into
goods. Many and different steps are necessary in order to convert available resources to products such as planning, manufacturing, selling.
Recently, the above procedure seems to be changed. 3D-printing restructures the steps of the production chain. Customized products,
small or big markets could be served without enabling companies to
warehouse or produce goods with large cost. The scope of this paper
is to describe changes, which will be produced in production chain by
using 3D-printing technology.
4 - Analytical Hierarchy Process and SCOR Model to
Support Supply Chain Re-Design: A Case Study in
an Airline MRO Provider
Jaime Palma
In a supply chain re-design effort, it is better to focus on the process or
processes with the highest importance. A solution is presented here to
identify first the relevant processes using the Supply Chain Operations
Reference (SCOR) model, then to use Analytical Hierarchy Process
(AHP) for process selection. AHP can aid in deciding which supply
chain processes are better candidates to re-design in the light of predefined criteria. We propose a two level criteria structure, represented by
SCOR model performance attributes and metrics level 1.
HA-33
Thursday, 8:30-10:00 - Room 015
Defence and Security Applications V
Stream: Defence and Security Applications
Invited session
Chair: Ana Isabel Barros
HA-32
Thursday, 8:30-10:00 - Room 014
Supply Chain Concepts
Stream: Production Management & Supply Chain
Management
Contributed session
Chair: Jaime Palma
1 - Sustainable Supply Chain Management: Developing
a Framework through Conceptual Modelling
Norma Harrison, Tayyab Amjed
The research and implementation of environment-friendly and
socially-responsible supply chain practices are minimal. This study,
embedded in academic literature and industry publications, treats sustainable supply chain management as a meta-construct and develops
conceptual models for sustainable planning, procurement, manufacturing, transportation and warehousing. These are grounded in stakeholder theory, the resource-based view, triple bottom line, and supply
chain operations reference models.
1 - Risk Analyses for some Vulnerability Models of Industrial Control Systems
Alla Kammerdiner
Industrial control systems are facing new security challenges. Infrastructure, industrial and facility processes are increasingly interconnected. Failures in one process may result in disruption of others. If
power generation is controlled by energy consumption, the compromised data on consumption may affect generation and transmission.
This work investigates how our ability to protect critical infrastructure
depends on the topology of the network system and the vulnerability
of the control components. New models are proposed and their risk
analyses are performed via stochastic optimization.
2 - Combining Hard and Soft Evaluation of Security Risk
Factors
Leandro Teixeira, Antonio Rodrigues
The configuration of surveillance resources in the waterside area of a
port can be supported by risk maps. These maps result from the combination of several factors, which have to be estimated from geographic
and oceanographic data as well as from expert judgments. We provide
and illustrate a methodology, based on utility theory, for the elaboration of both types of estimates and for their combination.
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IFORS 2014 - Barcelona
HA-34
3 - Probabilistic Influence Diagrams for Modelling Influence Operations
Ken McNaught
We consider a problem relevant to military influence operations. A
high-level mission can be decomposed into lower-level objectives and
tasks. A typical way of representing this is as an effects tree. While this
is a useful description of the problem, a decision analytic influence diagram offers a more flexible representation. It can provide support for
resource allocation decisions by allowing the analyst to model the relationship between resource commitment, together with its associated
cost, and the likelihood of achieving high-level objectives, together
with their associated benefits.
4 - Simulating Anti-Submarine Warfare with MANA
Willem Knippenberg, Wouter Noordkamp, Herman Monsuur,
René Janssen, Raymundo Hordijk
The agent-based simulation programme MANA is a military oriented
tool for exploring scenarios. This research focuses on the suitability
of MANA as a simulation-tool for exploring ship-design concepts in a
premature state of the development. For this end, an Anti-Submarine
Warfare scenario has been modelled in MANA. The procedure of the
model and the output of the simulation are both compared with a highly
detailed physics-based programme. It appears that MANA is suited for
quick analyses, but becomes limited when scenarios become more and
more complex.
4 - The Limit Order Book in a High Frequency Regime
Peter Lakner, Joshua Reed, Sasha Stoikov
We model the one-sided limit order book for sell orders as a measurevalued process. Limit orders are placed on the book according to a distribution which varies depending on the current least expensive price,
and market orders remove from the book the current least expensive
price. We consider the order book in a high frequency regime in which
the rate of incoming limit and market orders is large and traders place
their limit sell orders close to the current best price. We provide weak
limit for the scaled order book process, and study the transient and
long-run behavior of the limit.
HA-35
Thursday, 8:30-10:00 - Room 131
Analysis and Management on Risk and
Security
Stream: Stochastic Modeling and Simulation in Engineering, Management and Science
Invited session
Chair: Silja Meyer-Nieberg
Chair: Erik Kropat
Chair: Dimitrios Vlachos
HA-34
1 - Containerization and Performance Evaluation in Port
Transport: Case of the Extra Zone Port ZEP of the
BMT Company-Bejaia
Fazia Aoudia-Rahmoune, Djamil Aïssani
Thursday, 8:30-10:00 - Room 016
Financial Modeling 1
Stream: Decision Making Modeling and Risk Assessment in the Financial Sector
Invited session
Chair: Dave Strugnell
1 - On the Ruin Probabilities of a Multidimensional Risk
Model
Tatjana Slijepcevic-Manger
Multidimensional models with common arrival process describe situations where each claim event produces more than one type of claim.
One example is motor insurance where an accident could cause claims
for different types of bodily injuries and property damages. We consider a multidimensional insurance risk model perturbed by Brownian
motion. An explicit asymptotic estimate is obtained for the finite-time
ruin probability in the heavy-tailed claims case.
2 - Real Option Valuation of Sequential R&D Investment
Michi Nishihara
This paper develops an investment timing model of R&D involving
research duration, a growth opportunity, rival preemption, technological and market uncertainty, and debt financing. We find that with the
slightest threat of preemption longer duration can delay investment.
Higher uncertainty of duration speeds up investment and enhances the
project value especially with the fear of preemption. Higher uncertainty of technological success increases the growth option value and
accelerates investment. These findings are consistent with the empirical evidence.
3 - Decision-Making
Strategy
Dave Strugnell
for
Pre-Retirement
Investment
Decision-making over long-term investment strategy for retirement
savings requires models of investor risk preferences and returns on
available assets, both of which are subject to error. We argue that optimal strategies should be robust to reasonable variation in key model
parameters, and present a range of stochastic models of asset class returns for the South African market. We further consider features of
the risk preference model essential for consistency with empirical evidence and intuition, informing tentative conclusions regarding asset
allocation strategies for retirement purposes.
164
In the era of globalization and liberalization of international trade, developing countries have little choice to follow the trend and build capacity to cope with change and the increase in international trade. This
is only possible by perfecting platforms leading receptions and sends.
That is why it is essential to attach great importance to port treatment.
In this work, we analyze container’s movements of the ZEP after modeling, thereafter to make a simulator that allows us to evaluate its performance of the ZEP in current conditions and to provide for variations
of parameters in the future.
2 - A Simulator for Distributed Algorithms
Malika Yaici
The complexity of distributed systems led to the need to evaluate them
using simulation. To model a distributed system we need to determine the number of nodes, their behavior and the complex relationships between them. Because of the similarity between the concepts of
agent in a multi-agent system and component in a distributed system,
a distributed system has been modeled using agents. The paper is on
the conception and realization of a simulator of distributed algorithms
based on agents using the multi-agent platform JADE.
3 - Design of Cost Efficient, Sustainable and Secure
Food Supply Chains
Dimitrios Vlachos, Christos Keramydas, Naoum Tsolakis,
Eleftherios Iakovou
In this research we firstly present a quantitative analytical costoptimization model for sourcing in perishable agri-food supply chains
taking into account service level and dietary preferences. We then
discuss a more generic framework for agri-food supply chain policymaking, which embraces sustainability, food nutrition, and security aspects. A System Dynamics methodology is employed that captures
the effect of environmental and social regulatory interventions on cost,
quality, and security along the supply chain.
4 - Mathematical Programming as a Tool for Virtual Soccer Coaches: A Case Study of a Fantasy Sports
Game
Guillermo Durán, Flavia Bonomo, Javier Marenco, Javier
Marenco
This presentation addresses the potential of mathematics to support
sports decision making using as a test case a fantasy soccer game organized by an Argentinian newspaper. Two mathematical programming
IFORS 2014 - Barcelona
models are presented that choose a virtual team lineup for each round
of the Argentinian soccer league. The a priori design creates a competitive team for the game, while the a posteriori model determines what
would have been its optimal lineup once all the results are known. The
a priori model was entered in the game, achieving results that positioned it among the highest scoring participants.
HA-36
Thursday, 8:30-10:00 - Room 132
Sustainability and Environmental
Management
Stream: OR in Agriculture, Forestry and Fisheries
Invited session
Chair: Israel Quintanilla
Chair: Marina Segura
1 - Public Preferences for Multifunctional Agriculture
System, using Analytic Hierarchy Process. Differences in Calculating Priorities
Inmaculada Marqués, Baldomero Segura
Multicriteria analysis (MCA) and the Analytical Hierarchy Process
(AHP) can help assess the social priorities to integrate them into the
decisions policies with the aim to maximize the use of the agricultural system. However different methods have been developed to derive priorities. These methods are derived from different concepts of
the estimation quality criteria and under different assumptions about
the perturbation factor structure. In this paper we present the results
of comparison of these prioritization techniques among the most commonly used and recommended methods in literature.
2 - Poultry and Olive Associated Production: A Multicriteria Analysis of Sustainability
Luisa Paolotti, Cesare Castellini, Antonio Boggia, Lucia
Rocchi, Adolfo Rosati
This paper aims to compare three different poultry production systems
in term of sustainability assessment (economic, social, environmental indicators) through a multicriteria method. The systems compared
are a conventional broiler farm and 2 free-range systems (10m2 pasture/bird), one where the chickens forage in a pasture, and the other
which combines the pasture in an olive orchard. The study shows how,
especially from an environmental perspective, the poultry system associated with the olive oil production reduces the land use and some
agronomic processes necessary in olive oil production.
3 - Management and Valuation of Ecosystem Services of
Mediterranean Natural Parks
Marina Segura, Concepcion Maroto, Concepción Ginestar
Studies of a natural parks network revealed the stakeholders’ difficulty
to prioritize the ecosystem services directly. In addition, there is a
lack of Decision Support Systems to manage environmental services,
which are the most important in Mediterranean protected areas. As
these services are free, their management should be supported by the
society. We propose a multiple criteria methodology to manage and
evaluate the ecosystem services by using group decision making. We
define criteria, indicators and methods for allocating resources to the
most important services for the stakeholders.
4 - A Regional Assessment of Sectorial, Environmental and Social Risks from Livestock Farms by using
Multi-Criteria Techniques
Israel Quintanilla, Áurea Gallego Salguero, Consuelo Calafat
Marzal, Concepcion Maroto
The European livestock sector is under strong social and legal pressure. The laws and regulations focus on defining minimum distances
between farms and urban centres and/or other farms. The main environmental issue is the risk of groundwater contamination and the
complaints due to odours represent a social risk. The objective of
this study is to assess the situation of Valencian livestock including
the regulations, as well as environmental and social risks. AHP and
PROMETHEE methods have been used to involve stakeholders and to
classify farms in order to support agricultural policy decisions.
HA-38
HA-37
Thursday, 8:30-10:00 - Room 017
Multiobjective Optimization in Asia, and
Related Subjects
Stream: Multiobjective Optimization
Invited session
Chair: Tetsuzo Tanino
Chair: Tamaki Tanaka
1 - Using a Maximizing Set Method to Rank Alternatives
under Fuzzy MCDM
Ta-Chung Chu
Most ranking methods cannot present connection by formula between
ranking procedure and the final fuzzy evaluation values of alternatives under fuzzy multiple criteria decision making (MCDM) model.
This work suggests a maximizing set method to resolve this limitation.
Membership functions of final fuzzy evaluation values in the suggested
fuzzy MCDM model can be developed. A maximizing set method
from Chen (1985) is used to defuzzify these values to rank alternatives, where ranking procedure can be clearly displayed by formulas.
A numerical example shows feasibility of the suggested method.
2 - Some Existence Criterions for Solutions to a Class
of Generalized Equilibria under Multi-Objective Multifunctions
Poom Kumam, Parin Chaipunya
The concept of an equilibrium plays a vital role in the theory of optimization. In this present article, we consider the generalized equilibria and propose some sufficient conditions under which the particular
multi-objective multifunctions enjoy the existence of such equilibrium.
By products of our results are also presented subsequently.
3 - Observation on Quasiconvexity for Set-Valued Maps
via Scalarization
Tamaki Tanaka, Syuuji Yamada
In general, there are several types of quasiconvexity for set-valued
maps and some gaps between original set-valued maps and their scalarized ones by marginal functions. We report mathematical characterization of certain types of quasiconvexity for set-valued maps via scalarization and consider such application to multiobjective problems.
4 - Multiple-Criteria and Group-Decision Making in the
Fleet Selection Problem for a Public Transportation
System
Jacek Zak
The paper presents an application of combined MCDM-GDM methodologies to rank different tram—cars. The evaluation is based on a consistent family of criteria that includes different aspects and interests
of different stakeholders (passengers, operator, local authorities). The
way of defining and modeling decision maker’s (DM’s) and stakeholders’ preferences, and reaching the group compromise along two separate frameworks: "ex-ante" and "ex-post" is presented. Computational
results generated by different ranking methods (AHP-ANP, Electre,
Promethee) are demonstrated.
HA-38
Thursday, 8:30-10:00 - Room 214
Soft OR / Systems Practice
Stream: Soft OR / Systems and Multimethodology
Invited session
Chair: Ashley Carreras
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HA-39
IFORS 2014 - Barcelona
1 - Systemic Thinking in Management Practice: Using
Soft Systems Methodology in Family Businesses in
Catalonia
Alberto Paucar-Caceres, Joan Roma, David Sierra, Diane Hart
This paper claims that ’soft’ OR can provide important tools when
making sense of the complexity faced by organisations, particularly
family businesses. There is a reluctance to accept these approaches and
we explore some of the reasons. Soft Systems Methodology is used to
conduct an organised, systemic reflexion to integrate different visions,
perceptions and interests amongst the stakeholders through a series of
workshops for top and middle managers from a group of small family
businesses in Catalonia. The paper should be of interest to systems
practitioners, consultants and managers.
2 - Managing the Client-Consultant Relationship
Ashley Carreras, L. Alberto Franco, Thanos Papadopoulos,
Elena Tavella
The communication between client and consultant is always a critical
factor in any project, this is particularly the case when a project requires the use of Problem Structuring Methods. Both the client and
the consultant undergo a process of transformation in their respective
understandings of the problem at hand and the nature of the techniques that will help them reach a successful conclusion. Drawing
upon Tsoukias’ concept of a Productive Dialogue we analyze the structure and content of conversations from real projects to see how this
communication can be understood and enhanced.
3 - Evaluating the Value of PSM use in Urban Planning
Projects
Ine Steenmans
There has been significant recent interest in evaluating the performance
of PSMs. The aim of this practice-based project is to develop evidence
supporting arguments for greater use of PSMs in the field of urban
planning, which is currently undergoing a ’turn’ towards more collaborative practices. Critical, however, to this intended outcome, is
a framework capable of evaluating longitudinal changes in the value
added by PSMs to both the content and the process of planning. This
paper presents such an evaluation framework and reflects on the processes of its validation and implementation.
4 - A Simulation Study of a Combination System of Enterprise Resource Planning (ERP) and Informality
Yucan Wang, Andrew Greasley, Pavel Albores
Current ERP research is limited to system implementation, not focusing on the flexibility of ERP to respond to changes in everyday
business. Therefore, this study explores a combination system of an
ERP and informality, to provide organisations of efficiency and flexibility simultaneously, by using a mixed method. The qualitative part
aims to define a new system corresponding to the constraints of using
a single ERP. The quantitative part contains a discrete-event simulation study that is intended to examine the impact of operational performance when a company implements the hybrid system.
HA-39
Thursday, 8:30-10:00 - Room 018
Recent Developments in the SCIP
Optimization Suite
Stream: Discrete and Global Optimization
Invited session
Chair: Gerald Gamrath
1 - SoPlex 2.0
Matthias Miltenberger, Ambros Gleixner
In this talk we present the latest developments of SoPlex, the linear
programming solver of the SCIP Optimization Suite. SoPlex has been
used since almost 20 years to reliably solve LPs in the academic world
as well as practical problems of industry partners. For our current release we created an entirely new interface and introduced several new
features. Most important being the ability to solve LPs exactly. Due
to the clever combination of floating point and rational arithmetic the
exact solving process is barely slowed down compared to a standard
precision run.
166
2 - Presolving in SCIP
Dieter Weninger, Gerald Gamrath, Thorsten Koch, Alexander
Martin, Matthias Miltenberger
Presolving attempts to eliminate redundant information from the problem formulation and simultaneously tries to strengthen the formulation. It can be very effective and is often essential for solving instances.
Especially for mixed-integer programming problems, fast and effective
presolving algorithms are very important. We show some standard and
newly developed presolving algorithms of the non-commercial solver
SCIP.
3 - Generic Branch-Price-and-Cut
Jonas Timon Witt, Martin Bergner, Gerald Gamrath, Marco
Lübbecke, Christian Puchert
Reformulating a given mixed-integer program by the use of DantzigWolfe decomposition leads to a potentially stronger linear programming relaxation. The reformulated problem can be solved by applying
a branch-price-and-cut algorithm. Our generic branch-price-and-cut
solver GCG, which is based on SCIP, automatically detects the structure of the constraint matrix belonging to a given mixed-integer program, performs the decomposition, and solves the reformulated problem via branch-price-and-cut. We present some important features and
report on the latest experiments with GCG.
4 - Recent Branching Improvements in SCIP
Gerald Gamrath
One of the essential components of a branch-and-bound based mixedinteger linear programming (MIP) solver is the branching rule. We report on recent branching improvements developed within the academic
MIP solver SCIP, including strong branching with domain propagation
and cloud branching.
HA-40
Thursday, 8:30-10:00 - Room 019
Innovations in Meta-Analytics III
Stream: Meta-Analytics: A Marriage of Metaheuristics
and Analytics
Invited session
Chair: Kenneth Sörensen
Chair: Roberto Battiti
Chair: Marc Sevaux
1 - An Enhanced Particle Swarm Optimisation Method
Designed for Real-Time Applications by using Neural Network
Cedric Leboucher, Stéphane Le Menec, Patrick Siarry,
Hyo-Sang Shin, Rachid Chelouah, Antonios Tsourdos
This paper proposes to reduce the computational time of an algorithm
based on the combination of the Evolutionary Game Theory (EGT)
and the Particle Swarm Optimisation (PSO), named C-EGPSO, by using Neural Networks (NN) in order to lighten the computation of the
identified heavy part of the C-EGPSO. The EGT part consists in determining an Evolutionary Stable Strategy iteratively by solving a system
of Ordinary Differential Equations and this part might be computationally intensive. Therefore, it is proposed to use NN to decrease the
computational time and obtain a real-time algorithm.
2 - A Dandelion Code Extension
Carlos Luna-Mota, Elena Fernandez
The Dandelion Code has proven to be a useful tool to represent spanning trees in population based algorithms. However, the good properties of the Dandelion Code can be exploited in a broader set of algorithms, such as local search or Latin hypercube sampling. The Partially
Ordered Neighborhood Structure associated with an extension of the
Dandelion Code is introduced and its good properties are illustrated
with examples.
IFORS 2014 - Barcelona
HA-42
3 - Improving the Performance of Metaheuristics with
Solution Polishing
Christian Blum
4 - The Inventory Routing Problem for Perishable Products: A Green Approach
Jacqueline Bloemhof, Mehmet Soysal, Jack van der Vorst
The term "hybrid metaheuristics" refers to research which is concerned
with the development of efficient combinations between metaheuristics and other techniques for optimization. In this work we propose the
combination of a metaheuristic known as ant colony optimization with
the "solution polishing" option of CPLEX. Solution polishing is the
implementation of a branch & cut approach with the aim to improve a
given solution rather than proving optimality. We show in the context
of various string selection problems that "solution polishing" can help
to make a metaheuristic more efficient.
The transition to sustainable food supply chain management has
brought new key logistical aims beside cost minimization. The foremost ones of the new aims are the abilities to control product quality in
the supply chain, and to reduce environmental impacts of operations.
We develop a stochastic model for the inventory routing problem that
manages relevant main key performance indicators of total waste, total
quality lost, total working hours for drivers, total cost and total energy
use (emissions) simultaneously. The stochastic model captures the risk
associated with uncertain demand.
4 - Meta-Analytics for Extreme Personalization in ECommerce
Roberto Battiti
Learning and Intelligent OptimizatioN (LION) means combining
learning processes with modeling, problem-solving, and optimization.
E-commerce is an area where dynamic models of user behavior are
critical in order to provide a better personalization of the interaction between a customer and an e-commerce business. Collaborative recommendation is now a standard tool for a growing number of e-commerce
sites. The talk reviews some problems in this area and proposes novel
methods to marry analytics with adaptve ways to convey information
to a decision-maker in e-commerce.
HA-42
Thursday, 8:30-10:00 - Room 215
Business Intelligence, Knowledge
Management & Decision Systems
Stream: Decision Support Systems
Invited session
Chair: Fatima Dargam
Chair: Ana Paula Costa
HA-41
Thursday, 8:30-10:00 - Room 216
Stochastic/Robust Routing and Inventory
Routing
Stream: Stochastic Models for Service Operations
Invited session
Chair: Luca Bertazzi
1 - Dynamic Orienteering in Textbook Sales
Jeffrey Ohlmann, Shu Zhang, Barrett Thomas
We consider a stochastic orienteering problem on a network of queues
motivated by the textbook industry. A salesperson visits professors
during office hours to promote textbooks. At each epoch, the salesperson must decide whether to stay in the queue at the professor’s office
or to leave for another professor’s office. The salesperson’s objective is
to meet with professors in order to maximize expected sales resulting
from the visits. We focus on developing a rollout approach to obtain
dynamic routing policies to maximize the total expected sales.
2 - Benders Decomposition for Production Routing Under Demand Uncertainty
Jean-François Cordeau, Yossiri Adulyasak, Raf Jans
We consider the stochastic production routing problem with demand
uncertainty in two-stage and multi-stage settings. The decisions in
the first stage include production setups and customer visit schedules,
while the production and delivery quantities are determined in the subsequent stages. We have developed a solution algorithm based on Benders decomposition for the two-stage problem and we explain how this
approach can be extended to the multi-stage case. We also show how
solving the two-stage problem in a rolling horizon framework can provide good solutions to the multi-stage problem.
3 - Optimal and Heuristic Robust Policies for the Inventory Routing Problem with Outsourced Transportation
Demetrio Laganà, Luca Bertazzi, Adamo Bosco
We study the Stochastic Inventory Routing Problem with Outsourced
Transportation from the robust optimization point of view. First, we
design an exact dynamic programming algorithm for the proposed
problem, and we compare the optimal policy minimizing the total expected cost with the minimax optimal policy arising with the robust
version of the problem. The comparison is performed on the worst
case. Second, we propose an approximated dynamic programming
algorithm for the robust Stochastic Inventory Routing Problem with
Outsourced Transportation.
1 - Assessing a Firm’s Patent Litigation Propensity and
the Effectiveness of its Defense Strategy: Decision
Support Models
Ilan Vertinsky, Steven Minns, Steven Minns
Despite a dramatic recent increase in patent litigation and its growing
importance as a competitive tool, there is a paucity of research in this
area. Using insights from network theory and economics, we develop
and test econometric models to assess the patent litigation propensity
of firms and the effectiveness of their defensive strategies. We utilize
a unique data set (1995-2006) compiled from multiple sources: patent
data from NBER, financial data from Compustat, litigation data from
LexMachina’s IPLC and alliance data from Thomson’s SDC Platinum.
2 - The Theory of Search Applied to Business Strategy
Haemin Aziz, Allan Payne
This paper presents a viewpoint of a business strategy based on the Operations Research technique known as the Theory of Search. The first
part gives a brief description of the previous work in business strategy
whilst the second section enumerates Theory of Search and its techniques. The third portion develops a general business strategy of a user
finding units of a business strategy and draws conclusions about the
characteristics of the user and the strategy. The fourth portions analyses the business strategy documentation process and shows how the
search process is applied.
3 - A System based on a Competency Framework to
Support the Choice of Teaching Activities
Isabelle Linden
In recent years, the business administration department of our university committed in a quality process, that integrates the development of
a competencies framework. The project started with the identification
of 9 key capabilities developed by the students. They do not only guide
every actor of our education process but also support the communication between students, teaching staff and socio-professional partners.
This work describes the system developed to support students’ choice
of optional activities by providing a visual summary of the level of
each capabilities resulting of a choice.
4 - Effective Knowledge Sharing for Intelligent Supply
Chain Decision Support
Shaofeng Liu, E. Irina Neaga, Oluwafemi Oyemomi
Along with the complexity of supply chain networks in current automotive industry, challenges have arisen for decision makers to tackle
knowledge sharing problems, especially when facing the "big data" situation. This paper explores the key factors that the "big data" paradigm
brings to the knowledge sharing community in the automotive industry. A theoretical framework is proposed based on the review of recent
literature with the identification of KPIs that affect the effectiveness of
knowledge sharing using "big data".
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HA-43
IFORS 2014 - Barcelona
HA-43
Thursday, 8:30-10:00 - Room 217
Various Advances on Optimisation in
Health Care
Stream: Optimisation in Health Care
Invited session
Chair: Sanjay Mehrotra
1 - Online Scheduling of Outpatient Procedure Centers
Brian Denton, Bjorn Berg
Outpatient procedure centers (OPCs), are a fast growing trend for providing specialty health care procedures (surgical and non-surgical).
This talk will describe a generalization of the stochastic online bin
packing problem which can be applied to scheduling of OPCs. We
first present a multistage stochastic programming formulation of the
problem. Next, we describe exact methods based on decomposition of
the scenario subproblems a fast approximation for which worst case
performance bounds can be derived. Finally, we present numerical results, based on a real OPC, and discuss future research.
2 - Evaluation of Inventory Technologies for Operating
Rooms
Vera Tilson, Gregory Dobson, Anthony Froix, Abraham
Seidmann
After labor, supply chain costs are the second-largest expense for hospitals, constituting up to 40% of the total operating budget. According to a recent PWC study perioperative services account for approximately 61% of these costs. We examine the issue of supply and inventory planning in operating rooms, and evaluate the benefits of standardization and of using technologies such as bar codes and RFIDs.
3 - On Biological and Geometrical Uncertainties in Radiation Therapy
Omid Nohadani
In radiation therapy, treatment variables can be optimized to attain desired and complex dose distributions. However, uncertainties can degrade otherwise optimal treatments, so much so that they may turn
out clinically unacceptable. We investigate geometric sources of uncertainty and discuss the corresponding robust convex or non-convex
methods. Furthermore, an extension to multi-modal treatments is motivated in conjunction with concurrent chemotherapy. We show that
spatiotemporal and biological changes can be incorporated for individualized treatment.
The ability to manage unexpected disruptions is a key factor of retaining the performance and reliability of supply chains. This work
investigates the disruption management of two different supply chain
types, the automotive and the food supply chain. Interviews with practitioners from both industries have been analysed to identify specific
disruption management strategies. The authors observe that depending
on the different characteristics of the two supply chains, varying strategies are required to manage disruptions efficiently. The work provides
a decision support in handling disruptions.
3 - Qualifying Stock Impact of Supply Chain Disruptions
under Various Market Cycles and Industry Domicile
Kumar Sanjay, Jiangxia Liu, Ashutosh Deshmukh
This research explores the effect of supply chain disruptions on companies and competitors. Stock market reactions are used to assess the
impact of disruptions. We specifically analyze the impact based on
market cycles and industry domicile of affected companies and competitors. We find that the effect of disruptions is dependent on the upward or downward trend in the stock market. Also, American domicile
companies experience greater negative impact from disruptions. Our
study has implications for supply chain managers who make decisions
regarding investments in disruptions mitigation.
4 - Carbon Emissions Reduction and Transfer in Supply Chains under a Cap-and-Trade System with
Emissions-Sensitive Demand
Gendao Li, Yu Xiong
In this paper, through a stylized model, we investigate the carbon emission and transfer in a supply chain comprised by a manufacturer and
a retailer under the cap-and-trade system. Optimal price and carbon
emission reduction are derived under both centralized and decentralized supply chain. The impact of carbon price and consumer environment sensitivity is analyzed. We found that under decentralized
supply chain, the transfer decision depends on the carbon price and
consumers’ emission sensitivity. The results of this paper can shed
light on companies’ carbon emission reduction decision.
HA-45
Thursday, 8:30-10:00 - Room 219
Business Analytics Optimization and Big
Data
Stream: Business Analytics Optimization and Big Data
Invited session
Chair: Matan Abraham
HA-44
Thursday, 8:30-10:00 - Room 218
Managing Risk in Supply Chains I
Stream: Managing Risk in Supply Chains
Invited session
Chair: Kumar Sanjay
1 - Unveiling the Supplier Risks with a Neural Network
Based Supplier Selection Model
Gulcan Petricli, Gül Gökay Emel
Suppliers pose a high level of risk especially for production oriented
businesses as outsourced materials comprise up to 80% of their total
cost. In order to reveal the risk, suppliers of a Tier-1 manufacturing
company will be evaluated by a two-step neural network model. While
the first step eliminates strategically unfitting suppliers, the second step
looks for technical fitness. Outcomes of the evaluation will be compared with real life supplier decisions in order to determine the risk.
2 - Managing Supply Chain Disruptions: A Comparison
of the Automotive and Food Industry
Tobias Gelau, Ole Hansen, Maja Herrmannsdoerfer
168
1 - Large-Scale PCA in Mapreduce Under the Manhattan
Norm
Diego Klabjan
The Manhattan or L1 norm is known to be more robust to outliers than
the standard L2 norm. We developed an iterative algorithm for solving large-scale PCA algorithms that in each iteration solve a weighted
L2 PCA problem. This L2 problem is solved by mapreduce and the
weight updates are also computing by mapreduce.
2 - Big Data Tools and Techniques in the UK Retail Sector
Elly Philpott, Ramakrishnan Ramanathan, Yanqing Duan,
Guangming Cao
This study is based on interviews with 12 leading Big Data
users/consultants in the UK retail sector. These companies included
those operating pure off-line, both online and offline, pure online retailers and also Big Data consultants. We used Technology-OrganisationEnvironment framework to structure the interviews. A number of Big
Data tools and techniques have been mentioned by our interviewees.
They included, among others, tools such as Excel including special
macros and add-ins, SQL, SAP, SAS and SIMALTO. We provide a
more detailed analysis of these tools and techniques in this paper.
IFORS 2014 - Barcelona
3 - Relaxed Normality Assumption in Stochastic DEA for
Efficient Handling of Big Data
Panagiotis Zervopoulos, Ioannis Mitropoulos
The scope of this theoretical work is to present an alternative stochastic Data Envelopment Analysis (DEA) program to enable the measurement of efficiency with minimum computational burden when big data
is present. The new stochastic DEA program assumes that uniform
distribution prevails. When this program is applied to big data, the
elapsed time for measuring efficiency scores is no more than 2% of
the time that conventional stochastic DEA programs require. In addition, there is no significant difference between the efficiency scores
measured by the new and conventional DEA programs.
4 - The Use of Data Envelopment Analysis (DEA) for Profiling Specialist Healthcare Providers in South Africa
Matan Abraham, Shivani Ramjee, Kathryn Dreyer
This research illustrates how DEA can be used to aid the decisionmaking process of specialists allowing them to make the most efficient use of resources when treating patients; and highlights how DEA
improves on provider-profiling techniques currently used by managed
care organisations. Claims data from a prominent South African health
insurance administrator are used to analyse 545 general/paediatric surgeons. The use of claims data as opposed to individually collected
micro-data is considered. A stepwise DEA using sensitivity analysis is
performed to help ensure interpretability of inputs.
HB-02
Thursday, 10:30-12:00
HB-01
Thursday, 10:30-12:00 - Room 118
Robustness in Railway Operations
(RobustRailS)
Stream: Railway and Metro Transportation
Invited session
Chair: Richard Lusby
1 - Adapting Stopping Patterns of Railway Lines to Improve Robustness from the Users’ Perspective
Jens Parbo, Otto Anker Nielsen
This study considers the problem of enhancing railway timetable robustness without adding slack time, hence increasing the travel time.
The approach integrates a transit assignment model to assess how passengers adapt their behaviour whenever operations are changed. First,
the approach considers the existing stopping patterns of the railway
lines. Then, based on the passenger demand we try to optimize the
overall utility by changing the stopping pattern in a way that capacity
utilization is reduced without affecting the frequency of the train lines
nor increasing the passengers’ travel time.
2 - A Branch-and-Price Framework for Rolling Stock Recovery
Jørgen Thorlund Haahr, Richard Lusby, David Pisinger,
Jesper Larsen
Disruptions in railway passenger transportation are regrettably not uncommon and render planned rolling stock schedules infeasible. Finding new schedules in such time-critical situations is not trivial. We
present a Branch-and-Price framework for solving this optimization
problem, which is embedded in a rolling time horizon framework in
order to model uncertainty. Provisional results are presented based
on historical data from the suburban railway operator in Copenhagen
(DSB S-tog).
3 - Integrating Depot Planning when Recovering Rolling
Stock Schedules
Richard Lusby, Jørgen Thorlund Haahr, Jesper Larsen, David
Pisinger
We consider integrating two important operational level planning problems arising in the railway industry. Traditionally, the routing of rolling
stock units and depot planning problems are treated separately; however, the ordering of the units in the depots naturally influences the
possible routes each can be assigned. Here we describe two techniques
for incorporating depot planning in a larger framework for rescheduling rolling stock units under disruption. Preliminary results from DSB
S-tog, a suburban railway network operator in Copenhagen, are presented.
4 - Partitioning a Passenger Rail Network and Rolling
Stock Units to Reduce Disruption Propagation
Simon Bull, Richard Lusby, Jesper Larsen
Disruptions to railway operations can negatively affect passenger’s perception of rail transport, and it is therefore useful to create schedules
that can resist propagating delays. One approach to reducing disruption
propagation is to group rolling stock units and partition the rail network, such that each independent partition is served by one unit group.
We present a rolling stock optimization model for comparing different
network partitions and finding unit group allocations, and present preliminary results from data for the Danish rail network operator (DSB).
HB-02
Thursday, 10:30-12:00 - Room 111
Variants of the Vehicle Routing Problem 1
Stream: Vehicle Routing
Invited session
Chair: Daniele Manerba
169
HB-03
IFORS 2014 - Barcelona
1 - A New Formulation and Approach to Solve the Black
and White Traveling Salesman Problem
Ibrahim Muter
This study proposes a new formulation and a column generation approach for the black and white traveling salesman problem. This problem is an extension of the traveling salesman problem in which the
vertex set is divided into black vertices and white vertices. The number of white vertices visited and the length of the path between two
black vertices are constrained. We modeled the undirected version of
the problem as a traveling salesman problem with an extra constraint
set. A branch-and-price algorithm is designed to find the integral optimal solution for this problem.
2 - Specific Multi-trip Operators for Vehicle Routing
Problems
Yasemin Arda, Yves Crama, Véronique François, Gilbert
Laporte
In vehicle routing problems with multiple trips (VRPM), each vehicle is allowed to perform more than one trip during its working period.
Classical solution techniques for this problem use existing VRP heuristics to create trips, together with bin packing methods aimed at assigning these trips to the available vehicles. In this work, specific local
search operators for the VRPM are proposed. Heuristics using these
operators are compared with classical solution techniques mentioned
above.
3 - Results on the Polyhedron Associated with NodeBalanced Vehicle Routing Problems
Antonio Martinez Sykora, Tolga Bektas, Luís Gouveia, Juan
José Salazar González
This talk will present some results on the polyhedron associated with
the unit-demand vehicle routing problem where, along with the usual
capacity limitations, a lower bound is imposed on the number of customers visited on each route. The results concern to the dimension of
the polyhedron and some facet-defining inequalities.
4 - A Column Generation Approach for the Multi-Vehicle
Travelling Purchaser Problem with Pairwise Incompatibility Constraints
Daniele Manerba, Michel Gendreau, Renata Mansini
Recently, a Multi-Vehicle Travelling Purchaser Problem variant, characterized by the presence of pairwise incompatibility constraints (PIC)
between products, has been introduced. PICs yield the impossibility
of loading two incompatible products on the same vehicle. We propose a branch-and-price approach, based on a set-partitioning formulation. Two different procedures are introduced to solve the pricing
problem, namely a labeling algorithm solving a resource-constrained
Elementary Shortest Path Problem on an expanded graph, and a tailored branch-and-cut. Preliminary tests seem very promising.
HB-03
Thursday, 10:30-12:00 - Room 001
Network Location
Stream: Location
Invited session
Chair: Maria Albareda Sambola
1 - Degree Dependent Tree Location
Alfredo Marín
Spanning trees on graphs usually aim to optimize an objective which
depends on the edges weights. But there are still some problems in the
field where the goal is to identify spanning trees with a given structure, usually depending on the degrees of the nodes. For some of these
problems we present Integer Programming formulations, heuristic approaches and branch-and-cut algorithms providing good computational
results.
170
2 - A Path Location Model with Equality Aspects
Maria Barbati, Giuseppe Bruno
A path location problem consists in locating a path that enables the
transfer of flows from given origin-destination pairs. The topic can
have several applications within transportation and logistics contexts.
We propose a multi-objective model in which balancing or equality aspects, i.e., measures of the distribution of distances of users from the
path, are considered. The model can be used when there is the need
to balance risks or benefits among all the potential users. The application of the proposed model shows its ability to find solutions with
significant level of equality.
3 - The p-Median Facility Location Problem with Uncertainty on the Costs
Sergio García Quiles, Laureano Fernando Escudero
The p-median problem is one of the most classical problems in Discrete Location and consists on choosing p locations and assigning the
other locations to these p medians so that total allocation cost be minimum. Here we study how to solve this problem when the costs are
uncertain: a radius based formulation is developed to model the minimization of the expected cost over a set of scenarios at the same time
that a set of first order stochastic dominance constraints are required to
reduce the risk on the cost due to non-wanted scenarios. A computational study is provided.
4 - The Probabilisitic p-Center Problem
Maria Albareda Sambola, Antonio Manuel Rodriguez-Chia
When locating emergency facilities, the aim is often to ensure that the
best possible coverage is assured to all customers. Among the basic
facility location models built upon this idea, we find the p-center problem which seeks the set of p facilities minimizing the longest distance
between a customer and its closest facility. We extend this model to
the case where it is uncertain which potential customers will require
being served. In this situation, the probabilistic p-center problem aims
at minimizing the expected maximum distance between a request and
the set of facilities.
HB-04
Thursday, 10:30-12:00 - Room 119
Network Traffic Modeling II
Stream: Traffic Flow Theory and Traffic Control
Invited session
Chair: Jaume Barceló
Chair: Nicolas Chiabaut
1 - A Mesoscopic Simulation based Dynamic Traffic Assignment Model
Ma Paz Linares, Carlos Carmona, Jaume Barceló, Oriol Serch
In this work we develop a dynamic traffic assignment model based on
the dynamic user equilibrium by solving a variational inequalities formulation under a preventive approach. An iterative solution algorithm,
which is a modification of the Method of Successive Averages, considers the time and a variable traffic demand on each path of the network within the flow propagation and assignment processes. The dynamics of the reassigned flows at each iteration is simulated by a new
mesoscopic multiclass multilane model accounting for lane changes
and traffic control at signalized intersections.
2 - Scale Selection in Multi-Scale Traffic Flow Modelling
Mahtab Joueiai, Hans van Lint, Serge Hoogendoorn
Traffic is a highly complex system in a sense that it is made up of multiple interconnected elements. Since the behaviour of a complex system
at different scales is related, our descriptions of traffic flow phenomena should also include these relationships. Multi-scale modelling is
an adaptive strategy to reproduce and explain all traffic phenomena
that are observable at different scales. In this paper we will analyse
the concept of scale separation that is basis of multi-scale modelling.
Furthermore, complexity of the phenomena will be quantified and use
to select appropriate modelling scale.
IFORS 2014 - Barcelona
3 - An Integrated Traffic Modelling for Ramp Metering
with Dynamic Speed Limit Strategies
Josep Maria Torne, Francesc Soriguera, Nikolas Geroliminis
A new integrated strategy, i.e., rampmetering together with dynamic
speed limits (DSL), is proposed to reduce the capacity drop occurrence
in the vicinity of an on-ramp. It is tested with a cell transmission model
extension which incorporates the ability to reproduce DSL strategies
together with capacity drop phenomenon.
4 - Methodology for Measuring Performance of High Occupancy Vehicle Lanes
Ali Haghani, Masoud Hamedi, Yanru Zhang
Making more efficient use of existing system through HOV lanes is a
cost-effective solution to improve mobility. Effective management of
such facilities calls for continuous and reliable monitoring of their performance. This research focuses on developing an evaluation framework that combines traffic data from several sources to estimate key
HOV indicators. Motivated by advancements in travel time measurement technologies, a pattern recognition algorithm for separating travel
time on HOV and regular lanes collected by Bluetooth sensors is developed.
HB-05
Thursday, 10:30-12:00 - Room 002
Stowage Planning
Stream: Port Operations
Invited session
Chair: Dario Pacino
1 - The Terminal Management Perspective on the Ship
Stowage Planning Problem
M. Flavia Monaco, Marcello Sammarra, Gregorio Sorrentino
The Ship Stowage Planning Problem, i.e. determining the stowage position of containers in a containership, is usually faced by the shipping
line to optimize vessel related objectives. Here we discuss the problem
from the point of view of the terminal manager which aims to minimize the cost of the loading process. We refer to the Gioia Tauro port
which adopts a DTS configuration. In this context, the operative costs
are related to yard-to-quay transport of containers and possible yardshifts. We propose a Binary Model, a heuristic algorithm, and discuss
the numerical results on real instances.
2 - Port Call Duration Optimisation through Quay Crane
Parameter Constrained Containership Stowage Planning
Tommi Muona, Evrim Ursavas, Iris F.A. Vis
Container terminals face an increasing pressure to shorten the port calls
of containerships. As a result, investments must be made and planning
has to be optimised. This research provides an approach to evaluate the
effects of deploying a new type of quay cranes, capable of serving adjacent ship bays, to handle ultra-large containerships. The evaluation
is based on the terminals’ and the shipping line’s perspectives by considering port calls per port and for the whole multi-port service. Port
call durations are defined by the stowage plans limited by the number
and type of quay cranes.
3 - Heuristic Algorithms for Solving the Slot Planning
Problem
Francisco Parreño, Dario Pacino, Ramon Alvarez-Valdes
In the Slot Planning Problem, for each location of the container ship we
are given a list of containers to be loaded, and the problem is to assign
each container to a feasible position, satisfying the specific packing
constraints associated to the ship locations and to the different types
of containers involved. We have developed a GRASP algorithm in
which the constructive randomized phase packs as many containers as
possible and the improvement phase tries several moves in order to
minimize the number of containers left out. The algorithm has been
tested on a set of real-world instances.
HB-06
4 - Stowage Plans with Hazardous Containers
Anna Sciomachen, Daniela Ambrosino
We analyze the impact of hazardous containers on sea transport and
stowage plans. Starting from recent results on the well-known Master
Bay Plan Problem, we plan the shipping of containers’ lots via liner
service. We present a MILP model in which rules derived from the International Maritime Dangerous Good Code are considered. A heuristic method aimed at optimizing the available space on each ship and
minimizing the total shipping costs is also given. Stowage plans with
and without hazardous containers derived from data of maritime terminals in the port of Genoa are presented and compared.
HB-06
Thursday, 10:30-12:00 - Room 211
Learning and Games in Networks
Stream: Social and Economic Networks
Invited session
Chair: Victor Preciado
Chair: Ozan Candogan
Chair: Kostas Bimpikis
1 - Competing in Networks
Kostas Bimpikis
This paper examines a game-theoretic model of competition between
firms, which can target their marketing budgets to individuals embedded in a social network. We provide a sharp characterization of the
optimal targeted strategies and highlight their dependence on the social network structure. Furthermore, we identify network structures
for which the returns to targeting are maximized, and we provide conditions under which it is optimal for the firms to asymmetrically target
a subset of the individuals. Finally, we provide a lower bound on the
extent of asymmetry in these asymmetric equilibria.
2 - Global Games on Networks with Noisy Information
Sharing
Behrouz Touri, Jeff Shamma
Global games are games with imperfect information where each player
takes a noisy observation of an underlying state of the world and subsequently chooses to take a binary action. In this paper, we consider a
setup where the private signals are shared through a noisy channel. We
show that under a general condition on the noisy channel the threshold
policy surviving the iterated elimination of the dominated strategies
is unique by arguing that iterated elimination of dominated strategies
induces a contraction mapping on the space of thresholds.
3 - Modeling Media Content Production and Consumption among Users and Platforms in a Digital Social
Network
Patrik Wikström
This paper presents the results from an exploratory modeling study
of production and consumption of media content in online social networks. The agent-based model captures the social interaction and innovative behavior of both content producing organizations and individuals and is able to generate a number of observed real-world phenomena
such as the dynamics of illegal/legal content distribution; the transformation of the creative industries from product-based to service-based
economies; and the motivational drivers behind amateur creativity.
4 - Balancing Load via Small Coalitions in Selfish Ring
Routing Game
Xudong Hu, Xujin Chen
This talk concerns the asymmetric atomic selfish routing game for load
balancing in ring networks. It has been known that the classical Nash
equilibrium may cause large loss of efficiency in terms of maximum
link loads. In this paper we extend the classical Nash equilibrium to
a general one which allows coordination within any coalition of up
to k selfish players on the condition that every player of the coalition
benefits from the coordination. Our study shows that the network performance, in terms of maximum load, benefits significantly from coordination of small-sized coalition.
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HB-07
IFORS 2014 - Barcelona
HB-07
Thursday, 10:30-12:00 - Room 003
Dynamical Models in Sustainable
Development III
Stream: Dynamical Models in Sustainable Development
Invited session
Chair: Katrin Seddig
1 - Optimal Harvest with Different Fishing Fleets for Obtaining a Total Allowable Catch Quota of the Oriental
South Pacific Jack Mackerel Fishery
Victor M. Albornoz, Cristian Canales
A methodology proposed for obtaining an optimal harvesting policy of
the oriental south pacific jack mackerel fishery is described as a planning tool in the exploitation of this resource with four different fishing
fleets. More precisely, a nonlinear optimization model that maximizes
the biomass yield is formulated. The model is based on an age structure population dynamic model and considers the fishing selectivity of
each fleet and conditions that ensure the sustainability of the studied
renewable resource. The main aspects of the methodology, the results
and conclusions are presented.
2 - An Agent-based Simulation Approach for Scheduling
the Charging Process of Electric Vehicles in Fleets
Katrin Seddig, Patrick Jochem, Wolf Fichtner
In the field of energy economics there are various approaches for modeling. This paper applies an agent-based simulation for analyzing
charging and load shift potentials of fleets of electric vehicles. Hereby
the construction of the model with the interaction and behavior of different agents is considered. This paper gives a brief systematization
of agent-based simulations in the context of energy economics with
a special focus on fleets of electric vehicles and corresponding issues
like scheduling of charging processes, availability of electricity or grid
restrictions.
storage, as well as resource procurement. To facilitate IS, collaborative planning models are developed that consider waste supply and demand. The goal of the collaboration is to include IS in tactical planning
and to maximize waste utilization.
3 - Two-Stage Stochastic Modeling of New Dairy Production Technologies in a Supply Chain Context
Bryndís Stefánsdóttir, Martin Grunow
The evaluation of new and more sustainable production technologies requires integrated decision making to account for the resulting
changes in the supply chain. A two-stage stochastic MILP model
which integrates the technical design and selection of new dairy production technologies with the relevant supply chain decisions is introduced. The aim is to improve the efficiency of the whole supply chain,
accounting for food specific characteristics and demand uncertainty.
The applicability of the methodology is shown for a dairy company in
Germany.
4 - Resource Efficiency in Food Supply Chains
Aleksander Banasik, Argyris Kanellopoulos, G.D.H. (Frits)
Claassen, Jacqueline Bloemhof, Jack van der Vorst
This research focuses on improving resource efficiency & effectiveness
of food supply chain such that raw materials and resources are used to
their full potential. We take the mushroom supply chain as an illustrative example and demonstrate the complexity for improving resource
efficiency as it involves conflicting economic and environmental objectives and uncertainty. We propose a Multi Objective Optimization
model to support managerial decisions and improve sustainability of
the mushroom supply chain in the Netherlands. Trade-offs between
economic and environmental indicators are calculated.
HB-09
Thursday, 10:30-12:00 - Room 121
Models for Electricity Production and
Distribution
HB-08
Stream: Technical and Financial Aspects of Energy
Problems
Invited session
Sustainable Supply Chains
Chair: Paolo Pisciella
Stream: Energy Economics, Environmental Management and Multicriteria Decision Making
Contributed session
1 - Pumped-Storage Hydropower Optimization: Effects
of Several Reservoirs and of Ancillary Services
Martin Densing
Thursday, 10:30-12:00 - Room 120
Chair: Jacqueline Bloemhof
1 - Planning and Scheduling of Multiproduct Multistage
Semicontinuous Production with Perishability and
Waste Considerations: Dairy Supply Chain
Çağrı SEL, Bilge Bilgen, Jacqueline Bloemhof, Jack van der
Vorst
The Dairy industry is a significant component of many economies, and
is a major industry in the most developed and developing economies of
the world. Effective planning and scheduling of Dairy Supply Chains
has attracted more interest due to increasing awareness on freshness
and environmental concerns such as production loses and waste. In
this study, we introduce a mixed integer linear programming model for
multiproduct multistage semicontinuous planning and scheduling of
yoghurt production accounting perishability and waste considerations.
2 - Collaborative Tactical Planning to Facilitate Industrial Symbiosis
Gábor Herczeg, Renzo Akkerman
Resource efficiency is a key aspect in sustainable supply chain management. To improve resource efficiency in industrial symbiosis (IS),
one company’s production waste substitutes virgin resources in another
company’s production process. To optimize economic benefits for both
parties, tactical planning of operations need to include waste treatment,
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The economic environment for hydropower in Europe has changed in
recent years: With the advent of more wind and solar generation, the
spread between peak and off-peak prices is decreasing, such that the
dispatch of pumped-storage hydropower needs to be carefully chosen
to be profitable. We consider a dual-scale medium-term stochastic programming model for hydropower dispatch using the occupation times
of the electricity price. We model interconnected reservoirs, and we
evaluate profits of ancillary services. In terms of mean-risk optimization we consider hedging against inflow variations.
2 - A Mixed-Integer Program for the Optimised Capacity
and Dispatch Planning of Residential Cogeneration
Systems
Erik Merkel, Russell McKenna, Wolf Fichtner
Research is lacking in considering important constraints for the costminimal capacity and dispatch of residential combined heat and power
(CHP) systems, like non-linear economies of scale. A mixed-integer
program is presented that determines the optimal capacity and dispatch
of a CHP unit and thermal storage through piecewise linear approximation. Based on data from a field trial in the UK it takes into account important technical and economic aspects previously neglected. Results
indicate that total annual costs can be significantly reduced compared
to a reference case of a CHP-only system.
IFORS 2014 - Barcelona
3 - Multicycle Optimization of VVER-Type Reactors
Roman Cada
In the talk we describe the problem of optimization of fuel reloading patterns for nuclear reactors. We discuss the influence of different
fresh fuel types on length and quality of loadings obtained. We present
a computational method based on a combination of several approaches,
mainly based on topological structure and nonlinear optimization with
a combination of some local search methods guided by topological
properties. The methods are incorporated in a new optimization code
Enyo. We compare VVER440 and VVER1000 reactor types regarding
optimization process and criterions to be met.
4 - Transmission Lines Switching in Electric Power Networks by Means of Nonlinear Stochastic Programming
Francesco Piu, Alois Pichler, Asgeir Tomasgard, Maria Teresa
Vespucci
Switching off selected transmission lines of an electricity network can
lead to savings in the total production costs. This fact is gaining increasing interest since new transmission lines are required to access
power production places not exploited in the past (e.g., off-shore wind
parks). This offers the opportunity to redesign the power network and
to incorporate new switching possibilities. The problem is to identify the transmission lines with the highest savings potential. We employ stochastic programming to face the problem and we study how to
achieve a tractable problem size.
HB-11
4 - Assessing University Research Output from Different
Perspectives
Emmanuel Thanassoulis, Dimitris Despotis,
Dimitrios-Georgios Sotiros, Yannis Smirlis, Giannis
Karagiannis
Most assessments in the literature of academic research output have
been at an academic unit level. We compare individual academic staff
members both within academic units and across academic units from
a variety of perspectives. One perspective is that of the duration of
the academic in an academic unit. A second perspective is that of the
salary cost of the academic to the academic unit. We contrast the findings from the alternative perspectives both within and across academic
units and derive information that would be of value both to the individual and the home department.
HB-11
Thursday, 10:30-12:00 - Room 113
Combinatorial Optimization
Stream: Combinatorial Optimization
Invited session
HB-10
Thursday, 10:30-12:00 - Room 122
DEA Theory II
Stream: Theoretical Developments in DEA
Invited session
Chair: Emmanuel Thanassoulis
1 - A Probabilistic Efficiency Analysis using Stochastic
DEA and Bayesian Techniques
Panagiotis Mitropoulos, Michael Talias, Ioannis Mitropoulos
Stochastic DEA can deal effectively with noise in the efficiency measurement but unfortunately formal statistical inference on efficiency
measures is not possible. We use a Bayesian perspective to improve
result robustness by increasing parameter accuracy and reducing the effect of outlying observations. This model incorporates the uncertainty
in DEA by means of a probabilistic-analysis approach. Moreover, it is
known that Stochastic DEA in their initial settings require panel data.
This paper addresses this limitation with a combined stochastic DEABayesian model in cross sectional data.
2 - A Learning Ladder Towards Efficiency: Proposing an
Application of Social Network Analysis in Data Envelopment Analysis
Abaghan Ghahraman, Diego Prior
Stepwise efficiency improvement facilitates the process of inefficiency
removal. Based on the knowledge-based view of efficiency, a networkbased approach is proposed to find the optimal stepwise benchmarking
paths toward the efficiency frontier. The approach treats the Data Envelopment Analysis system as a network of teaching and learning firms
and calculates the overall shortest paths taking into account both input
endowment similarity and efficiency gap covered in each step. For an
empirical example, the method is applied to a dataset of Canadian bank
branches.
3 - On Productive Efficiency and Total Factor Productivity Change of China’s Listed Food Companies Based on the DEA Method and 2008-2012 Panel Data
QIU Hong, Zhu Nan, Dan Yang
This paper applies Data Envelopment Analysis (DEA) to measure the
productive efficiency and total factor productivity change of China’s
listed food companies, based on 2008-2012 panel data. Meanwhile,
the study also finds that the New Hope Company is both in the largest
production scale and highest production efficiency in 2011 and 2012
by using the super-efficiency evaluation.
Chair: Monique Guignard-Spielberg
1 - A Model for Forest Harvesting and Road Network Design under Uncertainty in Wood Demand and Prices
Antonio Alonso-Ayuso, Laureano Fernando Escudero,
Monique Guignard-Spielberg, Andrés Weintraub, Martin
Quinteros
We consider a problem of forest planning along a time horizon. Basic decisions concern the areas to harvest in each period, the amount
of timber to produce to satisfy the demand of the different products
(sawmills low and high quality and pulp plants). Additionally, a road
network must be designed for access and storage of timber. The model
considers that there exists uncertainty in the demand and price of the
products. This uncertainty is represented via a set of scenarios. An
MIP Stochastic model is used for representing the problem. Some preliminary computational experience is reported.
2 - A Branch&Price Approach for the Vehicle Routing
Problem with Intermediate Replenishment Facilities
Lucas Létocart, Paolo Gianessi, Alberto Ceselli, Roberto
Wolfler-Calvo
Vehicle Routing Problem with Intermediate Replenishment Facilities
is defined on a graph where the node set consists of a depot n clients
and p replenishment facilities. The aim is to find the least cost set of
routes that visit each client exactly once with a fixed capacity vehicle
based at the depot. Vehicles can recharge at facilities so as to perform not one but a sequence of routes called a rotation. We propose
a Branch&Price algorithm where the pricing is an elementary shortest
path problem with resource constraints. Tests have been conducted on
medium-sized benchmark instances.
3 - Satisfaction Guaranteed
Sophie Toulouse, Jean-François Culus, Frederic Roupin
A large variety of combinatorial optimization problems fall into the
framework of Boolean Constraint Satisfaction Problems (CSPs). We
here focus on CPSs where the constraints are of arity at most k and the
goal is to satisfy as many constraints as possible (kCSPs). Since kCSPs
are NP-hard in the general case, we address the question of their differential approximability: What kCSPs are approximable within some
constant factor? What predicates are the hardest? For 2CSPs, what
graph structures enable to beat solutions obtained by means of SDP
relaxation?
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HB-12
IFORS 2014 - Barcelona
4 - Improving Crossdock Efficiency Through Improved
Door Assignment
Monique Guignard-Spielberg, Peter Hahn, Heng Zhang
1 - Renewal Theory Methods to Compute Stationary Inventory Control Strategy Parameters (for Lot-sizing)
Alexander Mandel
We consider an actual crossdock where trucks to be unloaded are available at the start of the day, and assigning incoming and outgoing trucks
to doors is currently done manually every day. Instead we propose to
consolidate the goods for that day by destination and determine the location of these staging areas and of the corresponding doors, as well
as that of inbound trucks, so as to minimize, by an NLIP heuristic,
the total labor required to empty incoming trucks, move goods across
the dock and load the outbound trucks, while ensuring that goods are
shipped within twenty four hours.
As is known to compute stationary inventory control strategy parameters (for lot-sizing) the renewal theory methods can be used. In this
presentation, under corresponding model, original minimal average
multi-step costs criteria are replaced by one-step minimal costs criteria
where the stationary inventory level distribution substitutes the stationary demand distribution. The point is that the stationary inventory level
distribution is realized only when time is rather big but stationary control strategies are applicable only in case when the number of reverse
time steps tends to infinity.
HB-12
Thursday, 10:30-12:00 - Room 004
Decentralized Multi-Project Scheduling
Stream: Project Management and Scheduling
Invited session
Chair: Andreas Fink
Chair: Jörg Homberger
1 - Decentralized Multi-Project Scheduling: Review and
Classification
Andreas Fink, Jörg Homberger
The problem is characterized in that individual decision makers pursue
individual goals. This may involve decision makers that control individual projects and/or global resources. A coordination mechanism
must resolve conflicts due to interdependencies between the projects,
which may result from temporal and resource-oriented constraints. After providing a more detailed description of such kinds of problems and
the resulting peculiarities of decentralized decision making, a classification of respective problem types is provided, which leads to related
requirements for solution procedures.
2 - An Extension of the Resource Constrained MultiProject Scheduling Problem with Financial Constraints
Adolfo Lopez-Paredes
Most of the project program and portfolio scheduling problems can be
modeled by means of the Finance-based Resource Constrained MultiProject Scheduling Problem (FRCMPSP). Within this approach, we introduce the concept of Financial Baseline (FB) curve, as the evolution
of firm cumulative financial resources over time. This financial dynamic restriction is particularly useful for managing internal projects
in project based organizations, where projects can only be financed
with firm internal financial resources and project priority is mainly dependent on corporate strategic constraints.
3 - Benchmark Instances and Solutions for the Decentralized Multi-Project Scheduling Problem
Jörg Homberger, Andreas Fink
Benchmark instances and solutions for the decentralized multi-project
scheduling problem are described. The considered multi-project
scheduling problem takes different kinds of decision makers (project
agents and resource agents), as well as private information of the decision makers (objective functions and precedence relations of activities)
into account. Solutions, calculated by a new automated negotiation
approach, are also presented. In order to compare alternative solution
approaches a web-based evaluation system is introduced.
HB-13
Thursday, 10:30-12:00 - Room 123
Process Planning and Task Scheduling
under Uncertainties
Stream: Scheduling
Invited session
Chair: Alexandre Dolgui
Chair: Olga Battaïa
174
2 - The Impact of Deadline Rush on Tardiness Across
Three Material Flow Policies
Kenneth Doerr, David Nembhard
We explore some of the consequences of Deadline Rush to the on-time
performance of material-flow policies. Deadline Rush is a term used
to describe the behavioral response to a deadline, and in particular the
hyperbolic increase in work rate as a deadline approaches. We examine how Deadline Rush impacts the probability of on-time completion of a quota under three material-flow policies: paced-synchronous,
paced-asynchronous, or unpaced. We show that individual differences
in deadline reactivity matter when determining the relative efficiency
of these three policies.
3 - Production Planning in Dairy Industry: An Industrial
Case Study
Bilge Bilgen
This paper addresses the production planning problem of several products in a multi-stage production system stimulated by a particular case
study in the dairy industry. The model incorporates several distinguishing characteristics of dairy production, such as multi-stage bulk production, shelf life requirements, intermediate storage, setups, resource
speeds, minimum and maximum lot sizes, conservation of flow among
various tanks, and demand satisfaction. The objective is to maximize
the total profit to determine the quantity of intermediate and end products processed on various resources.
4 - Optimal Design of Assembly Lines with Flexible
Workers
Olga Battaïa, Xavier Delorme, Alexandre Dolgui, Johannes
Hagemann, Sergey Kovalev, Sergey Malyutin
This presentation will describe an application of the optimisation module of the Advanced Platform for Manufacturing Engineering and
Product Lifecycle Management (amePLM). It deals with the assignment of flexible workers in mixed assembly lines. We prove that the
problem is NP-hard in the strong sense, develop an integer linear programming formulation to solve it, and propose conventional and randomized heuristics.
HB-14
Thursday, 10:30-12:00 - Room 124
Advances in Nonlinear Optimization:
Theory and Applications II
Stream: Nonlinear Programming
Invited session
Chair: Tunjo Perić
Chair: Florian Potra
1 - Vendor Selection and Supply Quotas Determination
by using Multi-Objective Fractional Programming
and Game Theory
Tunjo Perić, Zoran Babic, Sead Resic
In this paper a new methodology for vendor selection and supply quotas determination is proposed. This work deals with a concrete problem of flour purchase by a company that manufactures bakery products.
The problem is solved by the model that combines revised weighting
method for determining the objective function coefficients, and multiple objective fractional programming and coopeartive game theory
techniques for vendor selection and supply quotas determination.
IFORS 2014 - Barcelona
2 - Methods for special structured quadratic constrained quadratic programmings
Cong Sun, Yaxiang Yuan
Consider a kind of quadratic constrained quadratic programmings
(QCQP) which come from wireless communications. The problems
have nonconvex objective functions while the constraints have only
positive definite second-order terms. By approximating the problem
as a series of trust region subproblems, we achieve a feasible solution of QCQP. This point acts as the starting point of the nonconvex
Sequential Quadratic Programming (SQP) method, to achieve a stationary point of the QCQP problem. Such methods allow us to solve
these QCQP problems with low complexity and achieve considerable
solutions.
3 - Trajectory-based Method for Nonlinear Constrained
Optimization
Terry-leigh Oliphant, Montaz Ali
The trajectory-based method for solving constrained nonlinear programming problems is proposed. The augmented Lagrangian problem reformulation is used to convert the constrained problem into an
equivalent unconstrained problem and a new scheme for updating the
penalty parameter is discussed.
4 - Direct Search Based on Probabilistic Descent
Zaikun Zhang, Serge Gratton, Clément Royer, Luis Nunes
Vicente
Direct search methods are a class of derivative-free algorithms based
on evaluating the objective function along polling directions. It is
typical to assume that the directions form a positive spanning set, so
that at least one of them is descent. We study a more general framework where the directions are only required to be probabilistic descent,
meaning that with a certain probability at least one of them is descent.
This framework enjoys almost-sure global convergence and a global
rate of 1 over the squareroot of k for the gradient norm with overwhelmingly high probability.
HB-16
3 - Revenue Management with Ancillary Services
John Wilson, Fredrik Odegaard
Motivated by the growing prevalence for airlines to charge for checked
baggage, we consider the pricing of ancillary products. We assume
there are two types of customers: those that only demand a primary
item and will not consume the ancillary service and those that demand
a primary item provided they also receive the ancillary service. The objective is to determine optimal prices both primary and ancillary products and derive structural properties for when it is optimal not to charge
separately for ancillary services.
4 - Bundle Pricing of Ancillary Services with Dependent
Valuations
Fredrik Odegaard, Mihai Banciu
This paper introduces a novel approach to bundle pricing of products or
services when consumers’ valuations exhibit dependence. We model
the joint density of valuations using copula theory and provide analytical derivations for the prices under different bundling strategies.
We also provide sharp bounds for the profit function regardless of the
dependence functions and analyze how the typical assumption of independence impacts the seller’s profits. Specifically, we find that the
relative gap in profitability, which we call the "price of independence",
can be arbitrarily bad.
HB-16
Thursday, 10:30-12:00 - Room 127
Topic Modeling and Information Retrieval
with Applications
Stream: Intelligent Optimization in Machine Learning
and Data Analysis
Invited session
Chair: Anton Khritankov
HB-15
Thursday, 10:30-12:00 - Room 125
Contemporary Issues in Revenue
Management
Stream: Revenue Management II
Invited session
Chair: Fredrik Odegaard
1 - Exponential Approximations for Network Revenue
Management
Christiane Barz, Dan Adelman, Canan Uckun
We consider a new approximation architecture for the network revenue
management problem using exponential functions to express concavity. We address a number of technical challenges in fitting parameters
and demonstrate numerical performance compared against other approximations.
1 - Finding Scientific Topics and Similarity Search
Anton Khritankov
Finding relevant scientific results is a common problem for researchers. It usually requires a researcher to know exactly what to look
for, which might not be the case when research starts. We propose a
feasible solution to this problem based on similarity search using topic
models. In this report, we present a software system we built for a
major library where it is used to search a collection of over 800 thousand full-text Ph.D. theses and other documents. We demonstrate the
system and topic search on several examples.
2 - Topic Profiles - Applications of Topic Models
Caslav Bozic
Topic Models are statistical language models based on LDA. Instead of
assigning only one ’language’ to the document, they use a distribution
across ’topics’ which are in turn defined as distributions over words.
This corresponds with the intuitive notion of a document containing a
mixture of distinct topics, which can appear in different combinations
and proportions. The presented results of method’s novel applications
include creation of ’Topic Profiles’ for scholarly authors by analyzing texts of their publications, and using the profiles for quantitative
matching with funding opportunities.
2 - Dynamic Pricing with Strategic Consumers and Social Learning
Tatsiana Levina, Yuri Levin, Mikhail Nediak, Jue Wang
3 - Thematic Classification for EURO/IFORS Conference
Using Expert Model
Arsentii Kuzmin, Alexander Aduenko, Vadim Strijov
We present a dynamic pricing model for a monopolist offering a
durable product to multiple segments of strategic consumers. Consumers use social learning to determine the true quality of the product
in order to make their purchase decision. The network structure is captured by weighting the impact of the consumers’ reviews of the product
with their level of influence in the social network. The firm’s objective
is to maximize the expected profits. We study the structure of the optimal pricing policy of the monopolist in relation to consumer preference
for quality and network parameters.
The decision support system predicts the areas, streams and sessions
for the abstracts of a major conference. Abstract collections from the
previous EURO/IFORS (2010, 2012, 2013) conferences and their expert thematic models are considered. The terminological dictionary of
the conference and the global thematic model of these collections are
constructed. A similarity function between two abstracts is proposed.
The non-metric hierarchical clustering algorithm which considers a
constructed global thematic model is used to construct the thematic
model of a new conference without an expert model.
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IFORS 2014 - Barcelona
HB-17
4 - Constrained Independent Semantic Analysis
Takashi Onoda
Many clustering methods have been proposed due to the difference of
the rule to generate a cluster. The clustering is unsupervised learning, so in many cases, an initial discovered clusters by a clustering
method do not coincide with users’ desired clusters. So many clustering methods are extended to deal with users’ constraints. Recently,
Independence Semantic Analysis (ISA) have been proposed. ISA is
different from Latent Semantic Analysis (LSA). In this paper, we propose a method of constrained ISA. We show experimental results for
some benchmark datasets using the proposed method.
Thursday, 10:30-12:00 - Room 112
Behavioral Aspects in Multiple Criteria
Decision Making
Stream: Multiobjective Optimization - Theory, Methods
and Applications
Invited session
Chair: Pekka Korhonen
1 - Pricing New Services Using Utility Functions
Merja Halme, Outi Somervuori
HB-17
Thursday, 10:30-12:00 - Room 005
Conic Optimization and IPMs
(contributed)
Stream: Interior Point Methods and Conic Optimization
Invited session
Chair: Lino Silva
1 - An Active-Set Method for
Quadratic Programming
Noam Goldberg, Sven Leyffer
HB-18
Conic
Constrained
Choice-based conjoint analysis is used to set prices of new services,
which were available for a trial period in an airport relaxation area.
300 passengers evaluated the services with different prices after getting
familiar with them using a questionnaire. The results allow to assess
optimal prices for the different services and assess the value of different product profiles for the respondents. The study was ordered by
the company managing Finnish airports. Its results will be compared
with a similar study employing incentive-based conjoint analysis in the
same environment.
2 - Emotional-Motivational
Responses
Predicting
Choices: A Neurophysiological Investigation
Outi Somervuori, Niklas Ravaja, Murat Koksalan, Pekka
Korhonen, Jyrki Wallenius
We consider the minimization of a quadratic objective subject to
second-order cone constraints; a formulation that generalizes boundconstrained quadratic programming and which can also be used for
tackling more general variants. We propose a two-phase solution
method: First, a projected gradient method is used to quickly identify the active set of cones. In the second phase a sequential quadratic
programming (SQP) method is applied to rapidly converge given the
subsystem of active cones.
In the study, the participants made win-win and trade-off choices
between three product packages (base package and two new product packages). Also, there were two conditions for the base packager: (a) high emotional attachment and (b) low emotional attachment.
We found out that greater approach motivation and increased arousal
elicited by a previously selected choice option predicted a stronger endowment effect. In addition, high trade-off difficulty was associated
with increased withdrawal motivation (or less approach motivation)
and negatively valenced arousal.
2 - An Adaptive Conic Approximation to Nonconvex
Quadratic Programming Problems
Qingwei Jin, Zhibin Deng, Shu-Cherng Fang, Cheng Lu
3 - Predicting Choices with a Linear Value Function in a
Four-Criteria MCDM Problem
Tommi Pajala, Pekka Korhonen, Jyrki Wallenius
In this work, an adaptive conic reformulation and approximation is proposed for solving nonconvex quadratic programming problems. The
original problem is transformed into a linear conic programming problem based on cones of nonnegative quadratic matrices. Then the linear
conic problem is approximated adaptively by a sequence of subproblems. Each linear conic subproblem in the sequence can be solved
using the semidefinite programming techniques. Several numerical examples are used to illustrate how the algorithm works and the computational results demonstrate the efficiency of the algorithm.
I predicted choices in a four-criteria pairwise MCDM problem with a
linear value function model with the epsilon formulation (Korhonen et
al., 2012). I investigated whether the Cognitive Reflection Test score
is related to the predictive power, but no effects were found. Most subjects were inconsistent with their importance of criteria, questioning
the usefulness of eliciting judgments of importance. The model predicted 81,7 % of choices, outperforming models using equal weights,
weights derived from importance judgments, or a lexicographic strategy across both nonlinear and linear subjects.
3 - Characterizing Q-Linear Transformations for Linear
Complementarity Problems over Symmetric Cones
Julio López, Ruben Lopez, Hector Ramirez
4 - Difficulties in Making Rational and Consistent
Choices
Pekka Korhonen, Niklas Ravaja, Outi Somervuori, Jyrki
Wallenius
In this work, we study the symmetric cone linear complementarity
problem (SCLCP). Specifically, our aim is to characterize the class
of linear transformations for which the SCLCP has always a nonempty
and bounded solution set in terms of larger classes. For this, we introduce a couple of new classes of linear transformations in this SCLCP
context. Then, we study them for concrete particular instances (such
as second-order cone and semidefinite linear complementarity problems) and for some specific examples: Lyapunov, Quadratic, Stein and
Rexalation transformations.
4 - Improving the Preconditioning of Linear System arising in Interior-Point Methods by Updating the Controlled Cholesky Factorization
Lino Silva, Aurelio Oliveira
This work presents an update of the controlled Cholesky factorization.
It employs a hybrid preconditioner wich is build by combining the controlled Cholesky factorization and splitting preconditioner. This study
reveals that the update proposed to the first preconditioner save considerable time in the preconditioning of linear systems arising in interiorpoint methods. It is important because the computational time required
by interior-point methods is often dominated by the linear system solution.
We present the results of an experiment with the aim to study, whether
the choices of subjects are rational and/or consistent. If not, then we
would like to understand “why not”? The choice problems are quite
simple consisting of 2-3 criteria and 3, 4, and 6 alternatives. Our pilot
study revealed that the subjects had difficulties in making rational and
consistent choices. We are in the process of repeating the experiment
with a larger group with an aim to look for plausible explanations to
our findings. The study is based on the use of two sets of criteria:
utilitarian and hedonistic.
HB-19
Thursday, 10:30-12:00 - Room 128
Retail Inventory Management
Stream: Demand and Supply Planning in Consumer
Goods and Retailing
Invited session
Chair: Heinrich Kuhn
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1 - Clickstream Big Data and Dynamic Lot Sizing Models
for Online Retailers
Yeming Gong, Haoxuan Xu
Our research is inspired by a leading online retailer using clickstream
big data to estimate customer demand and then ship items to customers
by a mode of "Delivery Before Order Making" (DBOM) operational
mode. We first use clickstream data to obtain advance demand information in order quantities, lead time, and locations. We then integrate the forecasting with a single-item uncapacitated dynamic lot
sizing problem in a rolling-horizon environment. Using the real clickstream data, we study the cost saving and fast delivery effects.
2 - Dynamic Lot-sizing Models with Advance Demand Information for E-tailers
Haoxuan Xu, Yeming Gong, Chengbin Chu, Jinlong Zhang
Facing time-varying demands, our paper studies the inventory replenishment planning problems for e-tailers able to obtain advance demand
information (ADI). We incorporate ADI to dynamic lot-sizing models
to formulate the problems in three scenarios. 1) Companies act as pureplay e-tailers with customers homogeneous in demand lead time. 2)
Customers are heterogeneous in delivery priorities. 3) E-tailers operate in a bricks-and-clicks structure, where online and offline channels
are either independent or interactive. We apply the methods to several
e-tailers and validate the cost-saving effects.
3 - A Genetic Algorithm to Optimize a Multi-Product
Continuous Review Inventory Model with Deterministic and Stochastic Demand
Ilkay Saracoglu, Seyda Topaloglu
This study aims to develop a multi-item, multi-period (Q, r) inventory policy in order to calculate the optimal order quantity and optimal
reorder point under the constraints of shelf life, budget, storage capacity, and “extra number of products” promotions. Initially, the problem
is formulated as a mixed integer linear programming (MILP) model.
Next, a genetic algorithm (GA) embedded with a local search is proposed as a solution approach for large-scale problems. The results indicate that the proposed approach can generate good solutions within
reasonable time frame.
4 - Flexible Capacity Strategy with Flexibility Degree under Demand Uncertainty
Liu Yang, Chi To Ng
This study focuses on flexible capacity strategy with flexibility degree
under demand uncertainty, which has received little attention in the literature. The flexibility degree could be used to measure a firm’s ability
to hedge against the demand fluctuations through adjusting its production quantity. We find the relationship between the flexibility degree
and the capacity volume, which need to be considered simultaneously
when a firm makes an optimal strategy. We solve the optimal strategy
and identify their conditions.
HB-20
Thursday, 10:30-12:00 - Room 129
Optimizing Generation with Wind and
Hydro
Stream: Stochastic Optimization in Energy
Invited session
Chair: Ali Koc
1 - Wind Hydro Integration in Quebec Interconnection
Ali Koc
Renewable energy integration is receiving increasing attention in the
energy industry. We study daily generation and transmission planning
of a pure hydro-power system with large-scale wind power integration. We propose a two-stage stochastic program that addresses the
wind power intermittency and aims to reduce the operating reserves,
which help to stabilize the hydro network against wind power fluctuations. We use “range of operation” approach to make the two-stage
program operationalizable in the multi-period setting. We present use
cases from Quebec Interconnection.
HB-21
2 - On How to Account for Short-Term Flexibility in a
Medium-Term Optimization of Pumped Hydro Storages: A Multihorizon Stochastic Programming Approach
Hubert Abgottspon, Göran Andersson
The work is about how short-term flexibility influence medium-term
self-scheduling policies for pumped hydro storages. We have compared different approaches based on dynamic programming with varying degree of detailism for intrastage subproblems: peak / offpeak
prices, price duration curves, deterministic and stochastic subproblems. The policies are tested in a Monte Carlo simulation study. The
results suggest that the more complex a power plant structure or market structure (e.g., ancillary services market) is, the more a detailed
consideration of short-term flexibility is beneficial.
3 - Optimal Scenario Set Partitioning for Multistage
Stochastic Programming with the Progressive Hedging Algorithm
Michel Gendreau, Pierre-Luc Carpentier, Fabian Bastin
We propose a new approach to reduce the total running time of the
progressive hedging algorithm for solving multistage stochastic programs defined on scenario trees. Instead of using the conventional
scenario decomposition scheme, we apply a multi-scenario decomposition scheme and partition the scenario set in order to minimize the
number of non-anticipativity constraints on which an augmented Lagrangian relaxation must be applied. The proposed method is tested
on an hydro-electricity generation scheduling problem covering a 52week planning horizon.
HB-21
Thursday, 10:30-12:00 - Room 006
Cutting and Packing 2
Stream: Cutting and Packing
Invited session
Chair: A. Miguel Gomes
1 - Integer Programming Formulations for Approximate
Solution of Circle Packing Problems
Edith Lucero Ozuna Espinosa, Igor Litvinchev
A problem of packing circles is considered. The aim is to maximize
the number of circles packed. Frequently the problem is formulated
as a nonconvex continuous optimization problem. New linear integer programing formulations are proposed based on approximating the
container by a regular grid and considering the nodes of the grid as
potential positions for assigning centers of the circles. Two families of
valid inequalities are proposed. The case of nesting circles inside one
another is also considered. Numerical results are presented to demonstrate the efficiency of the proposed approach.
2 - GPU-accelerated Irregular Nesting Algorithm with
Raster Representation
Andre Sato, Giovanna Ono Koroishi, Thiago Martins, Marcos
Tsuzuki
Cutting and packing problems are of great importance and an efficient
solution can be beneficial in both economical and environmental terms.
This work proposes an algorithm for the irregular strip nesting problem, in which the items are irregular and the container is a rectangular
strip, with an infinite length. A raster variant of an overlap minimization algorithm is conceived. A parallel Euclidean distance transformation implementation is used to obtain the overlap value for each pair of
item in a pre-processing step. The use of a GPU resulted in improved
speed for the packing algorithm.
3 - A Two-Phase Nonlinear Programming Approach for
Nesting Problems with Continuous Rotations
Pedro Rocha, A. Miguel Gomes, Rui Rodrigues, Franklina
Toledo, Marina Andretta
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The nesting problem is a Cutting and Packing problem variant with
irregular pieces that aims to place pieces inside a strip with minimum
length. We propose a 2 phases approach. The first phase starts by placing a set of big pieces favouring the fitting between them, up to a target
value. The second one places the small pieces in the holes between the
big ones while minimizing the layout length. Managing the tradeoff
between the target value, the number of holes and the big/small pieces
division size is the major challenge in this approach. Preliminary experiments have shown promising results.
4 - Upper Bounds for Heuristic Approaches to the Strip
Packing Problem
Torsten Buchwald, Guntram Scheithauer
We present an algorithm for the two-dimensional SPP that improves
the packing of the FFDH heuristic and state theoretical results of this
algorithm. We also present an implementation of the FFDH heuristic
for the three-dimensional case, which is used to construct a new algorithm with absolute performance ratio of at most 5. Based on this algorithm, we prove a general upper bound for the optimal height, which
depends on the continuous lower bound and the maximum height lower
bound, and show that the combination of both lower bounds also has
an absolute worst case performance ratio of at most 5.
HB-22
Thursday, 10:30-12:00 - Room 007
Auctions and Algorithmic Mechanism
Design
Stream: Algorithmic Game Theory
Invited session
Chair: Gagan Goel
1 - Revenue Monotone Auctions for Online Advertising
Gagan Goel
Online advertising is an essential part of the Internet and the main
source of revenue for many web-centric firms. A key component of
online advertising is the auction mechanism which selects and prices
the set of winning ads. This work is inspired by one of the biggest
practical drawbacks of the widely popular VCG auction mechanism. It
is known that VCG lacks a desired property of revenue monotonicity
(RM) - revenue of a mechanism should not go down as the number of
bidders increase. In this work, we design mechanisms that satisfy RM
for two practical scenarios from online advertising.
2 - Mechanism Design for Crowdsourcing
Adish Singla
The recent adoption of crowdsourcing markets in the Internet has
brought increased attention to the scientific questions around the design of such markets. A common theme in these markets is that there
is a requester who has a limited budget and a set of tasks to accomplish
by a pool of online workers. A key to making these markets efficient
is to design proper incentive structures and pricing policies for workers. We will present our mechanisms that trade-off between efficiency
and workers’ incentives, under the realistic market constraints, such as
skill matching and limited budget.
3 - Bidding in Markets with Non-Convex Costs: A Comparison of Market Outcomes Under Different Pricing
Mechanisms
Panagiotis Andrianesis, George Liberopoulos
Truthful bidding in markets with non-convex costs, under marginal
cost pricing, may result in losses for the market participants. To deal
with this highly undesirable property, various pricing schemes have
been proposed that provide side payments and/or higher than marginal
prices. We present several such schemes and explore the market outcomes under competitive bidding for a stylized capacity-constrained
duopoly. We employ a game-theoretic methodology to study the behavior of the two suppliers and compare the equilibrium outcomes under different pricing mechanisms.
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HB-23
Thursday, 10:30-12:00 - Room 008
How Corporations Use Analytics to
Impact the Bottom Line
Stream: Analytics Application and Practice
Invited session
Chair: Rina Schneur
1 - Resource Allocation Analytics for US Hospitals
Don Kleinmuntz
US healthcare organizations are making large investments in Analytics
to cope with the requirement to provide higher quality services at lower
cost. This presentation will describe lessons learned on how to address
this through 18 years implementing optimization-based resource allocation Analytics in hospitals.
2 - Work Center Location and Technician Assignment to
Minimize Total Business Cost
Dave Allen, Roger Tobin
Work of a telecommunications company involves installing, maintaining, and expanding its infrastructure, requiring many employees and
vehicles located at work centers. These serve as a home base for workers, provide a supply chain location for parts, supplies, and tools, provide parking for vehicles, and represent a significant cost of doing business. This paper addresses the problem of determining where work
centers should be located and where to assign techs to provide appropriate service levels at lowest cost. Optimized results show significant
savings compared to current operations.
3 - Forget the Drones: The UPS ORION Project
Ranganath Nuggehalli
UPS delivers more than 16 million packages every day in US alone. To
manage the ever increasing complexity of its delivery operations, UPS
embarked on an ambitious mission in 1999 to streamline and automate
its delivery route planning process. ORION (On-Road Integrated Optimization and Navigation) is the result of this long quest. Considered
to be the largest operations research project in the world, ORION uses
an array of technologies and advanced algorithms, to provide the UPS
drivers with optimized routes. This presentation will focus on the development and deployment of the ORION system.
HB-24
Thursday, 10:30-12:00 - Room 212
Dynamic Mechanism Design
Stream: Dynamic and Repeated Games
Invited session
Chair: Tristan Tomala
1 - Incoming Demand with Private Uncertainty
Daniel Garrett
We study a profit-maximizing monopolist selling a durable good to
buyers who arrive over time and whose values for the good evolve
stochastically. The setting is completely stationary with an infinite
horizon. Contrary to the case with constant values, optimal fullcommitment prices fluctuate over time. We show how the pattern of
optimal prices at a steady state can be understood by considering a stationary dynamic program. Departing from the stationary setting, we
illustrate how changes in the arrival rate of buyers to the market can
affect optimal pricing, providing a novel rationale.
2 - The Delayed-Verication Mechanism for Dynamic Implementation
Olga Gorelkina
This paper introduces a mechanism that virtually implements the socially efficient allocation with sequentially arriving agents, and agents’
prior over future types is more informative than the principal’s prior.
To reveal the agents’ information, the mechanism features a scheme
IFORS 2014 - Barcelona
of betting on future type reports. An agent’s betting reward depends
on how accurately his reported prior predicts the type reports observed
in the following period. In an environment with negative externalities,
this mechanism satisfies ex ante participation constraints and generates
no deficit ex post.
3 - Dynamic Moral Hazard with Persistent States
Suehyun Kwon
This paper studies a principal-agent problem in a partially persistent
environment. The costly unobservable action of the agent produces a
good outcome with some probability corresponding to the state. The
states are unobservable and follow an irreducible Markov chain. The
second-best contract resembles a tenure system: The agent is paid
nothing during a probationary period after which the principal implements the first-best action every period. The second- best contract becomes stationary or has a finite memory after tenure. We provide a
recursive formulation for complete characterization.
4 - Approximate Implementation In Markovian Environments
Tristan Tomala
This paper considers dynamic implementation problems in environments with changing private information (according to Markov processes). A social choice function is approximatively implementable
if it is correctly implemented an arbitrary large number of times with
arbitrary high probability in all (communication) equilibria. We show
that if a social choice function is strictly efficient in the set of social
choice functions that satisfy an undetectability condition, then it is approximatively implementable. We revisit the classical monopolistic
screening problem and show that the monopolist
HB-25
Thursday, 10:30-12:00 - Room 009
Advanced OR Methods for Data Mining
Chair: Richard Weber
1 - Mixed-Integer Linear Programming Formulations for
Feature Selection and Support Vector Classification
Sebastian Maldonado, Juan Perez, Richard Weber, Martine
Labbé
The performance of classification methods, such as Support Vector
Machine (SVM), depends on the proper choice of the feature set used
to construct the classifier. In this work we propose two different
Mixed-Integer Linear Programming formulations based on extensions
of SVM. These approaches perform feature selection during classifier
construction using optimization models. Experiments on real-world
datasets demonstrate the effectiveness of our approaches, obtaining
classification models that outperform existing techniques using consistently fewer features.
Clustering
We propose to model the interaction between classifiers and adversaries in adversarial classification as a two-player game. We show how
to model the interaction between players and present an adversaryaware online support vector machine (AAO-SVM) which provides
competitive classification results in a real-world environment and reveals important insights into the complex relation among players. In
the particular application we analyze emails in order to identify phishing messages, making necessary text mining techniques for feature
construction.
HB-26
Thursday, 10:30-12:00 - Room 010
Nondifferentiable Optimization: Theory,
Algorithms and Applications II
Stream: Nonsmooth Optimization and Variational Analysis
Invited session
Chair: Welington de Oliveira
1 - Assessing Numerical Performance of some Nonsmooth Optimization Methods in Solving Thermal
Unit-Commitment Problems
Marcelo Cordova, Erlon Finardi, Welington de Oliveira
Optimization problems arising from the energy sector often need to
be decomposed for numerical tractability. In the presence of coupling
constraints, Lagrangian Relaxation is an important tool for decomposing the problem into smaller, and easy-to-solve subproblems. The resulting dual problem, which is convex, but nonsmooth, provides useful information such as a pseudo solution and bounds for the optimal
value. In this work we focus on bundle methods for nonsmooth convex optimization. We assess the performance of several algorithms in
real-life unit commitment problems in the energy sector.
2 - Solving Convex Optimization Problems with Column
Generation and Interior Point Methods
Pedro Munari, Pablo Gonzalez-Brevis, Jacek Gondzio
Stream: Data Mining
Invited session
2 - Semi-Supervised Constrained
Cluster-Dependent Constraints
Cristian Bravo, Richard Weber
HB-26
with
In this work we present a heuristic procedure to perform clustering
subject to constraints for K classes, when the constraints refer to the
cluster themselves, that is, an element must satisfy a set of constraints
given the cluster in which the element is in. These constraints can link
clusters, or can just restrict the space of feasible points that cluster can
permit. The problem, combinatorial in nature, appears when incorporating external knowledge about the structure of the clusters, and is of
use in Business Analytics applications, as will be shown in the presentation.
3 - Advanced Adversarial Classification using Game
Theory and State-of-the-Art Data Mining Approaches
Richard Weber, Nicolas Figueroa, Gaston LHuillier
The column generation technique and the primal-dual interior point algorithm can be suitably combined for solving challenging optimization
problems. Interior point methods provide stability to column generation, typically reducing the number of iterations and improving running
times. In this talk, we describe the theoretical and computational issues
regarding such combination. In addition, we present the results of using this strategy to solve convex optimization problems which arise in
important real-life situations, such as data analysis, decision-making
under uncertainty and networks.
3 - A Parallel Bundle Framework for Asynchronous Subspace Optimization of Nonsmooth Convex Functions
Frank Fischer, Christoph Helmberg
We present an algorithmic framework for optimizing convex functions
by nonsynchronised parallel processes. Each process runs a bundle
method on a problem restricted to a suitable subset of coordinates until
sufficient progress is attained. To ensure convergence, dependencies
between coordinates are automatically detected by analysing aggregate subgradient information. We apply the framework to problems
with different structure: a single convex function, the sum of partially
separable convex functions, and a function obtained by Lagrangian relaxation of packing type constraints.
4 - Non-smooth Optimization Methods for Chance Constrained Programming
Welington de Oliveira, Wim van Ackooij
Chance constrained programming is one of the main approaches for
dealing with uncertainty in optimization problems. This approach is
particularly suitable whenever high uncertainty is involved and reliability is a crucial issue. Contrary to conventional optimization problems, chance constraints are, in general, not given explicitly. They can
be non-differentiable and difficult to be evaluated. In this work we
present bundle methods suitable for solving convex problems of this
class. We give some numerical results on realistic joint chance constrained energy problems.
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HB-27
Thursday, 10:30-12:00 - Room 213
Decision Analysis and Performance
Measurement
Stream: Decision Analysis, Decision Support Systems
Contributed session
Chair: Josep Freixas
1 - Creating New Agreements by Adjusting Evaluation
Dimensions
Tsutomu Mishina, Alejandra Gomez Padilla, Kei Ogiwara
Teams where each member has diverse ideas may have great potential to perform high levels of accomplishments. However, in order to
achieve goals effectively, the team must share an overall understanding
of the common objectives and procedures. This paper shows a method
to reach a consensus through negotiations when different opinions arise
in the process of decision making. We propose a logical procedure to
create a new agreement, first by increasing evaluation items, then gradually decreasing the assessment elements back to the original structure
of the decision making.
2 - Measuring Decision Making Ability
Ceren Akman Biyik, IrfanUllah Shah, Sabri Erdem
Decision making is important in our daily and professional life. It has
an effect especially on productivity or profitability. In this respect the
aim of the study is to prepare a scale to measure decision making ability of individuals. The steps that we follow in our research process are
as follows; we got five expert opinions, we have 15 phd candidates as a
focus group, and idea generation with PhD candidates via workshops,
scale preparation and dimension reduction via factor analysis after data
gathering by pilot study and principal component analysis over target
group as final study.
3 - Two-Stage Superposition Choice Procedures and
their Properties
Sergey Shvydun
30 two-stage superposition choice procedures are studied. The twostage superposition choice procedure is a procedure which sequentially
applies two choice procedures in compliance with superposition principle. The main goal is to define which of them satisfy given normative
conditions. Normative conditions show how a final choice is changed
due to the changes of preferences, a set of feasible alternatives, or a set
of criteria. A theorem is proved showing which normative conditions
are satisfied for two-stage choice procedures under study.
Electricity and steam pose significant challenges in the daily operation of oil refineries due to the fact that they cannot be inventoried
for later use. Therefore, production planning to fulfill the steam and
electricity demand, considering fluctuations in the price of electricity
within a day, is one of the primary objectives. In this work, we present
an industrial scale decision support system for the rational analysis of
operational decisions. We present our MILP modeling approach and
summarize the findings on an industrial case study.
2 - Decomposition Method for Mutiperiod Blending
Scheduling
Irene Lotero, Francisco Trespalacios, Ignacio Grossmann
A decomposition approach to the multiperiod blending problem arising in the petroleum industry is presented. The proposed algorithm
decomposes the MINLP model in two levels: a master problem that is
an MILP relaxation of the original MINLP that provides rigorous upper bounds, and a subproblem, where a subset of discrete variables are
fixed, yielding a reduction in the number of binary variables and bilinear terms. These problems are solved successively until the gap between the upper and lower bounds is closed. We illustrate this method
and its computational results with several examples.
3 - An Efficient Decomposition Strategy for the
Petroleum Operational Planning Under Uncertainty
Tiago Andrade, Fabrício Oliveira, Gabriela Ribas, Silvio
Hamacher
Oil refining is one of the most complex activities in the chemical industry, mostly because of the nonlinear nature of the refining processes
and their several possible configurations. Moreover, uncertainties concerning the input data surround the definition of optimal operational
plans and must, thus, be considered in the decision process. This
work proposes a two-stage stochastic model for the refinery operational planning problem under uncertainty, combined with a decomposition method to efficiently solve this model. Results obtained confirm
the superior performance of the proposed method.
4 - Refinery Operational Planning Under Uncertainty
Silvio Hamacher, Gabriela Ribas, Fabrício Oliveira
This article presents a two-stage nonlinear stochastic model to the refinery planning problem. The scenario tree generation is essential for
good performance of the stochastic model, but there are few accounts
of how to measure the influence of scenario trees on the quality of the
stochastic solution. This study proposes the selection of scenario trees
via quality measures that intends to assess the ability of scenario trees
to approximate the solution of the stochastic model. The results provide advances in the refinery planning process and contributions for
the scenario tree generation.
4 - A Comparative Study of Success and Decisiveness
Josep Freixas, Montserrat Pons
The power of individuals participating in a vote depends on their position in the voting system and their intention to vote. The position of
voters is modeled by the strength they have in the voting system, while
voting intention is modeled by a probability vector. The decisiveness
and success of the voters are the two main aspects to be measured in
such situations. This work presents a study on the similarities and differences of these two main concepts, e.g., situations in which they are
ordinally equivalent are determined.
HB-30
Thursday, 10:30-12:00 - Room 012
Teaching OR/MS 1
Stream: Teaching OR/MS
Invited session
Chair: Vladimir Deineko
HB-29
Thursday, 10:30-12:00 - Room 011
Planning and Scheduling in
Petrochemicals
Stream: OR in Petrochemicals and Mining
Invited session
Chair: Silvio Hamacher
1 - Production Planning and Scheduling in Cogeneration Systems in Refineries
Ertürk Açar, Metin Turkay
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1 - OR/MS Tools for Teaching/Learning
Bottom-Up Energy Modelling
Denis Lavigne
Integrated
This presentation offers you an overview of a new energy modelling
course that I created and taught at the École Polytechnique de Montréal
during the fall semester of 2013. I will share the experience I gained
from teaching it to graduate students and propose a basic course outline
that could be useful for whom wishes to choose a similar approach for
teaching bottom-up energy modelling using simple yet powerful software such as LEAP and OSeMOSYS. The students had the opportunity
to work hands on a project that enlightened greatly their understanding
of what energy modelling is.
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2 - Educating Military Operations Research Practitioners
Ron Fricker, Robert Dell
The 2013 Smith Prize was awarded to the Naval Postgraduate School
(NPS) Operations Research (OR) department for “effective and innovative preparation of students to be good practitioners of operations
research, management science or analytics.” In the spirit of the prize,
this talk shares details about our degree program. NPS began offering a degree in OR in 1951, making it the first OR degree in the United
States. The program is closely linked to its sponsor, the US Department
of Defense, in a unique relationship that ensures NPS OR is focused
on important military problems.
3 - MS Excel-based Software Tools for Decision Problems with Multiple Criteria
Josef Jablonsky
Multiple criteria decision making (MCDM) and data envelopment
analysis models, even they solve different problem classes, belong to
the most often used modeling techniques at all. Their effective teaching depends on availability of appropriate software tools. The paper presents two freeware software systems - DEA Excel Solver and
Sanna. DEA Excel Solver covers basic DEA models, and uses the
internal MS Excel optimization solver. Sanna is a simple MS Excel
based application for multi-criteria evaluation of alternatives using several important MCDM methods.
4 - Using OR to Teach OR whether we Practice what we
Preach
Vladimir Deineko
In this presentation we talk about our experience of developing and using IT tools to enhance the teaching and learning process. We will talk
about an allocation of students to equitable teaching groups, the OR
techniques behind the allocation tool, and the experience of teaching
the students in the groups. In another example we describe a decision
support system for generating test problems for linear programming
assignments and for semi-automatic marking the students’ models and
solutions.
HB-32
3 - Vulnerability Assessment of Spatial Networks: Models and Solutions
Eduardo Álvarez-Miranda, Alfredo Candia-Véjar, Emilio
Carrizosa, Francisco Javier Pérez Galarce
In this paper we present a collection of combinatorial optimization
problems that allow to assess the vulnerability of spatial networks in
the presence of disruptions. The proposed measures of vulnerability
along with the model of failure are suitable in many applications where
the consideration of failures in the transportation system is crucial. By
means of computational results, we show how the proposed methodology allows us to find useful information regarding the capacity of a
network to resist disruptions and under which circumstances the network collapses.
4 - Combined Network Design and Routing Optimization
using Distributed Benders Decomposition
Dimitri Papadimitriou, Bernard Fortz, Enrico Gorgone
The combined network design and distributed routing problem can be
formulated as a large-scale multi-period mixed integer optimization
problem. Its resolution on realistic instances is intractable and unscalable with state-of-the-art solvers which ignore the distributed nature
of routing. We decompose the global optimization problem following
the distributed Benders decomposition method. Using this method,
the optimization problem subdivides into a distributed master problem
solved at each node and subproblems of tractable size involving only
local decisions when computing routing paths.
HB-32
Thursday, 10:30-12:00 - Room 014
Supply Chain Management - Assembly
Lines and Maintainance
Stream: Production Management & Supply Chain
Management
Contributed session
Chair: Ileana Perez
HB-31
Thursday, 10:30-12:00 - Room 013
Survivability and Vulnerability
Stream: Telecommunications and Networks
Invited session
Chair: Eduardo Álvarez-Miranda
1 - Models for Communication Network Design with Survivability Requirements
Remberto Emanuel Delgadillo, Irene Loiseau
A telecommunication network is said survivable if it is able to provide
service after one of its components fails. A p-cycle provides one protection path for a failed span it crosses and also protects spans that have
both end nodes on the cycle but are not on the cycle. P-cycle based networks gather the characteristics of both mesh and ring topologies. The
Spare Capacity Allocation problem requires to protect the traffic of a
network with p-cycles at minimum cost. We propose a new ILP model
that does not require a priori candidate cycle enumeration. Results improved those of previous models.
2 - The Minimum Flow Cost Hamiltonian Cycle Problem.
Camilo Ortiz, Ivan Contreras, Gilbert Laporte
We introduce the Minimum Flow Cost Hamiltonian Cycle Problem
(FCHC). Given a graph and positive flow between pairs of vertices,
FCHC consists of finding a Hamiltonian cycle that minimizes the total
flow cost between pairs of vertices through the shortest path on the cycle. Applications arise naturally in general network design problems
in which a ring topology is sought. We present five MIP formulations
for the FCHC which are theoretically and computationally compared.
We also propose families of valid inequalities and perform some computational experiments to assess their performance.
1 - Calculation of the Troughput Time in Simple Assembly Lines with Learning Effect
Tamás Koltai
During the startup period, learning effect may significantly influence
the operation time of workstations in assembly lines. When learning
effect is present, the operation time of the workstations depends on
the number of times the operations are repeated. The operations, however, are repeated fewer times at the downstream workstations, than at
the upstream workstations. This phenomenon makes the estimation of
the throughput time difficult. An algorithm is presented to calculate
the throughput time of a given production quantity in simple assembly
lines at the presence of learning.
2 - A General Framework for Comparing Conditionbased Maintenance with Age-based Maintenance
Bram de Jonge, Ruud Teunter, Tiedo Tinga
Condition-based maintenance (CBM) is often preferred over age-based
maintenance because of its just-in-time nature. However, the performance of CBM strongly depends on the characteristics of the deterioration process, the cost structure, the setup time required to perform
preventive maintenance, the accuracy of the measured condition information, and the uncertainty in the deterioration level at which failure
occurs. We present a general framework for assessing the benefits of
CBM.
3 - A New Look at the Bowl Phenomenon
Alysson M. Costa, Pedro B. Castellucci
The bowl phenomenon states that assembly lines having central stations with slightly less load than external ones are more productive
than perfectly balanced lines. The topic has been the subject of some
controversy in the literature. We present new simulations that tend
to confirm the existence of the phenomenon. These simulations are
different from previous ones since they: a) consider the indivisibility
of tasks in the load assignment, b) use a large set of new instances
recently proposed in the literature and c) are extended to the case of
heterogeneous workers.
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4 - General Procedure Oriented to Improve a Maintainance Plan Based on PMO and RCM
Ileana Perez, Jose Alberto Rojas Lopez, Lina Marcela
Moncayo Gonzalez, Yasmin Tocoche
This paper presents a general procedure oriented to improve a maintenance plan based on the Methodology of Preventive Maintenance
Optimizing (PMO). It integrates decision making tools of the Reliability Centered Maintenance (RCM) methodology, Industrial Engineering
Tools such as motion and time studies techniques, key performance indicators analysis and continuous improvement models. It also exhibits
design and implementation in a Colombian meat food company.
HB-33
Thursday, 10:30-12:00 - Room 015
Hyperheuristics: Interfaces,
Implementations and Applications
Stream: Hyperheuristics
Invited session
Chair: Shahriar Asta
Chair: Daniel Karapetyan
1 - The Broadening Future of Hyper-heuristic Interfaces
Andrew J. Parkes, Ender Özcan
Hyper-heuristics provide a general-purpose software component to
help reduce the implementation time needed for effective search methods. However, hyper-heuristics studies have generally used a framework with an overly limited communication between the high-level
search control and the low-level domains. We discuss ideas for enriching the interface to allow better search control. We give progress on
converting it into a set of implemented APIs and benchmark problems.
The dual aim is to support both future research in hyper-heuristics, and
also usage in specific problem domains.
2 - Hyperheuristic Applied to Maritime Service Network
Kassem Danach, Wissam Khalil, Shahin Gelareh
Many exact methods proposed to solve variants of service network design problem (SNDP). However, it is known that the successes with
such methods are almost limited even with small size instance with
more real features of real practice. In this article, we are resort to
hyperheuristics to develop methods based on a low level heuristics for
solving instance in liner shipping SNDP. Our problem description takes
into account more aspects of reality (time windows, customers’ priorities, delays, fuel, assets, etc.). Our work is supported by computational
experiments from the real-world cases.
3 - Cretaing Heuristics viA Many Parameters: CHAMP
Shahriar Asta, Ender Özcan, Andrew J. Parkes
Hyper-heuristics are search methodologies which, in contrast to metaheuristics, take the search a level higher to either low level heuristic
selection or heuristic generation. We represent a generation heuristic using a "many parameter" representation stemmed from policy indexing (hence the name Creating Heuristics viA Many Parameters CHAMP). Index policies assign scores to available options leading to a
ranked based decision system. We have performed experiments on the
well-known online bin-packing problem (NP-hard) resulting in powerful policies outperforming well known heuristics.
4 - James: A Modern Java Framework for Optimization
using Local Search Metaheuristics
Herman De Beukelaer, Guy Davenport, Geert De Meyer,
Veerle Fack
A major advantage of metaheuristics is that they are generally applicable to optimization problems from various fields. James is a modern
object-oriented Java framework that exploits this generality by separating metaheuristic implementation from problem specification. A
wide range of generic local search algorithms are provided, which can
easily be applied to any user-defined problem, by plugging in a custom objective and neighbourhood for the corresponding solution type.
Predefined components are included in the framework for common optimization problems, including subset selection.
HB-34
Thursday, 10:30-12:00 - Room 016
Financial Modeling 2
Stream: Decision Making Modeling and Risk Assessment in the Financial Sector
Invited session
Chair: Nelson Hein
1 - ARIMA: A Model for the Time Series Forecast applied
to Sao Paulo Stock Exchange Index
Leonardo Alves de Carvalho, Edson Pamplona, Paulo Rotela
Junior, Fernando Salomon
The study aims to evaluate the performance of the ARIMA model
to predict the time series of Sao Paulo Stock Exchange index. The
research method used was mathematical modeling and followed the
Box-Jenkins methodology. To compare the results with other models
of smoothing we used as a parameter for assessing the MAPE (Mean
Absolute Percentage Error). The results prove that the ’one step ahead’
model used had lower MAPE indicating their better fitness, and it
shows that the ARIMA model can be used for time series of indices
related to the stock exchange.
2 - The Influence of Crude Oil Prices in Emerging and
Developed Capital Markets
André Salles
The purpose of this work is to study the relationship between crude oil
prices and selected stock markets. This work studies the cointegration
and the conditional correlation of crude oil and stock market returns. It
also estimates SUR models to explain each stock market index returns
using first the global stock market index as a regressor and later the
global stock market and crude oil returns as repressors of five emerging markets and five developed markets. The data used in this study
is daily closing quotations in US$ of stock market index of selected
emerging, developed and global stock
3 - Application of Real Options Fuzzy Pay-Off Method:
An Ex-post Multi-criteria Analysis
Luiz F. Autran M. Gomes, Luiz Geraldo Biagioni Martins,
Carlos Bastian-Pinto
The purpose of this paper is to demonstrate the importance and also
to recommend the application of multi-criteria decision aid methods
especially in decisions under uncertainty and changing environments.
By using an actual case presents an ex-post evaluation, applying the
Real Options Fuzzy Pay-Off method, to select the best alternative location of an expansion industrial project and comparing with the decision
taken at that time by the company. It highlights the relevance of scenario analysis and the introduction of qualitative variables in addition
to economic and financial parameters.
4 - Degree of Relationship Between Indicators of Capital Market, the Financial Indicators and the Return
of Shares in Brazilian Companies — A Multi-criteria
Analysis
Nelson Hein, Adriana Kroenke, Itzhak David Simão Kaveski
This study aimed to establish the degree of relationship between the
indicators of the capital market, financial-economic indicators and the
return of share, in the brazilian companies. To make the analysis was
used the Vikor multi-criteria method. Were selected 27 companies belonging to IBrX-50 (Brazil), basing the analysis for the periods 2008 to
2012. It was concluded that, for some companies the analyzed years,
tend to have similarities in efficiency positions in the capital market,
in the traditional economic and financial indicators and the return of
shares.
HB-35
Thursday, 10:30-12:00 - Room 131
Stochastic Modeling
Stream: Stochastic Modeling and Simulation in Engineering, Management and Science
Invited session
Chair: Frank Herrmann
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IFORS 2014 - Barcelona
1 - A Model Based Systems Engineering Framework for
Large Scale Enterprise Design and Management
Craig Lawton
Large scale Enterprises are complex systems containing many highly
interrelated elements that evolve over time with a high degree of uncertainty. Design and management of efficient Enterprises is a significant
challenge for those responsible for Enterprise performance. This paper
will present a Model Based Systems Engineering (MBSE) framework
for Enterprise modeling, design and management. The framework integrates both traditional systems architectures (SysML, DODAF) as
well as simulation (Systems Dynamics). A case study with application
to a military enterprise will demonstrate utility.
2 - An Agent-based Simulation of the Diffusion of Intelligent Technical Systems in Future Markets
Christian Stummer, Lars Lüpke, Sabrina Backs
In the German Leading-Edge Cluster (Spitzencluster) "it’s OWL" 174
companies and research institutions cooperate in 45 projects in furthering the development of (successful) intelligent technical systems. Our
contribution lies in setting up a tool that can support decision makers in
finding the "best" combination for the attributes of their systems with
respect to the envisioned market segments. To this end, we resort to
scenarios for the respective markets ("ITS 2020") and run simulations
for various alternatives. In our talk, we discuss remaining challenges
and provide some initial results.
3 - A Bayesian Negotiation Model for Reliability and
Price
María Jesús Rufo Bazaga, Jacinto Martín, Carlos Javier Pérez
Sánchez
This paper presents a Bayesian sequential negotiation model between
a manufacturer and a consumer on two issues (price and lifetime of a
product). A mediator’s presence is not required. The decision problem
is solved under the manufacturer viewpoint. A class of parametric lifetime distributions that belong to the exponential family is considered.
Thus, a unified framework addressing the main points in the work is
shown. In particular, a simulation-based approach is proposed. Finally, an application is presented to show that this technique can be
easily applied in practice.
4 - Simulated Determination and Usage of a Clearing
Function for Leadtime Estimation
Frank Herrmann
In production systems, nonlinear relationships occur between lead
times of orders and the system workload. Relative recently a clearing function (CF) is introduced to describe these nonlinear relationships. A new simulation based determination of CF is presented. Its
quality is analysed. In addition it is applied to two major problems in
operative production planning and control. A CF based order release
outperforms an inventory based order release.
HB-37
2 - Simulating Temporal Dynamics of Provisioning
Ecosystem Services from Agricultural and AgroForest Land Uses
Marcos Jiménez-Martínez, Christine Fürst
A key issue in land use planning is how to maintain the functioning
of ecosystem processes to ensure the provision of natural resources.
Through this research, land use models accounting for management
techniques will be embedded to spatially assess their impact on the
temporal fluctuations of biomass related products (food, fodder, energy, raw industrial materials) provision on a district/watershed scale in
Upper East Ghana. This project contributes to the development of the
software platform GISCAME, supporting the assessment of regional
land use change scenarios.
3 - How to make Mechanistic Forest Simulations Fast
and Easy for End-users: A Belgian Study using Regional Bayesian Parameterization
Gaby Deckmyn
Mechanistic forest models can simulate responses to changes in climate and management, but their use is hampered by the high number of input parameters and the resulting large uncertainties. We
used Bayesian parameterization to acquire robust parameter values that
were used to simulate growth and yield of for different species, soil
types and climate regions of Flanders, under different managements
and climate scenario’s using the ANAFORE forest model. The results
(> 600.000 simulations) were used to create a database that allows fast
analyses on climate, soil and management effects.
4 - Carbon Footprint and the Management of Metrological Laboratories
Teresa Pino, José L. Pino, Ma Teresa Cáceres
Metrology is important for scientific research,industry and our everyday lives.This activity belongs to the service sector, and not out among
the most studied activity due to contamination. However, calibrations
require laboratories that keep the controlled and constant environmental conditions throughout the year and this implies high energy consumption. In this work we show how by associating carbon emission
parameters with various decision variables, traditional models can be
modified to support decision-making for minimize operational cost and
carbon footprint in metrological laboratories.
HB-37
Thursday, 10:30-12:00 - Room 017
Multi-Actor Multi-Criteria Analysis
Stream: Multiobjective Optimization
Invited session
HB-36
Thursday, 10:30-12:00 - Room 132
Sustainable Forest Management
Stream: OR in Agriculture, Forestry and Fisheries
Invited session
Chair: Gaby Deckmyn
1 - Multi-criteria Analysis Techniques to Prioritize Criteria and Indicators for Sustainable Management of
Mediterranean Forests
Pablo Valls-Donderis, María C. Vallés, Francisco Galiana
A set of criteria and indicators for sustainable forest management under Mediterranean conditions applicable at the forest management unit
scale have been identified. Aspects have been defined for each criterion, they refer to the specific topics that it covers. In order to verify
and prioritize the criteria, aspects and indicators, two processes have
been carried out: a participation process to rank criteria and aspects
according to participants’ preferences for a specific forest; and a questionnaire with experts to rank the indicators through pairwise comparisons.
Chair: Cathy Macharis
1 - Involving Stakeholders in Transport Decision Making
using Planning Workshops and MCDA
Michael Bruhn Barfod, Marie Pryn
Developments regarding decision making in the transport sector has
revealed an increasing need for involving stakeholders in the decision
support process in order to capture all aspects of the often complex decision problems. This paper proposes the use of planning workshops
and multi-criteria decision analysis to gather stakeholders and decision
makers with the purpose of improving the final decision making by including a collaborative planning approach. An outline is made for how
the planning workshop can be used for real decision support at different organizational levels in the process.
2 - Should we Weight the Stakeholders in Multi-actor
Multi-criteria Analysis (MAMCA)? Problem Description and Solutions
Klaas De Brucker, Cathy Macharis
Recently MCA has been geared towards addressing stakeholder interests. For instance, in MAMCA criteria are clustered so that they contribute to particular stakeholder objectives. Here, the problem arises
of aggregating the different points of view. We discuss several approaches to aggregate stakeholder points of view. Most of these use
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weights to obtain the multi-actor solution. A distinction is made between intra- and inter-stakeholder weights. Also the possibility of not
using inter-stakeholder weights is discussed. The different approaches
are illustrated using a real-life case study.
3 - Application of MCDA Methods and Stochastic Dominance Rules in the Entry Mode Selection Process in
International Expansion
Dorota Górecka, Małgorzata Szałucka
When the company decides to go on foreign markets, it must take a
number of strategic decisions, e.g., select a proper entry mode. Various entry modes differ greatly in resource commitment, degree of risk,
level of control or profit potential. Hence, it is essential to conduct
an analysis of their advantages and disadvantages from the point of
view of various internal and external factors and taking into account
the opinion of different participants of the decision-making process.
The aim of the paper is to carry out the simulation of the entry mode
selection, using MCDA methods and SD rules.
4 - Evaluation of City Distribution Projects:
Stakeholder-based Approach
Lauriane Milan, Cathy Macharis, Sara Verlinde
A
Organizing freight transport in a sustainable way is one of the challenges faced by urban areas. Most of the measures that have been
tested suffer from a lack of systematic evaluation and long term adoptions often fail, because not all stakeholders were taken into account
(Macharis & Melo, 2010). The new City Distribution—Multi Actor Multi Criteria Analysis (CD-MAMCA) assessment framework incorporates the city distribution actors and their objectives as the primary focus complemented with a Multi-Criteria Decision Analysis
performed with the GDSS-PROMETHEE GAIA.
HB-38
Thursday, 10:30-12:00 - Room 214
Soft OR / Systems and Multimethodology
1
Stream: Soft OR / Systems and Multimethodology
Invited session
Chair: Leroy White
1 - Refining a Generic Constitutive Definition of PSMs
through the use of Quantitative Data
Mike Yearworth, Leroy White
Is it possible that PSMs are actually in widespread use? We do not
know for sure because use of PSMs could be under reported. What
seems more likely is that use of PSMs is not recognised or described
as such, and is also under reported. In previous work we have addressed the problem of how to identify non-codified PSM use. Here
we discuss how our method might be implemented at scale in order to
answer the question. We also discuss the benefit of obtaining a large
data set of PSM use in terms of refining our generic constitutive definition of PSMs through the use of quantitative data.
2 - Building a Better Model: A Novel Approach for Mapping Organizational and Functional Structure
Damian Flynn
Complex organisations often rely on informal social group networks
which can contradict the organisation’s more formal hierarchy chart.
The ability to perform is shaped by both formal and informal arrangements. This paper proposes a novel methodology for developing a
model to represent the true functional and organisational structure
within an organisation using a combination of social network analysis and group model building techniques. The methodology described
represents a useful way to capture the current organisational state and
its value is discussed through a case study.
3 - Promoting More Efficient Energy Behaviours: From a
Soft OR Structuring Approach to Contextualised Understanding
Marta Lopes, Carlos Henggeler Antunes, Maria São João
Breda, Paulo Peixoto, Nelson Martins
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Energy behaviours are recognised as increasingly important in the context of energy efficiency in the residential sector. More effective behaviour change interventions are required as a support for effective
policies promoting energy efficiency. A multimethodology approach
is used for structuring the influence of energy behaviours on energy
consumption and contextualised understanding generated through a
real-world intervention is exploited. Electricity monitoring data and
questionnaires are analysed to identify the most relevant variables and
validate the conceptual model developed.
HB-39
Thursday, 10:30-12:00 - Room 018
Advances on TSP and Related Subjects
Stream: Discrete and Global Optimization
Invited session
Chair: Gerald Gamrath
Chair: Vladimir Ejov
1 - SLH Algorithm for Solving Hamiltonian Cycles Problem
Vladimir Ejov
We describe a deterministic, polynomial complexity algorithm for
solving the Hamiltonian Cycle Problem (HCP) in undirected graphs,
called Snakes and Ladders Heuristic (SLH). We observed that the algorithm is successful even in cases where Hamiltonian cycles in the
graph are extremely rare. The use of a stopping criterion ensures the
heuristic terminates in polynomial time if no improvement is made.
Comparison of SLH performance to the state of the art TSP algorithms
Concorde and LKH (adapted to solving HCP) is provided. Practical
on-line demonstration of SLH will accompany the presentation
2 - Investigating the Robustness of the TSP Routes
through the Recognition of Special Structured Matrices
Azmin Azliza Aziz
In this study, the robustness of the TSP routes is investigated by recognizing the special combinatorial structures of Kalmanson and Burkard
matrices. A recognition algorithm was developed and executed on a
number of randomly generated instances. The procedures produce four
lower bounds which provide guarantees on the quality of the solutions.
Computational experiments showed that the proposed LP-based procedure performs consistently well and provides the best lower bounds
to the TSP solutions. This is supported by small average deviation
between the TSP tour lengths and the lower bounds.
3 - Conjecture about the Extremal Graphs for the
Geometric-Arithmetic Index with Given Minimum Degree
Ljiljana Pavlovic, Tomica Divnic, Milica Milivojevic
The geometric-arithmetic index GA of a graph is defined as sum of
weights of all edges of graph. The weight of one edge is quotient
of the geometric and arithmetic mean of degrees of its end vertices.
Let G(k,n) be the set of connected simple n-vertex graphs with minimum vertex degree k. We give a conjecture about structure of extremal
graphs of this index for n-vertex graphs with given minimum degree.
We find for k greater or equal to q(n-1), where q is approximately
0.0874, extremal graphs in G(k,n) for which geometric-arithmetic index attains its minimum value or we give lower bound.
HB-40
Thursday, 10:30-12:00 - Room 019
Innovations in Meta-Analytics IV
Stream: Meta-Analytics: A Marriage of Metaheuristics
and Analytics
Invited session
Chair: Helena Ramalhinho Lourenco
IFORS 2014 - Barcelona
1 - Meta-Analytics for Market Basket Analysis
Antonio Ladrón de Guevara, Helena Ramalhinho Lourenco,
Pedro Martins
HB-42
2 - Integrating Resilience in Stochastic ProductionDistribution Network Design Models
Walid Klibi, Atidel B. Hadj-Alouane
The Market Basket Analysis consists in mathematical modeling and
algorithm techniques to analyze the customer purchasing behavior and
helps design of marketing strategies to increase sales. The main objective of this work is to study the application of Clique Models in the
Market Basket Analysis. We propose the use of Metaheuristics to perform this Analytics study and evaluate the implications of the results
in Marketing Strategies of a retailer company. We focus on the marketing analytics perspective, not on the mathematical and algorithm. The
results presented are based on a real database.
This research studies alternative resilience seeking formulations to the
production-distribution network design problem. The mathematical
model builds on stochastic programing to consider uncertainty into
a set of scenarios considering potential demand surges and disrupted
production-distribution capacities. To foster resiliency, the concepts
of chaining and multiple sourcing are inspected. This gives rise to a
two-stage stochastic location-allocation model with multiple products
and capacitated production features, and where the decisions include
technology and facilities mission selection.
2 - A Regret Model Applied to the Maximum Coverage
Location Problem with Queue Discipline
Francisco Silva, Pedro Nunes, Helena Ramalhinho Lourenco
3 - A Stochastic Programming Approach to Design a Robust Supply Flow by Considering the Response Time
Characteristics
Alireza Ebrahim Nejad, Onur Kuzgunkaya
The article considers a special type of the Maximum Coverage
Location problem where a queue discipline is considered at each
server/location. This problem considers the location of services that do
not only depend on the time between the demand points to the server,
but includes also the service waiting time in a queue. Examples of such
services are medical systems, police operations, and other public services. We propose a metaheuristics based on GRASP that incorporates
the p-minmax Regret method to evaluate the heuristic solutions with
respect to to its robustness within different scenarios.
3 - Advances in Solving Max 3-SAT Problems
Peter Greistorfer, Cornelia Rainer, Haibo Wang, Gary
Kochenberger
We investigate a penalty function approach for the Max 3-SAT problem. This work extends a metaheuristic multi-start algorithm, which is
based on adaptive memory projection. We present different randomized choice rules and advanced weighing schedules for the base greedy
heuristic and introduce the first Max 3-SAT results made with LocalSolver, a new generation hybrid optimizer. Additionally, we use an LPformulation and CPLEX to evaluate performance and results’ quality
of our different heuristic solution procedures, based on a DIMACS test
set of problem instances.
4 - A New Tabu Search Approach for solving the
Quadratic Assignment Problem
Haibo Wang, Zhipeng Lu, Fred Glover, Gary Kochenberger
The quadratic assignment problem, despite years of research, remains
one of the most challenging combinatorial problems. A variety of papers in recent years have reported encouraging progress and yet largescale instances still pose great difficulty for even the best crafted metaheuristic methods. Recently one of the best known approaches for
solving the unconstrained quadratic binary program was modified to
accommodate assignments constraints. In this paper we give a brief
overview of this Tabu Search method and report on its application to
challenging quadratic assignment test problems
HB-41
Thursday, 10:30-12:00 - Room 216
Stochastic Models for the Design of
Supply Chain Networks
Stream: Stochastic Models for Service Operations
Invited session
Chair: Walid Klibi
1 - Service-Oriented Carriers Selection in Transportation Auctions under Uncertainty
Monia Rekik, Walid Klibi
We consider the problem of strategic carriers selection encountered by
shippers that decide to outsource their transportation activities to external carriers on a long-term basis. The trading mechanism corresponds
to a combinatorial reverse auction where the shipper is the auctioneer
and competing carriers are the bidders. We propose a stochastic model
for determining winning bids under the assumption that both shipment
volumes and carriers quality of service are not known with certainty.
The contingent sourcing is a cost-efficient strategy to deal with disruptions. The response time is crucial since only a fraction of required
capacity might be available within this period. The objective of this
paper is to determine optimal safety stock level and response speed of
back-up supplier to build a robust supply chain. In order to incorporate the randomness associated with response time and disruptions, we
present a robust optimization model. Through a sensitivity analysis
we identify the optimal supply chain configuration with respect to the
level of decision maker risk aversion.
4 - Studying of Networks’ Dynamics by means of Probabilistic Modeling
Mark Korenblit, Ilya Levin, Vadim Talis
The work deals with a study of networks that grow according to a number of regularities. Specifically, each new vertex is connected to at
most one existing vertex; any connection is realized with the same
probability; the probability of connecting a new vertex to any existing vertex depends on the position of its degree in the sorted list of
vertex degrees. We propose a number of models for such networks
called one-max constant-probability models. The provided computer
simulation allows studying the dynamics of the networks’ topologies
by recognizing some previously unknown phenomena.
HB-42
Thursday, 10:30-12:00 - Room 215
Integrated and Simulation-Based DSS
Approaches
Stream: Decision Support Systems
Invited session
Chair: Isabelle Linden
Chair: Shaofeng Liu
1 - An e-Kanban based Decision-Support System for
Semiconductor Ingot Manufacturing
Taho Yang
The present study proposed an e-kanban based decision-support system (DSS) for semiconductor ingot manufacturing which is comprised
of three sub-systems - Lean system, e-Kanban and intelligent decision
support system. This problem is motivated by an industrial-academic
research project which becomes the foundation for the development.
A semiconductor ingot manufacturing case is used for the empirical illustrations. The results are promising, there are foreseeable challenges
which will also be addressed as future research opportunities.
2 - Evaluation of the Application of Agent-based Simulation in Container Terminal Planning
Thiago Brito
The inherent complexity of CTs requires complex methodologies for
DSS building, being able to consider the interrelationships between
its core planning problems. Agent-based simulation (ABS) is a rather
new approach for simulating systems - it is a methodology able to build
analysis and evaluate systems associated to emergent properties deriving from interactions between its elements, and is able to challenge
more complex questions that were not until now addressed by traditional OR. This work proposes to evaluate the application of ABS in
planning the CT operation, benefits and disadvantages.
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3 - Multi-Resolution Analysis (MRA): Integrated Solutions for Today’s Analytical Challenges
John Tindle
4 - Optimal Appointment Schedules in a Hospital Radiology Department
Engin Bayturk, Sila Halulu, Fadime Üney-Yüksektepe
Multi-resolution analysis (MRA) is a general term developed in various centers of excellence regarding modeling, simulation, and analysis. The basic premise is that complex domains of capability should
be analyzed from different perspectives with tailored models and tools
appropriate for each perspective, but with the various segments of the
analysis integrated to provide traceability of cause and effect for combined total impact. MRA produces greater depth of understanding in
less time than traditional monolithic modeling approaches by employing 5 operations research techniques.
There have been growing health problems in recent years. Magnetic
Resonance Imaging (MRI) results are expected for almost each patient to decide their treatment modalities. Therefore, demands of appointments for MRI machines are increasing rapidly. Since MRI machines of the hospitals are limited, they cannot meet the appointments.
For this reason, the patients have to wait for about 6 months. In our
study, we made an optimal schedule of the appointments for one of
the biggest state hospital in Turkey. The results are compared with a
current schedule and the improvements are discussed.
4 - Improved Decision Making by Incorporating Expert
Opinions into Statistical Models
Dries Benoit, Kristof Coussement, Michael Antioco
Interest in the use of company (big) data and statistical methods to
guide decisions has been increasing in recent years. However, the
impact of refining decisions based on statistical analyses by integrating management opinions into the decision-making process has been
under-investigated. This study develops an expert system that formally integrates subjective human expert opinions with objective organizational data. We empirically test our Bayesian expert system on
a customer-satisfaction dataset and contrast it with the frequentist and
human-experts alternatives.
HB-43
Thursday, 10:30-12:00 - Room 217
Scheduling and Optimisation Models
Stream: Optimisation in Health Care
Invited session
Chair: Janny Leung
1 - An Optimization Model for Health Facility Location
Planning Considering Congestion
Camila Metello, Fabrício Oliveira
Although health facility allocation has been a highly discussed theme
in current literature, it is rarely combined with staff sizing, which, in
terms of budget and process times, is a critical variable. We present
an optimization model to plan health facilities logistics that focuses on
process time minimization and considers congestion without compromising its linear structure. The model was applied to plan the mass
vaccination against Influenza in Rio de Janeiro. Results helped generating a list of possible new facilities and a more efficient vaccine
distribution plan.
2 - Comparison of Different Collimator Technologies
Used in IMRT from an Optimization Point of View
Merve Gören, Z. Caner Taşkın
Collimator systems used in Intensity Modulated Radiation Therapy
(IMRT) can form different geometric shapes of apertures depending
on their physical capabilities. We compare the efficiency of using regular, rotating and dual multileaf collimator (MLC) systems under different combinations of consecutiveness, interdigitation and rectangular
constraints and a virtual freeform collimator. We formulate the problem of minimizing beam-on time as a large-scale linear programming
problem. To deal with its dimensionality, we apply column generation
approach.
3 - Appointment Scheduling for the Breast Clinical of
Oporto Oncological Hospital
Alcinda Barreiras
This problem studies a scheduling system for patients with breast cancer. The clinical breast unit of Oporto Oncological Hospital is responsible for the schedule of the diagnosis appointment, treatment decisions appointment and follow-up appointment, as well as imaging,
laboratory and pathological exams required for each patient. The variables for the model are the waiting times and the pre-established intervals between the different phases of the pathway that a cancer patient
has to go through.
186
HB-44
Thursday, 10:30-12:00 - Room 218
Managing Risk in Supply Chains II
Stream: Managing Risk in Supply Chains
Invited session
Chair: Kumar Sanjay
1 - The Impact of Supply Chain Disruptions on Stockholder Wealth in Japan
Jiangxia Liu, Kumar Sanjay, Ashutosh Deshmukh
Past research has shown that disruptions in supply chains result in negative stock market returns. These results are, however, affected by various factors including firm domicile. Moreover, studies relating supply
chain disruptions and stock market impact have been limited to the US
companies. In this research, we study the stock impact of disruptions
on Japanese companies. We find that despite apparent resilience of
Japanese companies, supply chain disruptions cause negative reactions
in Japanese companies. The negative reactions are similar in magnitude to that in the US companies.
2 - A Supply Chain Risk Management Model with Random Demands
Yash Daultani, Ravi Suman, Sushil Kumar, Omkarprasad S
Vaidya, Manoj Tiwari
A decision support framework has been proposed to address the multitiered supply chain risk management problem. The objectives considered are minimization of risks and maximization of profit, whereas the
demand associated with markets is random. A mathematical model is
formulated using variational inequalities. A computational procedure
that exploits the network structure of the problem is proposed and then
applied to several numerical examples to provide managerial insights.
Resultant equilibrium pattern of production outputs, inventory, prices,
and costs are investigated and compared.
3 - Optimal Access Restoration for Disaster Response
with Explicit Consideration of Human Suffering
Felipe Aros-Vera, Jose Holguin-Veras
This paper develops a mathematical optimization model to help disaster responders prioritize access restoration activities. It uses a network
design approach to determine the sequence of links that need to be
open to minimize the impact on the affected population and optimize
the response to the disaster. The impact on people is incorporated using deprivation cost functions (i.e., the economic valuation of human
suffering due to the lack of access to a good or service for a period
of time). This represents a step forward on producing more realistic
mathematical models for disaster management
HB-45
Thursday, 10:30-12:00 - Room 219
Routing Problems
Stream: Hybrid Heuristics
Invited session
Chair: Niaz Wassan
IFORS 2014 - Barcelona
1 - A Hybrid Meta-Heuristic for the Mixed Fleet Vehicle
Routing Problem: A Case of Gas Delivery in the UK
Lina Simeonova
The purpose of this paper is to introduce a real-life version of the
Mixed Fleet Vehicle Routing Problem (MFVRP) based on real data,
collected from the market leader in the UK’s gas delivery sector. An
initial solution is obtained using a guided randomized version of the
Sweep algorithm, amended to fit the nature of the problem. Local
search techniques (including a meta-heuristic) are efficiently used to
improve the quality of the solution. New rich MFVRP datasets are
proposed ranging from 20-200 customers and some interesting results
are reported.
2 - The Vehicle Routing Problem with Divisible Deliveries and Pickups
Gábor Nagy, Niaz Wassan, M. Grazia Speranza, Claudia
Archetti
The VRP with divisible deliveries and pickups is a new reverse logistics model. Each customer may have a pickup and delivery demand
that may be served, if beneficial, in two separate visits. The model is
placed in the context of other problems and formulated as a mixed ILP.
We study the savings that can be achieved by allowing pickup and delivery quantities to be served separately with respect to the case where
they have to be served simultaneously. Both exact and heuristic results
are analysed for a better understanding of the problem structure and an
estimation of the savings achievable.
3 - The Fleet Size and Mix Vehicle Routing Problem with
Backhauls: Formulation and Set Partitioning-based
Heuristics
Niaz Wassan
In this paper we present a new variant of the classical Vehicle Routing Problem — the Fleet Size and Mix Vehicle Routing Problem with
Backhauls (FSMVRPB). An ILP formulation of the FSMVRPB is presented. Optimal solutions for small size instances are produced and
upper and lower bounds are generated for larger ones. In this paper we
also propose a Set Partitioning Problem (SPP) based heuristic. Three
frameworks are developed and tested on a set of new FSMVRPB data
instances which we generated. Computational results are presented
which can be used for future benchmarking.
HC-50
Thursday, 12:15-13:45
HC-50
Thursday, 12:15-13:45 - Plenaries room
Plenary Session R. Blackburn
Stream: Plenary Sessions
Keynote session
Chair: Gerhard-Wilhelm Weber
1 - Operations Research in BASF’s Supply Chain Operations
Robert Blackburn
Over the years, Operations Research has been used extensively to support the chemical industry in configuring and planning their end-to-end
supply networks. The applications deal with a wide range of problems,
ranging from long-term strategic problems related to product portfolio
and warehouse allocation, to mid-term tactical problems such as inventory and transportation optimization and to very short-term operational problems, such as order quantities and production scheduling
problems. Modeling approaches for customized make-to-order product industries differ from those of plain make-to-stock industries. Additionally, as process industry is designed through "many-to-many"
processes, its network dimensionality asks for different solution approaches than problems of a convergent network (automobile industry)
or divergent network (food industry). In this talk we examine the planning and design tasks with regard to industrial examples from BASF,
draw some conclusions about the degree to which different classes of
problems have been solved, and discuss challenges for the future.
4 - A Hybrid Two-level Variable Neighbourhood Search
for Vehicle Routing Problem with Backhauls and Multiple Trips
Naveed Wassan
The VRP with backhauls is one of the well-studied VRP versions in reverse logistics. This problem involves two types of customers, namely
deliveries and pickups with known demands served by a fleet of vehicles operated from a depot. Our VRPB model extension allows for
multiple trips of vehicles in order to achieve cost savings. A hybrid
two-level VNS is implemented; in the second level of the VNS skeleton a VND is used as a local search to manipulate the search efficiently.
Computational results are reported.
187
HD-01
IFORS 2014 - Barcelona
Thursday, 14:00-15:30
HD-01
Thursday, 14:00-15:30 - Room 118
Planning and Operations of Rapid Transit
Systems
Stream: Railway and Metro Transportation
Invited session
Chair: Juan A. Mesa
1 - A Rolling Stock Modelling Approach for Medium Size
RTS Networks
David Canca, Alejandro Zarzo, Eva Barrena
Rolling stock is one of the most difficult phases in the railway planning process and also plays a key role in a cost-efficient operation.
The rolling stock circulation plan includes a set of interrelated subproblems as train composition determination, vehicle and carriage rest
location, vehicle circulation problem and maintenance policies. In this
paper, we propose a general modelling approach to determine the minimum number of vehicles needed to perform the actual schedule, a
cyclic weekly train circulation and the most convenient maintenance
policy for medium size RTS networks.
2 - Building Train Schedules from Frequency Maps
Alejandro Zarzo, David Canca, Eva Barrena
1 - The Open Vehicle Routing Problem with Different Vehicle Types
Refail Kasimbeyli, Melis Alpaslan
In this work, open vehicle routing problems are studied and different
mathematical models considering different cases are presented. First
we consider the problem in which all vehicles that will be used are
exactly given. The second problem considers the case where we have
different number of vehicles for different types and we need to minimize not only the total route costs but also to minimize the number
of used vehicle types. Therefore, a two-objective mathematical model
is developed for this problem and different scalarization methods are
applied to calculate efficient solutions.
2 - Adaptive Local Search and Variable Neighborhood
Search Algorithms for the Heterogeneous Fleet Vehicle Routing Problem with Simultaneous Pickup and
Delivery
Mustafa Avci, Seyda Topaloglu
The Vehicle Routing Problem with Simultaneous Pickup and Delivery
(VRPSPD) has been considered with homogeneous fleet of vehicles so
far. In this study, the VRPSPD is extended by assuming the fleet of vehicles to be heterogeneous. In order to solve the problem, two solution
approaches are developed. The first approach is based on an adaptive
local search method while the second one is based on Variable Neighborhood Search. The performances of the algorithms are compared on
a set of randomly generated problem instances.
3 - Solving of the Open Routing Problems by SOMA
Juraj Pekár, Zuzana Čičková, Ivan Brezina
In the past few years a set of acceleration strategies for managing congestion problems in RTS have attracted increasing interest (e.g., the so
called short-turning and deadheading approaches). Usually, the output
of these models is an optimal frequency plan including new cycles and
deadheaded trips. After this stage, the frequency plan should be finally
converted into a concrete and compatible train schedule. In this paper
we present a general ILP model in order to obtain such schedules for
a given frequency map with the objective of preserving regularity as
much as possible.
The routing problems can be extended to open versions where in contrast to the classic formulation is not required to return the vehicle to
the starting point. That problems are particularly applicable in the case
of rental of vehicles, when financial costs are associated only with the
distribution actually made and it is not relevant whether the vehicle returns to the depot or not. The use of metaheuristics remains a popular
way to solve corresponding problems. We present the solving of open
travelling salesman problems and open vehicle routing problem by self
organizing migrating algorithm.
3 - Optimal Shortest Paths in a Public Transportation
Network from Different Points of View
Francisco A. Ortega Riejos, David Canca, Juan A. Mesa,
Miguel Angel Pozo
4 - A Hybrid Algorithm for a Large Class of Heterogeneous Fleet Vehicle Routing Problem
Puca Huachi Penna, Anand Subramanian, Luiz Satoru Ochi
The k-shortest path (KSP)-problem is a classical problem with many
applications in flow networks and optimization. The problem was initially studied in 1959 by Hoffman and Pavley but the fastest KSP algorithm was developed by Eppstein in 1988. In this work we provide
a review of the shortest path problem algorithms (commonly used as a
starting point for developing the KSPs algorithms) and revise the main
techniques for determining the KSPs. Thirdly, we analyze the suitability of these algorithms to the context of railway transportation from
both user and operator perspectives.
4 - Congestion in Railway Transit Lines: Frequency and
Capacity Setting in Presence of an Alternative Mode
Alicia De-los-Santos, Gilbert Laporte, Juan A. Mesa,
Federico Perea
We focus on the line planning problem taking into account aspects
related to rolling stock and personnel planning. We assume that the
fleet size is limited, that is, the problem we are considering is a capacitated problem and the line network can be congested. The main
novelty in this paper is the consideration of vehicle capacities and service frequencies as variables, as well as the inclusion in the model of a
congestion function measuring the level of in-vehicle crowding. Computational experiments will be presented.
HD-02
Thursday, 14:00-15:30 - Room 111
Variants of the Vehicle Routing Problem 2
Stream: Vehicle Routing
Invited session
Chair: Puca Huachi Penna
188
This paper deals with the a large class of Heterogeneous Fleet Vehicle Routing Problems (HFVRP). To tackle this class of problems we
present a multi-start hybrid heuristic based on the Iterated Local Search
(ILS) metaheuristic that uses a Set Partitioning (SP) formulation to add
memory to the ILS framework. In order to verify the efficiency of the
algorithms, the developed heuristic was used to solve several variants
of the HFVRP, including features like multi-depots, time windows and
backhauls. Extensive computational experiments demonstrate the notable contribution of this approach.
HD-03
Thursday, 14:00-15:30 - Room 001
Applications of Location Analysis
Stream: Location
Invited session
Chair: Francisco Saldanha-da-Gama
1 - The Maximin HAZMAT Routing Problem: Exact and
Heuristic Procedures
Vladimir Marianov, Andres Bronfman, Armin Lüer-Villagra,
Germán Paredes-Belmar
We address the hazardous material routing problem in an urban area.
The population-weighted distance between the route and its closest
vulnerable centre (school, hospital, senior citizens’ residence or the
like) is maximized. Previously studied in a continuous space, the problem is solved here over road network. We present an exact model, in
which the required variables are significantly reduced, as well as an
optimal polynomial time heuristic. Both are tested in a real-world case
study set in the transport network in the city of Santiago, Chile.
IFORS 2014 - Barcelona
2 - An Empirical Comparison of Customer Retail Patronization Models
Burcin Bozkaya, Seda Ugurlu, Vivek Singh, Alex Pentland
Several models in the literature aim at modeling customer retail patronization. One model, originally proposed by Huff, has been widely
used with various extensions. Recently discrete choice models, originally pioneered by McFadden, have spawned an interest for modeling
utility with random error components. We empirically validate the two
models using grocery purchase transaction data from a major consumer
bank. Results show that both models work well with homogenous customer groups and limited number of choice alternatives. We also point
out cases where one model works better over the other.
3 - A Two-Stage Stochastic Transportation Problem with
Fixed Handling Costs and A Priori Selection of the
Distribution Channels
Yolanda Hinojosa, Justo Puerto, Francisco Saldanha-da-Gama
A transportation problem with stochastic demands, fixed handling
costs at the origins and fixed costs associated with the links is addressed. It is assumed that uncertainty is captured via a finite set of
scenarios. The problem is formulated as a two-stage stochastic program. The goal is to minimize the total cost associated with the selected links plus the expected transportation and fixed handling costs.
A prototype problem is presented which is progressively extended to
accommodate capacities at the origins and multiple commodities. The
results of a set of computational tests are reported.
4 - Optimal Location of Battery Stations and its Charger
for Electric Vehicles Based on Japanese Road Networks
Yudai Honma, Shigeki Toriumi
Electric vehicles (EV) have attracted an increasing amount of attention. However, the continuous cruising distance of an EV is limited to
around 160 km, which is insufficient for everyday use. Battery capacity is the limiting factor in long-distance EV travel. In planning the EV
infrastructure, an appropriate number of EV stations and chargers must
be installed. In this study, on the basis of the supporting infrastructure
for widespread EV use, we propose a mathematical model for optimal
location of EV stations and its charger in Japanese road networks.
HD-04
Thursday, 14:00-15:30 - Room 119
Optimal Control of Motorways
Stream: Traffic Flow Theory and Traffic Control
Invited session
Chair: Ioannis Papamichail
Chair: Claudio Roncoli
1 - Optimisation of Multi-Lane Motorways in Presence of
Vehicle Automation and Communication Systems
Claudio Roncoli, Markos Papageorgiou, Ioannis Papamichail
The introduction of Vehicle Automation and Communication Systems
(VACS) is expected to bring along strong changes that call for new control strategies with the purpose of alleviating motorway traffic congestion. In this work, VACS are acting both as sensors (providing information on traffic conditions) and as actuators, permitting the integration of Variable Speed Limits and Lane Changing Control with Ramp
Metering. The problem is formulated as an optimal control problem
based on a first-order model for multi-lane motorways. A case study is
presented on a motorway using real data.
2 - Integrated Control of a Urban Freeway Off-ramp and
Neighboring Intersections
Xianfeng Yang, Yang Lu, Gang-Len Chang
Via an interchange off-ramp, congestion at the downstream intersections of main arterial often cause the queue spillback and then substantially reduce the freeway capacity. Therefore, this study proposes
a two-stage control strategy that accounts for both potential off-ramp
spillback and local congestion. Based on the real-time data, the firststage of signal priority control focuses on providing signal progression
to the off-ramp traffic. Under oversaturated condition, the second-stage
of gating control is activated at upstream of arterial to constrain the entry flows to the interchange area.
HD-05
3 - An Optimal Fleet Allocation of Emergency Response
Teams on Freeway Using a Two-Stage Stochastic
Programming
Hyoshin Park, Ali Haghani
Stochastic programming is used to identify optimal allocations of
emergency response teams on the freeway. Previous studies used the
probability of incidents, considering all incidents equal and ignoring
scenarios in which two incidents occurred within proximal regions and
intervals. In this study, first stage decisions are made before a realization of uncertainty of primary incidents. The recourse in the second
stage includes excessive response to secondary incidents, using multistate mixture model to present distribution of excessive response time
due to the negative impact of an incident.
HD-05
Thursday, 14:00-15:30 - Room 002
Hinterland Transportation
Stream: Port Operations
Invited session
Chair: Claudia Caballini
1 - Petri Net Modelling and Optimization of Container
Terminal using Automated Guided Vehicles
Danko Kezić, Anita Gudelj
We study a modelling and traffic control optimization problem of the
automated guided vehicle (AGV) system in a container terminal. The
authors present a formal mathematical technique to calculate deadlock
prevention control places (supervisor) which must be added to the net.
We are using Hybrid Petri net and P-time MRF1 class of Petri nets. By
changing the parameters of resources, such as the loading time or segment capacity, an attempt was made to determine the conditions under
which the transportation system performs optimally.
2 - Fleet Deployment in RoRo Liner Shipping under Inventory Constraints at Ports
Saurabh Chandra, Kjetil Fagerholt, Marielle Christiansen
We propose an integrated model for fleet deployment in RORO liner
shipping that considers inventory constraints at the served ports in different routes served by the company. We consider time varying demand/production at various ports for cargoes managed by the company.
3 - Truck Carriers Cooperation in Container Transportation: A Heuristic Approach
Claudia Caballini, Simona Sacone, Mahnam Saeednia
Our work proposes a heuristic approach for planning truck trips of multiple carriers cooperating with the purpose to reduce empty trips while
maximize their cost saving. The approach foresees a pre-processing
step in which transportation demand is decomposed to isolate nonoptimized trips, and a second phase where a linear optimization model
allows combining trips of different carriers. Trips values due to customers importance as well as time windows related both to orders due
dates and transportation nodes are considered. Simple instances have
been tested to prove the heuristic efficacy.
4 - Yard Arrangement at the Container Terminal with Irregular Configuration
Etsuko Nishimura
Relatively new marine container terminals often have a rectangular
configuration by making use of reclaimed land to serve large vessels
with deep draft. However, due to geographical reasons some terminals
have an irregular configuration. At the terminal with irregular configuration with RTG operated, the storage capacity depends on the location
and number of aisles used for yard trailers movement. In this study,
we consider the aisle location problem at the container terminal with
polygon configuration. We also consider the container storage problem
under the aisle location obtained.
189
HD-06
IFORS 2014 - Barcelona
HD-06
Thursday, 14:00-15:30 - Room 211
Information Economics and Networks
Stream: Social and Economic Networks
Invited session
Chair: Ali Jadbabaie
1 - Ad Exchanges and the Problem of Disclosing Information
Sofia Ceppi
In the advertisement exchange scenario, publishers ask an exchange
for ads to display to users. To provide each of these ads, the exchange
runs an auction among advertisers who express an interest in displaying their ads. In this scenario, the actors benefit from targeting the
users. However, to achieve an accurate targeting, the exchange should
disclose information about users. This has the side effect of reducing
the competition in the market, and, thus, the revenue of the exchange.
We aim to design a mechanism that uses the information while reducing the revenue loss of the exchange.
2 - Railroads and Economic Growth: A Trade Policy Approach
Fernando Pérez Cervantes
What was the impact of railroads on the output of the United States during the 19th century? I construct a railroad data set to estimate travel
times between every pair of counties for every year between 1840 and
1900. I use these results, together with a Ricardian model of trade
and output data from the 19th century to estimate county gains from
trade using a fixed-point algorithm that I designed. Then, I estimate
counter-factuals. My estimates suggest that if railroads had been suddenly made unavailable in there would have caused a large reduction
in output, contrasting with Fogel (1962).
3 - Optimal Contracting in Networks
Ali Jadbabaie, Alireza Tahbaz-Salehi
We study the optimal contracting strategy of a firm that sells a divisible good to a group of consumers. The consumers are embedded in a
network which captures the positive externality that they receive from
their neighbors’ consumption. The extent of this externality is the
private information of the consumers. We explicitly characterize the
firm’s optimal contract as a function of the underlying network structure.
4 - The Impact of Valuation Heterogeneity and Network
Structure on Equilibrium Prices in Supply Chains
Alper Nakkas, Yi Xu
Supply chains can be very complex and highly asymmetric structures.
The impact of these structures on the surplus sharing between manufacturers and their suppliers is not straightforward. To this end, we
consider a strategic bargaining model in which suppliers negotiate procurement prices. We provide a supply chain network decomposition
algorithm that takes manufacturer valuations into consideration and
show that the equilibrium behavior of the manufacturers and suppliers can be deducted from their behavior in the smaller supply chain
network structures that are determined by the algorithm.
1 - Interval Type-2 fuzzy Linear Programming: An Application to Logistic Networks
Juan Carlos Figueroa-García, German Jairo Hernandez
This paper shows an application of Interval Type-2 fuzzy linear programming to a logistics problem involving fuzzy uncertainty coming
from multiple experts who provide an individual estimate of the demands of the customers. Using linear programming models and previous results (Figueroa 2010, 2012, 2014) we find a solution to the
problem based on the fuzzy linear programming model proposed by
Zimmermann (1979). Some concepts of Interval Type-2 fuzzy linear
programming are introduced, a mathematical model is presented, and
some interpretation aspects regarding the study case are discussed.
2 - Solving Linear Programming Problems Involving Interval Type-2 fuzzy Technical Coefficients
German Hernandez, Juan Carlos Figueroa-García
This paper shows a method for solving linear programming problems
whose technical coefficients are Interval Type-2 fuzzy numbers. Type2 fuzzy numbers deal with linguistic uncertainty coming from the perception of multiple experts about a variable, so its applicability to decision making problems, in this case linear programming, is high. Using
the decomposition theorems for fuzzy sets and the Zadeh’s extension
principle, we present a general method for solving this kind of problems. In addition, an application on a PERT problem is presented, and
some interpretation aspects are explained.
3 - An Application of Fuzzy Logistic Regression
Gultekin Atalik, Sevil Senturk
Fuzzy set theory was proposed by Zadeh in 1965. Many studies have
been done to combine several statistical methods and fuzzy set theories, called fuzzy statistics, such as design of experiment, time series
analysis, probability theory and regression analysis. Fuzzy regression
model was first introduced by Tanaka et al.. This proposed model is
called possibilistic model. Tanaka’s possibilistic model was revised by
Chan et al. in 2007. The aim of this study is to solve fuzzy logistic regression model proposed by Pourahmad and et al. with Tanaka’s
revised model. The results are discussed.
4 - Ranking of Strategies in a Strategy Map based on
Logarithmic Fuzzy Preference Programming
Hossein Safari, Fatemeh Mirzaei Rabor
There is a well-known technique in MCDM entitled AHP. Pairwise matrix was used in AHP which always has a risk related to inconsistency.
So Least Square Method was developed to minimize inconsistency.
Then Logarithmic LSM introduced that gain better solutions with crisp
data. With fuzzy data, at first Fuzzy Preference Programming was presented. In continue, logarithmic FPP was developed that solve through
meta-heuristics algorithms. This paper introduces a method for converting LFPP to a NLP. Finally new method was tested for strategies
ranking with programming in LINGO.
HD-08
Thursday, 14:00-15:30 - Room 120
Teaching OR/MS 2 (JMP)
Stream: Teaching OR/MS
Sponsored session
HD-07
Thursday, 14:00-15:30 - Room 003
Fuzzy Programming and Fuzzy
Regression Analysis
Stream: Fuzzy Optimization - Systems, Networks and
Applications
Invited session
Chair:
Chair:
Chair:
Chair:
190
Silja Meyer-Nieberg
Erik Kropat
Juan Carlos Figueroa-García
German Hernandez
Chair: Volker Kraft
1 - How to Teach Crime Analytics? An Introductory
Board Game Motivating Policing Strategies
Richard Weber, Victor Bucarey
Crime is an important threat in most cities. The recent increase in
data availability allows developing quantitative models for crime analysis. What we have observed, however, is the need to recognize the
potential of advanced mathematical tools to improve the effectiveness
of policing strategies. Secondly, we noticed a lack of knowledge and
experience among engineering students when it comes to model complex human behavior. We present a board game that introduces the key
concepts of policing strategies and serves as an introduction to crime
analytics and agent-based simulation.
IFORS 2014 - Barcelona
2 - Teaching OR/MS using JMP (I)
Volker Kraft
The successful teaching of analytics in the classroom stands and falls
with the instructor, but also depends heavily on the utility of the chosen toolset and the relevance of the examples used during lessons and
workshops. JMP is software from SAS Institute aimed at Statistical
Discovery, and this presentation shows how its unique philosophy and
interactivity can help to foster and facilitate best practice when used in
teaching. A variety of live examples will be demonstrated to illustrate
the pedagogic advantage of JMP, especially in the fields of predictive
modelling and data visualization.
3 - Teaching OR/MS using JMP (II)
Volker Kraft
The successful teaching of analytics in the classroom stands and falls
with the instructor, but also depends heavily on the utility of the chosen toolset and the relevance of the examples used during lessons and
workshops. JMP is a software from SAS Institute aimed at Statistical
Discovery, and our presentation shows how its unique philosophy and
interactivity can help to foster and facilitate best practice when used in
teaching. A variety of live examples will be demonstrated to illustrate
the pedagogic advantage of JMP, especially in the fields of predictive
modelling and data visualization.
HD-10
4 - A Decision Support Tool for the Optimal Distribution
of Thermal Energy
Chiara Bordin
This work presents a mathematical model developed for supporting
district heating system optimal planning in real world applications.
The objective is the connection of an optimal set of new users to the existing thermal grid, minimizing costs and respecting the main hydraulic
conditions of real networks. Model constraints are inserted to control
flow rate values, pressures values, water direction along the pipes and
nodes degree. The model was integrated with a decision support tool
which uses GIS technology and database to facilitate scenario creation
and analysis of very big real networks.
HD-10
Thursday, 14:00-15:30 - Room 122
DEA Theory III
Stream: Theoretical Developments in DEA
Invited session
Chair: Kaoru Tone
HD-09
Thursday, 14:00-15:30 - Room 121
Exact and Heuristics Decision Support
Approaches for Energy Distribution,
Planning and Management
Stream: Technical and Financial Aspects of Energy
Problems
Invited session
Chair: Chiara Bordin
1 - Optimizing the Use of Domestic Loads in an Energy
Management System
Carlos Henggeler Antunes, Ana Soares, Alvaro Gomes
A methodology to be implemented in an energy management system
to schedule domestic loads is presented. A genetic algorithm is used
to solve this problem considering a limit for the contracted power, an
energy safety margin to take into account changes of non-controllable
load and avoid the risk of interruption of energy supply, and end-users’
preferences. These are tackled by assigning variable costs to the time
slots in which the end-user allows the operation of controlled loads.
The aim is minimizing the overall cost associated with energy purchase
and preference violation.
2 - Contract Portfolio Optimization for Energy Trader
Cristian Bovo, Mario Innorta
A mathematical model for the optimization of the contract portfolio
of a trader for the supply of natural gas will be described. The objective function is the minimization of the supply cost taking into account
the following constraints: balance constraints, Take or Pay (ToP) constraints; make up and carry forward constraints to hedge the risk associated with the ToP contracts; gas transmission constraints designed
to represent transportation contracts holds by the trader; storage constraints. Moreover, the model will take into account the possibility to
buy or sell gas on the spot market.
3 - Optimal Operation of Medium-Voltage AC Networks
with Distributed Generation and Storage Devices
Maria Teresa Vespucci, Diana Moneta, Paolo Pisciella
A medium-voltage AC network with distributed generation and storage
devices is considered for which set points are assigned in each time period of a given time horizon. In order to restore feasibility when some
parameters vary, new set points need to be determined to minimize distributor’s dispatching costs, while satisfying service security requirements and ensuring service quality. We propose a two-phase solution
procedure: an MILP model determines the active power production
and the use of storage devices; reactive variables are then computed by
solving a nonlinear programming model.
1 - The Overall Malmquist Index: A New Approach for
Measuring Productivity Changes Over Time
Mohsen Afsharian, Heinz Ahn
This paper proposes a new way of constructing the global framework
of the Malmquist index. The proposed index preserves the role of
each contemporaneous technology in the determination of the newlyproposed benchmark technology, whereby an acceptable level of discrimination between non-homogeneous observations is provided. Furthermore, previously computed results are more stable and less sensitive to changes in the shape of the benchmark technology when a new
time period is incorporated. The suggested index will be illustrated by
means of a real-world example from banking.
2 - Global Efficiency and Global Progress and Regress
Index: A Quasi-Concave Frontier Approach
Mohsen Vaez-Ghasemi, Zohreh Moghaddas, Farhad
Hosseinzadeh Lotfi
In existing models of data envelopment analysis (DEA) which evaluate efficiency measure in various time periods, technology variations
have not been considered. Note that using DEA approach for deriving
malmquist productivity index a specific score for efficiency will not
be resulted. Thus in regards of DEA axioms, a quasi-concave frontier
is considered for deriving efficiency score in different periods. Also
the measure of progress and regress of units is provided which is not
possible in malmquist productivity index introduced in DEA analysis.
3 - A New Approach to the Bi-Dimensional Representation of the DEA Efficient Frontier with Multiple Inputs
and Outputs
Carlos Bana e Costa, João Carlos Soares de Mello, Lidia
Angulo-Meza
This paper presents a new approach to the graphical presentation of
DEA results. Whatever the number of inputs and outputs are, an adequate normalization of their weights is enough to generate a simple
bi-dimensional graph, similar to that of the CCR frontier with one input and one output. No complementary techniques are required. It is
also shown that the horizontal (or vertical) distance between a DMU
and the frontier is the DMU’s efficiency score obtained by the standard
CCR model. The proposed normalization is also valid for the BCC
model.
4 - Resampling in DEA
Kaoru Tone
In this paper, we propose new resampling models in data envelopment
analysis (DEA). Input/output values are subject to change for several
reasons, e.g., measurement errors, hysteretic factors, arbitrariness and
so on. Furthermore, these variations differ in their input/output items
and their decision-making units (DMU). Hence, DEA efficiency scores
need to be examined by considering these factors. Resampling based
on these variations is necessary for gauging the confidence interval of
DEA scores. We propose three resampling models.
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HD-11
Thursday, 14:00-15:30 - Room 113
Applications of Combinatorial
Optimization
Stream: Combinatorial Optimization
Invited session
Chair: Stephan Visagie
1 - Adjusting the Size-Mix of Products During Stock Allocation
Elmien Thom, Stephan Visagie, Jason Matthews
A specific size-mix problem of a retailer with over 1500 stores is introduced. The retailer adjusts the size-mix sent to each store during
the season. Models are presented to find good adjustments to the original forecasted size-mix of each store. Heuristic approaches are presented because solving the problem to optimality is computationally
too expensive to implement in real life. Results show that the proposed
heuristics improve on the solutions found by the method currently in
use.
2 - SKU Assignment in a Zoned Order Picking System
with Unidirectional Picking Lines
Stephan Visagie, Jason Matthews
A real life order picking system in a distribution center that utilizes
16 unidirectional cyclical picking lines for break bulk picking is presented. SKUs are processed in waves on picking lines, each of which
defines a local deterministic set of orders. The assignment of SKUs
to available picking lines with the main objective of minimizing total
walking distance, while controlling carton utilization and work balance
is considered. Three families of algorithms are introduced. Results
show that the proposed algorithms improve on the current system.
3 - A 2D Irregular Levelled Strip Packing Problem: A
Case Study
Isabelle Nieuwoudt, Wayne Bossenger
Kohler Signs is a small company located in Cape Town, South Africa
that mainly manufacture road signs for the City of Cape Town. The
image design for each sign consists of letters, numbers and shapes that
must be cut from a roll of vinyl. In this talk the focus is on the packing of letters and numbers onto the roll of vinyl in such a manner as
to minimie the waste. Although irregular in nature, these items are
regular in one dimension. Thus, 2D regular strip packing ideas in conjunction with image processing methodologies are used to develop a
new packing algorithm for this specific problem.
4 - Computing Pairs of Disjoint Paths by Order of Cost
Marta Pascoal
Pairs of disjoint paths between two nodes have important applications
in routing, for instance, when a backup path is needed in case one of
the arcs of the best path fails or in order to avoid over-exposure of the
same region to hazardous materials. The problem of finding the minimum cost pair of disjoint paths can be formulated as a minimum cost
flow problem and can be solved polynomially by an adaptation of labeling algorithms. In this talk we address the problem of ranking pairs
of disjoint paths by increasing order of cost. Polynomial algorithms to
rank these solutions are discussed.
HD-12
Thursday, 14:00-15:30 - Room 004
Project Scheduling and Control
Stream: Project Management and Scheduling
Invited session
Chair: Mario Vanhoucke
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1 - Introducing Overtime in the Resource Renting Problem
Len Vandenheede, Mario Vanhoucke, Broos Maenhout
The use of overtime has frequently been studied in literature. Furthermore, it is applied in real-life for several reasons. However, research
on the project scheduling problem (PSP) in combination with overtime
are scarce. We aim to introduce the use of overtime in the Resource
Renting Problem. We have developed a method to study the trade-off
between stricter deadlines and a higher cost due to scheduled overtime.
A computational experiment will demonstrate how the use of overtime
and resource scheduling can lead to a more efficient use of resources
and a better human resource management.
2 - Payment Models and NPV Maximization in Project
Scheduling
Pieter Leyman, Mario Vanhoucke
In project scheduling literature several payment models exist. Although the goal is always to maximize the project NPV, these payment
models have different characteristics which typically require distinct
approaches to maximize each model’s NPV. We propose a general local search capable of handling the different NPV profiles efficiently.
This local search consists of several parts which can be turned on or
off, depending on the payment model. Specifically, this methodology
is applied to the resource-constrained project scheduling problem with
discounted cash flows.
3 - A Forecasting Approach for Project Duration and
Cost based on Exponential Smoothing
Jordy Batselier, Mario Vanhoucke
In this paper, the earned value management (EVM) project control
methodology is integrated with the exponential smoothing forecasting
approach. This results in an extension of the known EVM and earned
schedule (ES) time and cost forecasting formulas. The enhanced EVM
performance factor depends on only one smoothing parameter, which
facilitates calculation. Moreover, this parameter can be dynamically
adjusted during project progress according to information of past performance and/or anticipated management actions. The novel method
is evaluated based on extensive real-life project data.
4 - Strategic Incentive Contract Design for Projects
Louis-Philippe Kerkhove, Mario Vanhoucke
The agency problem between the owner and the contractor in a project
environment is often resolved using multidimensional incentive contracts. This research evaluates the design of such contracts from
a quantitative perspective, presenting several guidelines for strategic
contract design. The analysis is based on high-level models of the
cost/time/scope and incentive pay-offs. Using these models, computational experiments are carried out on both real and simulated data. The
presentation will focus on the preliminary results of these experiments
and the managerial implications thereof.
HD-13
Thursday, 14:00-15:30 - Room 123
Balancing and Sequencing of Assembly
Lines 1
Stream: Scheduling
Invited session
Chair: Alexandre Dolgui
Chair: Alberto García-Villoria
Chair: Xavier Delorme
1 - The Accessibility Windows Assembly Line Balancing Problem (AWALBP): A Review of Advances and
Trends
Gema Calleja, Albert Corominas, Alberto García-Villoria,
Rafael Pastor
We investigate the Accessibility Windows Assembly Line Balancing
Problem (AWALBP), where, in sharp contrast to traditional assembly line problems, only a portion of the workpieces can be reached
from each workstation. The literature distinguishes different variants
IFORS 2014 - Barcelona
of the problem, and several formulations and solution approaches have
been proposed. This talk gives an overview on recent advances in the
methods used to solve AWALBP, including exact, heuristic and hybrid
methods. An extensive set of computational experiments, along with
some guidelines for further lines of research are reported.
2 - MILP-based Tabu Search using Corridor Method for
an Assembly Line Balancing Problem with Accessibility Windows
Albert Corominas, Alberto García-Villoria, Gema Calleja,
Rafael Pastor
In this work, we present an MILP-TS matheuristic for an assembly
line balancing problem with accessibility windows. The proposed
matheuristic uses an MILP model embedded in a tabu search (TS) algorithm to iteratively solve reduced portions of the original solution
space. We use the paradigm of the corridor method to impose exogenous constraints of the original mathematical formulation and, subsequently, we apply an MILP solver to optimally solve the constrained
problem. Computational results show the effectiveness of the proposed
matheuristic.
3 - Ergo-Balancing in Assembly Lines based on Energy
Expenditure Rate
Fabio Sgarbossa, Daria Battini, Alessandro Persona
In many assembly systems, ergonomics impacts in relevant way on
productivity and human safety. Traditional optimization approaches
considers only time variables. In this paper an innovative balancing
model is developed including the ergonomics aspect, defined by energy expenditure rate, based on main features of assembly workstations. First, a comparison between time and energy balancing is carried out, and then a new integrated analytical model is introduced to
have a unique objective function. A real case allows the validation of
the approach and some further researches are defined.
4 - Efficient Multi-Objective Optimization Method for the
Mixed-Model-Line Balancing and Equipment Selection Problem
Jonathan Oesterle, Lionel Amodeo
The Assembly Line Balancing Problem is a classical Operations Research problem, having been tackled over several decades. While some
multi-objective approaches can be found in the literature, there only
exist few studies that address the task and equipment assignments together. Our paper proposes a new efficient multi-objective optimization method for the Mixed Model Line balancing and equipment selection problem based on an adaptation of the Strength Pareto Evolutionary Algorithm-2, in which the idle time of various models among an
assembly line and the equipment costs are minimized.
HD-14
Thursday, 14:00-15:30 - Room 124
Advances in Nonlinear Optimization:
Theory and Applications III (contributed)
Stream: Nonlinear Programming
Contributed session
Chair: Gonca Inceoglu
HD-15
2 - Convergence of the Gauss-Newton Method for a Special Class of Systems of Equations under a Majorant
Condition
Max Leandro Nobre Gonçalves
In this talk, we study the Gauss-Newton method for a special class of
systems of non-linear equations. On the hypothesis that the derivative of the function under consideration satisfies a majorant condition,
semi-local convergence analysis is presented. In this analysis, the conditions and proof of convergence are simplified by using a simple majorant condition to define regions where the Gauss—Newton sequence
is ’well behaved’. Moreover, special cases of the general theory are
presented as applications.
3 - Enhanced Line Search Methods
Adriano Lisboa, Douglas Vieira
We start proving that the classical Golden section converges to a local
optimum for any function, including multimodal ones. However, this
local optimum may be worse than the starting point. This is specially
undesired considering that the search direction usually induces better
points near the starting point. We solve this drawback by applying
a backtracking search until a no worse point is met. With this simple
change, it is possible to prove that the golden section method converges
to a local optimum no worse than the starting point. Analogous results
follow for other line search methods.
4 - Optimality Conditions via Generalized Radial Epiderivatives
Gonca Inceoglu, Refail Kasimbeyli
In this paper, the generalized radial epiderivative for set-valued maps
is introduced and its relationship to the radial epiderivative is investigated. Existence conditions for the generalized radial epiderivatives
are established and a unified necessary and sufficient optimality condition in nonconvex set-valued optimization is derived in terms of the
generalized radial epiderivative.
HD-15
Thursday, 14:00-15:30 - Room 125
Revenue Management Models in
Entertainment, Online Retail and Travel
Stream: Revenue Management II
Invited session
Chair: Kihoon Kim
1 - Pricing and Revenue Management in Sequential Distribution Channel: An Application to the Hindi Movie
Industry
Sumanta Basu, Megha Sharma, Soumyakanti Chakraborty
With about 125 movie releases in a year, Hindi movie industry is one
of the largest producers of movies in the world. Recently satellite or
DTH rights of the movies released are sold within 2 months of their
theater release. While a movie’s earnings from those channels decrease
with time, an early release cannibalizes box office collection and DVD
sales. Hence in this work, we attempt to determine the optimal release
times to different channels using statistical methods and mathematical
modeling, especially in light of video piracy, and word of mouth movie
reviews through social media.
1 - Generalized Inexact Proximal Algorithms: Habit’s
Formation with Resistance to Change, following
Worthwhile Changes
Glaydston Bento, Antoine Soubeyran
2 - A Simulation Optimization Approach for SelfAdjusting Bid Prices of a Network Revenue Management Considering Booking Cancellations and Firms
Competition
Kemal Subulan, Gokalp Yildiz, Derya Eren Akyol, Adil
Baykasoğlu
This work shows how, in a quasi metric space, an inexact proximal
algorithm with a generalized perturbation term appears to be a nice
tool for Behavioral Sciences (Psychology, Economics, Management,
Game theory, ...). More precisely, the new perturbation term represents an index of relative resistance to change, defined as a "curved
enough" function of the quasi distance between two successive iterates. We show when, and at which speed, a "worthwhile to change"
process converges to a variational trap.
Recently, there is a growing attention by researchers to compute bid
prices of resources dynamically in a network revenue management. A
simulation optimization approach is presented in order to determine the
appropriate values of coefficients in the bid price function that depends
on reserved capacity and expected demand. Different meta-heuristic
algorithms: DE, PSO & SOA are utilized to find out these coefficients
within a simulation model. Apart from the existing literature, uncertain
nature of cancellations and firms’ competition throughout the booking
horizon are also taken into account.
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3 - Implementing Balance Scorecard Using ELECTRE
Method for Revenue Management
Volkan Çakır, Idil Ekiz, Ozge Sahin
4 - Using Fare-Card Data to make Commuter Cycling
Policies in Singapore
Ashwani kumar, Viet Anh Nguyen, Kwong Meng Teo
Revenue management (RM) has become an indispensable strategic
tool in service industries whose total revenue often depends on the
abilities of firms to use capacity efficiently. The Balanced Scorecard
(BSC) is a widely used performance management tool designed to improve the performance of the businesses. This paper considers a real
case application of revenue increasing project selection for BSC implementation using ELECTRE. Results show that ELECTRE was well
received by the decision makers and, importantly, provided sensible
and straightforward rankings and can be easily used in RM problems.
Peak-hour week-day traffic congestion is a common challenge in urban
mobility. Promotion of commuter cycling can help in alleviating this
problem in many cities. This paper uses fare-card data to assess the
commuter cycling potential in Singapore. A spatio-temporal analysis
of the farecard data helps in suggesting policies like cycling towns and
links for the first-mile and end-to-end cycling. Further, an optimization
model is developed to make efficient policy choices for a given budget.
4 - Optimization of Flight Business Travel Procurement
Kathrin Armborst
Flight business travel is an important function of multinational corporations and leads to high costs. The developed decision support system assists in annual contract negotiations with airlines and optimizes
airline selection and flight contingent allocation with the goal of cost
reduction. Results of dynamic decision-making under uncertainty with
quantity discounts applying the structured decision process and MILP
models will be presented.
HD-16
Thursday, 14:00-15:30 - Room 127
Data Analysis and Transport Planning
Stream: Intelligent Optimization in Machine Learning
and Data Analysis
Invited session
Chair: Nikita Ivkin
1 - Vehicle Maneuvers Detection Using Data from Accelerometer
Nikita Ivkin
When applying data-driven classification approach to simulation modeling of traffic flow we suppose each simulated object (traffic vehicle)
to make decisions based on the current surrounding condition. In current research we consider the subproblem of creating formal description of decisions space. Using experimental data we develop an algorithm for detecting maneuvers (like lane change or overtaking) from
time series of acceleration measured in three dimensions. The proposed approach provides a technique of structured data collection for
the general problem of evaluation simulation models.
2 - The Use of New Technologies to Estimate Dynamic
Passenger Matrices: Proof of the Concept
Lídia Montero, Esteve Codina
The use of new technologies to track passenger progress in his/her trip
contributes to simplify the estimation of dynamic passenger OD matrices. The approach proposed is based on the detection of the electronic
signature of on-board devices, providing real-time dynamic data that is
treated as measurements in a space-state Kalman filter formulation. A
bus network has been developed for testing purposes and data generated by simulation. Some experiments have been conducted in order to
assess how the quality of the a priori historic matrix and sensor layout
affects the goodness of fit results.
HD-18
Thursday, 14:00-15:30 - Room 112
Optimization and Decision Making:
Theory and Applications
Stream: Multiobjective Optimization - Theory, Methods
and Applications
Invited session
Chair: Pekka Malo
Chair: Ankur Sinha
1 - An Enhanced Fourier-Motzkin Method for Data Envelopment Analysis
Abolfazl Keshvari
Generating redundant constraints is an issue of Fourier-Motzkin elimination method for a general linear programming problem. In this paper,
we propose an enhanced Fourier-Motzkin algorithm that does not generate redundant constraints for a data envelopment analysis problem.
The algorithm also generates normal vectors of the facets of production possibility set of the DEA problem. Using the proposed algorithm
and the Qhull program, we enumerate facets of some DEA problems.
We compare the results, and the running times of these two methods.
2 - Solving Hierarchical Decision Making and Optimization Problems
Pekka Malo, Ankur Sinha
We consider hierarchical decision making and optimization problems,
where both the leader and follower are faced with multiple objectives.
Often the leader attempts to optimize the problem by taking the actions
of the follower into account. However, when the preferences of the follower are unknown, it leads to decision uncertainty. In our study, we
discuss practical examples and propose an evolutionary optimization
strategy to solve such problems.
3 - Some Properties of Vectorized Directional Derivative
For Set-Valued Mappings
Mustafa Soyertem, Mahide Kucuk, Yalcin Kucuk
A generalization of directional derivative for set-valued mappings was
given by using vectorization in terms of total ordering cones. In this
study, some algebraic properties of this derivative are given for a special class of set-valued mappings. These properties are demonstrated
on some examples. The relations between this directional derivative
and some other directional derivatives for set-valued mappings are also
studied.
3 - Advanced Traffic Monitoring System by Probe Vehicles under Privacy Preservation
Hiroyuki Kawano
4 - A Two-Objective Container Loading and Assortment
Problem
Zeynep Özsüt, Refail Kasimbeyli
It is increasingly important to correctly measure traffic data by probe
vehicles, including speed, acceleration, location, and other data. In
our previous researches, we propose that it is possible to be accurately
monitored vehicle traffic by integration of supersonic wave detection
devices and highway patrol vehicles equipped GPS transceivers. In
this paper, we discuss accuracy of traffic volume and flows depending
on density of probe vehicles. Furthermore, under privacy preserving
conditions, we propose an architecture of traffic management system
using our proposed methods.
In this work we study container loading (CLP) and assortment problem where different sizes of container types is available and a set of
rectangular boxes has to be assign according to constraints. We propose a two-objective mixed-integer programming model for the CLP.
The objective functions are formulated in the form of minimizing the
free space of the used containers that is the wasted space, and the number of used container types. We used different scalarization methods
to solve the recommended two-objective mixed-integer programming
model and compared obtained solutions.
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HD-19
Thursday, 14:00-15:30 - Room 128
Inventory Planning III
Stream: Demand and Supply Planning in Consumer
Goods and Retailing
Contributed session
Chair: Hiroaki Sandoh
1 - Inventory-Routing Problem with Pickups and Deliveries of RTI in Closed-Loop Supply Chain
Sabine Limbourg, Galina Iassinovskaia, Fouad Riane
Reducing environmental impact, related regulations and potential for
operational benefits are the main reasons why companies share their
Returnable Transport Items (RTIs) among different partners of a
closed-loop supply chain. This research deals with an inventoryrouting problem with pickups and deliveries of RTIs. A mixed-integer
linear program is developed and tested on small instances. To handle
realistic large size problems, a clustering algorithm is coupled with a
simulation model. This hybrid heuristic allows assessing the benefits
of information and RTIs sharing among partners.
2 - Optimizing Inventory and Pricing Decisions for a
Periodic-Review System with Batch Ordering
Ying Wei, Feng Li
This paper examines inventory and pricing decisions in a periodic review system with an infinite planning horizon. Order quantities are
required to be a non-negative integer multiple of certain batch size Q.
Pricing decision is determined at the beginning of the planning horizon and fixed forever. A fixed and proportional ordering cost occurs
for each ordering. With the objective of maximizing the long-run average profit, this paper investigates the operating characteristics of an (r,
Q)-p system, and further develops a computing procedure identifying
the optimal (r, Q)-p decisions.
3 - Optimal Quantity of Apparel Goods for Direct Mail
Hiroaki Sandoh, Hyewon Kim, Takeshi Koide
In direct mail industries dealing with apparel goods, of greater concern is the determination of a stocking quantity of each product to be
purchased from a manufacturer prior to the seasonal catalogue. If the
demand distribution of each product is beforehand identified, the problem is a newsvendor problem. This study proposes a method for identifying the demand distribution of each product listed in the seasonal
catalogue, assuming that the DM firm offers advance sale of his products only to his members by sending a reservation catalogue about a
half year prior to the seasonal catalogue.
4 - Model to Optimize the Internal Supply Chain in an Industry of Mobile Phones Located in Brazil
Fabricio Rodrigues Costa
The mobile phone is an electronic device with high value added. Maintain inventories of raw materials, intermediates and finished products
are expensive. A supply chain network is characterized by the suppliers, plants, distributors and customers distributed across a geographic
region. This concept was applied to a mobile phone industry, located
in Manaus, capital of Amazon, Brazil. Was developed a model to optimize the internal supply chain using the tool Supply Chain Strategist,
who has applied the concept of Material Requirement Planning dedicated to stock the main printed circuit board.
HD-21
1 - Stochastic Optimization Methods for Real-Time Control of Electrical Grids by Using Explicit Power Setpoints
Andrey Bernstein, Lorenzo Reyes Chamorro, Jean-Yves Le
Boudec, Mario Paolone
The classic approach for controlling power networks is a combination
of both frequency and voltage controls. With the increased penetration
of volatile distributed generation and demand response, it shows severe
limitations. A different control approach was recently proposed by the
authors, enabling subsystems to directly communicate with each other
in order to define real-time power setpoints and advertise a simplified
representation of their internal state. In this paper, we discuss stochastic optimization methods to compute the setpoints that steer the system
to an optimal and safe state.
2 - Power Control for Solar Micro-Grids in Developing
Countries
Carlos Abad, Garud Iyengar
Solar micro-grids are emerging as the most promising means of providing power to isolated communities in some of the poorest parts of
the world. In order to avoid depleting the battery backup the micro-grid
operator shuts off a customer circuit whenever the consumer’s power
exceeds the individually pre-assigned power limit. In addition, weather
conditions can lead to lower electricity generation and the disruption
of customers that are not violating their power limits. We investigate
control policies that maximize the operator’s revenue while minimizing the number of disruptions to customers.
3 - Risk-Averse Strategic Planning of HVDC Grids
Pavlo Krokhmal, Bo Sun, Yong Chen
We consider the problem of risk-averse strategic planning of highvoltage direct current (HVDC) grids. HVDC transmission systems
offer significant advantages comparing to the traditional AC transmissions. We discuss the problem of long-term (strategic) planning of
HVDC grids that incorporate sources of renewable energy, such as
large-scale wind farms. Risks of power shortages are controlled using
nonlinear higher-moment coherent risk (HMCR) measures. Solution
methods for the resulting mixed-integer programming problems and
computational case studies are presented.
4 - Stochastic Approach used for Life Cycle Inventory
(LCI) Modeling of the Energy Production in the Integrated Steel Plant’s Power Plant in Poland: Case
Study
Boguslaw Bieda
The goal of this paper is to use stochastic approach for Life Cycle
Inventory (LCI) as the first step in performing a full Life Cycle Assessment (LCA) analysis in the energy production applied to a Power
Plant of Integrated Steel Plant in Krakow, Poland. The framework for
this study using Monte Carlo (MC) simulation is based on the 2005
data. The MC sampling was done using Crystal Ball R software. The
complete inventory was integrated by 48 environmental loads (inputs,
outputs): energy and raw materials consumed, wastes produced, and
emissions to air, water and soil.
HD-21
Thursday, 14:00-15:30 - Room 006
Cutting and Packing 3
Stream: Cutting and Packing
Invited session
HD-20
Thursday, 14:00-15:30 - Room 129
Managing Smart Energy Grids under
Uncertainty - II
Stream: Stochastic Optimization in Energy
Invited session
Chair: Pavlo Krokhmal
Chair: Ramon Alvarez-Valdes
1 - An Efficient MIP Formulation of the Container Loading Problem
Giorgio Fasano
Effective algorithms have been devised to tackle the container loading problem. An alternative overall approach addresses Mixed Integer
Programming (MIP), being well-suited for the introduction of additional conditions, e.g., balancing. Direct formulations are available in
the literature. They are, however, poorly efficient in practice, albeit the
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IFORS 2014 - Barcelona
addition of valid inequalities. A non-intuitive MIP-model, founded on
an ad hoc objective function expression, is proposed. This reformulation outperforms the straight MIP-models. It can profitably be used to
build up MIP-based heuristics.
2 - Studying Different Models for the Truck Loading Process
Maria Teresa Alonso Martínez, Ramon Alvarez-Valdes,
Manuel Iori, Francisco Parreño, Jose Tamarit
We model the process of loading products into trucks. There is a list
of products to be delivered, these products are put in pallets and the
pallets are placed into trucks. A basic model, including only limits on
the axle weights, has been created. Starting from this initial model,
we have studied different ways of placing the pallets into the trucks.
Additionally, some realistic constraints have been studied, concerning
the position of the centre of gravity, the stability of the load, and the
minimization of the unloading time. The models have been tested on a
set of real-world instances.
3 - Efficient Local Search Algorithms for ThreeDimensional Packing Using Sequence-Triple
Shinji Imahori, Hiroki Iwasawa
We study the problem to pack n boxes into a rectangular container with
three variable dimensions so as to minimize its volume. SequenceTriple is a topological representation of placements with a triplet of
permutations of boxes. In this talk, a decoding algorithm to compute
a layout of boxes for a Sequence-Triple is presented. We also propose
an efficient method to evaluate solutions in the neighborhood of the
current solution. Local search algorithms for the 3D-packing problem
using Sequence-Triple are designed, and experimental results show the
effectiveness of the proposed methods.
which makes an interesting parallel with the well-understood case of
CAs with money for single-minded bidders. We then give a host of
bounds on the approximation ratio obtained by either deterministic or
randomized truthful mechanisms when the sets and valuations are private knowledge of the bidders.
HD-23
Thursday, 14:00-15:30 - Room 008
Panel Discussion: Analytics in OR
Societies
Stream: Analytics Application and Practice
Panel session
Chair: Don Kleinmuntz
1 - Panel Description: Analytics in OR Societies
Don Kleinmuntz, Sayara Beg, Stewart Robinson, Glenn
Wegryn
The burgeoning growth and attention devoted to "Big Data" and Analytics poses both a challenge to and an opportunity for OR Societies
and for academic OR departments. Leaders of Analytics outreach
efforts from OR Societies in the UK and USA will provide a brief
overview of how their respective societies are responding, and the results to date. Session attendees are encouraged to provide their own
perspectives, and to identify opportunities for international cooperation. Confirmed panelists are listed above.
HD-22
HD-24
(In)efficiency and Truthfulness in
Auctions
Repeated and Stochastic Games
Thursday, 14:00-15:30 - Room 007
Stream: Algorithmic Game Theory
Invited session
Chair: Giorgos Christodoulou
1 - The Price of Anarchy of First-Price Auctions
Giorgos Christodoulou, Annamaria Kovacs, Alkmini
Sgouritsa, Bo Tang
We study the Price of Anarchy of simultaneous First-Price auctions for
buyers with submodular and subadditive valuations. The current best
upper bounds for the Bayesian Price of Anarchy of these auctions are
e/(e 1) and 2, respectively. We provide matching lower bounds for
both cases even for the case of the full information and for mixed Nash
equilibria. An immediate consequence of our results, is that for both
cases, the Price of Anarchy of these auctions stays the same, for mixed,
correlated, coarse-correlated, and Bayesian Nash equilibria.
2 - On the Inefficiency of Standard Multi-Unit Auctions
Orestis Telelis, Bart de Keijzer, Evangelos Markakis, Guido
Schäfer
We study two standard multi-unit auction formats, with significant
practical applications: the Discriminatory and the Uniform Price Auctions. We consider two bidding interfaces: (i) standard bidding, which
is most prevalent in the scientific literature, and (ii) uniform bidding,
which is more popular in practice. We evaluate the economic inefficiency of both formats for both bidding interfaces, by means of upper
and lower bounds on the Price of Anarchy of pure and Bayes-Nash
equilibria. Our results signify the near-efficiency of these auctions,
and justify their widespread use in practice.
3 - Combinatorial Auctions without Money
Carmine Ventre
We focus on the design of incentive-compatible CAs without money
in the general setting of k-minded bidders. We trade monetary transfers with the observation that the mechanism can detect certain lies
of the bidders. We prove a characterization of truthful mechanisms,
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Thursday, 14:00-15:30 - Room 212
Stream: Dynamic and Repeated Games
Invited session
Chair: Xavier Venel
1 - The Asymptotic Value in Finite Stochastic Games
Miquel Oliu Barton
Bewley and Kohlberg (1976) proved that the discounted values of finite
zero-sum stochastic games have a limit, as the discount factor tends to
zero, using the Tarski-Seidenberg elimination theorem from real algebraic geometry. This was a fundamental step in the development of
the theory of stochastic games. The current paper provides a new and
direct proof for this result, relying on the explicit description of asymptotically optimal strategies. Moreover, we prove that our approach can
also be used to obtain the existence of the uniform value, as in Mertens
and Neyman (1981).
2 - Attainability in Repeated Games with Vector Payoffs
Xavier Venel, Dario Bauso, Ehud Lehrer, Eilon Solan
We introduce the concept of attainable sets of payoffs in two-player
repeated games with vector payoffs. A set of payoff vectors is called
attainable if player 1 can ensure that there is a finite horizon T such
that after time T the distance between the set and the cumulative payoff is arbitrarily small, regardless of what strategy player 2 is using.
We provide a necessary and sufficient condition for the attainability of
a convex set, using the concept of B-sets from the theory of approachability.
3 - Dynamic Persuasion
Nicolas Vieille, Eilon Solan, Jérôme Renault
We study a class of dynamic sender receiver models. An informed
agent (say, a financial advisor) observes the successive realizations of
a state of nature, which follow a Markov process, and decides what
information to disclose to an uninformed decision-maker. We focus on
the case where the advisor can ex ante commit to a disclosure policy
(persuasion), and derive his optimal policy.
IFORS 2014 - Barcelona
HD-25
Thursday, 14:00-15:30 - Room 009
Heuristics for Dynamic Transit Routing
Stream: Applications of Heuristics
Invited session
Chair: Amelia C. Regan
Chair: Elise Miller-Hooks
1 - Routing for Ridesharing Services Considering Congestion
Maged Dessouky, Xiaoqing Wang, Fernando Ordonez
We consider a vehicle pickup and delivery problem with the objective
of minimizing the total travel cost and customer ride time while considering the discounted toll rates on high occupancy vehicles and the
availability of HOV lanes. This problem formulation is used to represent a real-time marketplace for ridesharing. Heuristics are developed
to efficiently solve the problem. The Adjust Pickup Time Algorithm
and the Waiting Strategy are proposed to reduce the total cost and the
customer ride time.
2 - Dynamic Vehicle Routing and Pricing with Look
Ahead for Flexible Transit
Joseph Chow, Hamid Sayarshad
We propose a dynamic dial a ride and pricing problem with nonmyopic policies for last mile transit, one with time-dependent nonhomogeneous Poisson process for customer demands. Three policies
are considered: customer-vehicle allocation, waiting/prepositioning,
and dynamic fare pricing. Pricing is incorporated as discussed in
Figliozzi et al. (2007). Several approximation dynamic programming
methods are compared in test instances: a Q-learning-based ADP, a
queueing approach based on Hyytia et al. (2012), and a benchmark
using least-squares Monte-Carlo simulation.
3 - The Dial-A-Ride Problem with Uncertain Travel Times
Elise Miller-Hooks
Paratransit services, including Dial-A-Ride (or DAR) services commonly offered at airports and to mobility-impaired persons, exist
worldwide. If operated efficiently, they provide door-to-door transport at significantly lower cost than taxis by serving multiple riders simultaneously and combining trips whose paths are somewhat aligned.
Efficient DAR services require solution of difficult combinatorial problems. Complexities associated with the efficient provision of DAR services in real-world applications, including uncertainty in travel times,
are presented here.
4 - Incremental Network Design
Martin Savelsbergh
We introduce a class of incremental network design problems that allow investigation of key issues related to the choice and timing of infrastructure expansions and their impact on the costs of the activities
performed on that infrastructure. We examine three variants: incremental network design with shortest paths, incremental network design
with maximum flows, and incremental design with minimum spanning
trees. We investigate their computational complexity, analyze the performance of natural heuristics, derive approximation algorithms, and
study integer programming formulations.
HD-27
1 - Optimal Replenishment Order Placement in a Finite
Time Horizon
Giovanna Miglionico, Manlio Gaudioso, Giovanni
Giallombardo
We introduce the problem of scheduling and aggregating a fixed number of replenishment orders, along a given planning horizon, with the
aim of minimizing the total inventory and backorder costs. A continuous formulation is provided, which is characterized by a nonconvex
piecewise affine objective function. We introduce an ad hoc algorithm,
based on the coordinate search approach. To evaluate the quality of the
obtained solutions we provide a discrete formulation of the problem
whose exact solutions can be obtained by means of an integer programming commercial solver.
2 - A Heuristic Algorithm for Solving the Minimum Sumof-Squares Clustering Problems
Burak Ordin, Adil Bagirov
Clustering is an important task in data mining. It can be formulated
as a global optimization problem which is challenging for existing
global optimization techniques even in medium size data sets. Various
heuristics were developed to solve the clustering problem the global
k-means and modified global k-means. However, these algorithms are
not always accurate in finding global or near global solutions to the
clustering problem. In this paper, we introduce a new algorithm to improve the accuracy of the modified global k-means algorithm in finding
global solutions.
3 - Decomposition Approaches: The Role of the Master
Problem Formulation
Antonio Frangioni, Alberto Caprara, Tiziano Parriani
Decomposition methods for large-scale programs work by separating
the problem into small subproblems, and then "gluing back together"
the generated information. This latter step is fundamental, and is typically achieved by a master problem. By using Lagrangian relaxation
of large-scale multicommodity min-cost flows as an example, we show
that, even for a fixed decomposition, choosing the right master problem
formulation has a substantial impact on the overall performances and
therefore is a crucial step to obtain an ultimately efficient approach.
4 - A Computational Comparison of Approaches to Lagrangian Duals: The Case Study of FC-MMCF
Enrico Gorgone, Antonio Frangioni, Bernard Gendron
The focus of this work is to compare a large set of approaches for
solving Lagrangian duals of combinatorial problems. In particular we
compare different nonsmooth optimization methods like (incremental,
deflected, projected) subgradient-type algorithms and (disaggregated,
generalized) bundle-type algorithms. We use as a test set the multicommodity capacitated network design problem (FC-MMCF), a problem
arising in many different applications such as logistics, telecommunication and transportation.
HD-27
Thursday, 14:00-15:30 - Room 213
Decision Making and Applications
Stream: Decision Analysis, Decision Support Systems
Contributed session
Chair: Di Xu
HD-26
Thursday, 14:00-15:30 - Room 010
Nondifferentiable Optimization:
Applications to Large-Scale and
Combinatorial Problems
Stream: Nonsmooth Optimization and Variational Analysis
Invited session
Chair: Enrico Gorgone
1 - Research Project Evaluation and Selection Based on
the Evidential Reasoning Rule
Fang Liu, Weidong Zhu, Jian-Bo Yang, Dongpeng Wang
Current studies on Research Project Evaluation and Selection mainly
use traditional project evaluation methods, which have various limitations, such as making no difference between importance and reliability
and the inability to distinguish proposals due to limited linguistic values. The Evidential Reasoning rule has the features of managing importance and reliabilities of sources separately and handling highly or
completely conflicting evidence, so it is introduced to aggregate peer
experts’ comments. A case study is conducted using the peer review
data to demonstrate the applicability.
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IFORS 2014 - Barcelona
2 - Job Selection in a Network of Autonomous Unmanned Aerial Vehicles (UAVs) for Delivery of Goods
Pasquale Grippa, Doris Behrens, Christian Bettstetter,
Friederike Wall
Based on the analysis of job selection policies, we provide decisionmaking support for planning and operating a networked UAV-based
supply service. Similar to a dynamic VRP, jobs arrive over time for
certain locations according to a space-time stochastic process, and are
addressed in real time. Key novelties: (i) analysis of interdependence
between job selection policies and system infrastructure, both in terms
of system cost and stability, and (ii) providing evidence that the timing
of decision-making affects performance whereas the ’direction’ of the
effect is policy-dependent.
3 - A Framework of Decision Support Systems for Products Innovation
Di Xu
Products innovation is prior to production and more complex and
riskier than production. It is important to have a decision support system to support products innovation, just like production which is usually supported by ERP. This paper classifies the process of products
innovation into five steps: creativity collection and screening, scheme
generation, demonstration and evaluation. The characteristics of these
steps are different and need different kind of decision methods. A
meta-synthesis method is developed and a framework of decision support systems for products innovation is proposed.
4 - Transportation of Valuable Product: A Case Study
Billur Ecer, Serpil Erol
In globalizing World, transportation has gained a remarkable importance. This study is motivated by the lack of choosing short and safety
routes. Transportation of fuel product, money, weapon and ammunition can be term valuable material transportation. In this study a multiobjective mixed integer model is established. As a case study, some
parts of Erzincan (Turkey) are selected and network was created. Data
which are received from geographical information system are coded to
GAMS. Finally routes are found for different level of valuable products.
HD-28
Thursday, 14:00-15:30 - Room 130
MINLP for Natural Gas Network
Optimization
Stream: Mixed-Integer Nonlinear Programming
Invited session
Chair: Jesco Humpola
3 - Topology Planning of Gas Transport Networks
Ralf Lenz, Benjamin Hiller, Jesco Humpola, Thorsten Koch,
Robert Schwarz, Jonas Schweiger
Gas transportation companies frequently need to extend their networks
in order to enable feasible operations. In this talk, we present a heuristic procedure that tackles this topology planning problem in a two step
approach. At first we propose different methods to derive a set of possible network extensions. Common methods in practice are to build
new pipes, e.g., in parallel to existing ones or new active network elements. In a second step, the problem of finding a cost-minimal subset
of the extension set that enable feasible gas operations results in the
formulation of an MINLP model.
HD-29
Thursday, 14:00-15:30 - Room 011
Distribution and Transportation in the
Petrochemical Sector
Stream: OR in Petrochemicals and Mining
Invited session
Chair: Vikas Goel
1 - Balancing Chemical Production Networks by Railway
Transports
Thomas Kirschstein, Christian Bierwirth
Chemical production networks consist of multiple integrated chemical production sites where a multitude of chemicals is processed. The
chemicals handled at a particular production site are often disbalanced.
These disbalances can be reduced by inter-site transports of the relevant chemicals. In this talk a distribution planning model for balancing chemical production networks by rail transports is presented. The
model allows determining distribution plans using chemical rail cars
such that chemical stocks are balanced. The application of the model
is illustrated by a real-world case study.
2 - Modeling, Simulation and Optimization of an Oil Polluted Water Pumping Process in Open Sea
Benjamin Ivorra, Susana Gomez, Roland Glowinski, Angel
Manuel Ramos
Oil spill contamination in open sea has caused some of the major environmental disasters. One of the cleaning techniques for these hazards
is the use of skimmer ships (e.g., our partner: www.novetec.es). In this
work, we are interested in improving this process. To do so, we first
introduce a model to simulate the effect on the evolution of a given
oil spill due to natural and pumping effects. Then, for some realistic
cases, we optimize the trajectory of a skimmer in order to minimize the
amount of pollutant after a fixed time. To do so, we use novel hybrid
global optimization methods.
1 - Capacity Planning for Natural Gas Transmission Networks
Jesco Humpola
3 - Production Analysis and Operations Research at Noble Energy
Wesley Dyk, Alexander Engau
We present a procedure for capacity planning of large-scale real-world
distribution networks. It decides which combination of network extensions such as additional pipelines, compressors or valves should be
added to increase the network’s capacity or enhance its operational
flexibility. We formulate this as a nonlinear mixed-integer problem.
For its solution we use a combination of linear outer approximation
and NLP solution techniques. We formulate capacity inequalities (or
cutting planes) which reduce the overall solution time when added to
the formulation and describe a primal heuristic.
Noble Energy, Inc. is a global energy producer with offshore and
US domestic onshore operations. To achieve optimal returns at maximum safety, the company develops and will use state-of-the-art analytic tools using linear, nonlinear, and global optimization. In this
presentation, we first take a look at current research of production facility operations and decision-making for scheduling, crude sales and
inventory. We also address our ongoing plans to extend models and
methods to more general problems across company operations.
2 - Bilevel Optimization in Pipeline Transport Planning
Robert Schwarz, Benjamin Hiller, Claudia Stangl
Gas network operators are faced with the task of transporting gas
through a network of pipelines. Active components such as valves,
compressors and regulators are used to control the flow of gas and
sustain feasible operation. Operators may also request to change the
supply distribution at entries through contractual means. The suppliers
then react in the manner of a Stackelberg game, which is modeled as a
bilevel optimization problem. This model extends an MINLP formulation of the feasibility problem for stationary gas transport. Preliminary
computational results are presented.
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4 - Simultaneous Production and Distribution of Industrial Gas Supply Chains
Pierre-Marie Valton, Jean André, Ignacio Grossmann
We describe a multi-period mixed-integer linear program to minimize
cost of production and distribution of liquid products in industrial gas
operations for coordinating production decisions at multiple plants and
distribution decisions at multiple depots. Production decisions include
production modes and rates that determine power consumption. Distribution decisions involve the source, destination, quantity, route, and
time of each truck delivery. Results show that significant benefits exist
with higher coordination among plants/depots to fulfill a common set
of shared customer demands.
IFORS 2014 - Barcelona
HD-30
Thursday, 14:00-15:30 - Room 012
Dynamical Systems and Game Theory
Stream: Applications of Dynamical Models
Invited session
Chair: Alberto Pinto
Chair: João Almeida
Chair: Bruno M.P. M. Oliveira
1 - Cournot Duopolies with R&D Investment
Bruno M.P. M. Oliveira, Joana Becker, Alberto Pinto
We analyse a duopolistic Cournot competition model, where both firms
can invest to reduce their production costs. We study an R&D investment function inspired in the logistic equation. We do a full characterization of the associated game and study the short and long term
economical effects derived from using this new R&D investment function. For high production costs, that can correspond to the production
of new technologies, the long term economical effects are very sensitive to small changes in the efficiency of the R&D programs.
2 - Dynamic Management Model of Small Work Groups
Liliya Mukhamedrakhimova, Ilmira Gerasimova
We consider the problem of small work groups management, namely
the problems of its functioning improvement and ensuring the work
rhythm. For solving these problems, we develop cognitive dynamic
models of small work group based on linear and nonlinear relationships. Through computer simulations, the rate and sustainability of
the activity process of small work groups are evaluated, control algorithms are produced, and required rate of activity is obtained. Each
group member is considered as a system capable for self-regulation
and self-organization.
3 - Nonlinear Model Predictive Control of a Renewable
Resource
Lotfi Tadj, Messaoud Bounkhel
Optimal control theory has been extensively used to determine the optimal harvesting policy for renewable resources such as fish stocks. Not
only in the basic model and its extensions, but also in more integrated
models which involve two or more species, structured models, a population of consumers, predator-prey models, reserve-unreserve areas,
etc. Our intention in this paper is to use a different approach, model
predictive control (MPC). MPC is an advanced method of process control that has been successfully used in the process industries, especially
in chemical processes.
4 - Dynamic Model of a Multi-Product Manufacturing
System
Juliana Keiko Sagawa, Marcelo Nagano
A dynamic model for the production control of multi-product manufacturing systems was developed using Control Theory and System
Dynamics tools. The model was applied to depict the dynamics of a
real job shop production system of propylene bags. The control objective is to adjust the processing frequency of the machines to attend
the demands of the products while keeping the work in process at the
desired levels. The simulation results showed that the system could be
successfully controlled. No similar model suitable to a multi-product
system has been previously reported in the literature.
HD-32
1 - Scheduling Wireless Networks: The Advantage of
Co-operation
Celia Glass
Wireless Networks provide low cost internet access, but have severe
scheduling restrictions. On the one hand data is transmitted as packets providing unit processing times, on the other hand the access nodes
cannot multi-task. Transmission is organised along a tree network with
periodic local schedules, as periodicity provides reliability of service
and energy saving. We present heuristics for co-ordinating transmissions across the network, and an optimal global perfect periodic solution, and then compare results to demonstrate the advantage of coordinated periodicities at the access nodes.
2 - Incremental Network Design for Maximum Flows
Thomas Kalinowski, Dmytro Matsypura, Martin Savelsbergh
Many real world networks are constructed over significant time periods, and often the performance of intermediate stages is an important
objective, in addition to the quality of the ultimate network. We propose a class of problems combining network design and scheduling
decisions, where the network is constructed over time, subject to resource and budget constraints, and the objective is the cumulative performance. We focus on the case where the underlying quality measure
is the max flow value, and discuss some complexity results, heuristics,
and approximation algorithms.
3 - A Branch-and-Price Algorithm for Communication
Systems with High Error Correction Capability
Banu Kabakulak, Z. Caner Taşkın, Ali Emre Pusane
Channel coding aims to minimize errors which occur during the transmission of digital information from one place to another. Low-density
parity-check (LDPC) codes add redundant bits to the original data to
improve error correction capability. In practice, heuristic iterative decoding algorithms are used to decode received message. However,
these algorithms may fail to decode if received message contains errors. We formulate the optimal decoding problem as an integer programming problem and propose a branch-and-price method for its solution.
4 - Forwarding Strategies for Congestion Control in Intermittently Connected Networks
Marcello Sanguineti, Marco Cello, Giorgio Gnecco, Mario
Marchese
An analytical framework is proposed to study node-buffer occupancy
in Intermittently Connected Networks (ICNs), where “universal connectivity” and “global information” lack. A relationship is derived in
the z domain between the discrete probability densities of the buffer
state occupancies and the sizes of the arriving bulks. Two classes of
forwarding strategies are studied and simulated. The results can be exploited for buffer dimensioning and to derive upper bounds on various
performance metrics (e.g., loss probability and average buffer occupancy or time to destination).
HD-32
Thursday, 14:00-15:30 - Room 014
Supply Chain Management - Supply and
Ressource Planning
Stream: Production Management & Supply Chain
Management
Contributed session
Chair: Pedro Martins
HD-31
Thursday, 14:00-15:30 - Room 013
Scheduling and Queuing in Networks
Stream: Telecommunications and Networks
Invited session
Chair: Marcello Sanguineti
1 - Does Punishment Work? On the Value of Buyer’s
Commitment in Supplier’s Dynamic Improvement
Morteza Pourakbar, Mohammad Nikoofal, Saied Samiedaluie,
Mehmet Gumus
There are strong empirical evidences that the stability in buyer-supplier
relationship significantly influences supplier commitment to improve
its reliability. We allow the supplier to gradually improve its reliability by investing in process improvement through offering punishment
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IFORS 2014 - Barcelona
and commitment contracts. Contrary to the previous studies, our analysis reveals that punishment contract is more effective to incentivize
supplier to improve its reliability. We then solve for the buyer’s optimal regime, and show that it mainly depends on the cost of process
improvement and outside option price.
2 - Design of the Field Study about the Criteria used in
Supplier Selection
Joan Ignasi Moliné, Anna M. Coves
With the aim of contrasting the recently published literature dealing
with the criteria used in supplier selection with that actually used by
companies, a questionnaire has been designed in order to carry out a
field study. This has been sent to the purchasing professionals collective Aerce (Association of professional purchasers, contractors and
suppliers in Spain). The present article describes and develops the
methodology used in the design and diffusion of the questionnaire,
as well as advancing some early conclusions based on the responses
obtained.
3 - Supply Management of a Commodity Processor
Zhong Chen
In this paper, we study an agricultural commodity processor’s optimal
policy when it sources its input from spot market and contract market.
The processor also sells its processed output in another commodity
market. While contracted inputs provide a better homogeneous quality which benefits the processor, it also reduces transaction costs for
the farmers. In an environment where both input and output commodity prices are stochastic and correlated, we study optimal operational
decisions of the processor in terms of ordering, procurement and processing.
4 - Workforce Planning and Financing on a Production/Capital Discrete-Time Model
Pedro Martins, Ana Paula Quelhas
Current day’s financial crisis is imposing new challenges for small and
medium sized companies, namely in the production sector. The decisions on how to manage cash-flows in order to combine production and
workforce together with the financial commitments of the company
are becoming increasingly complex and harder to adjust. We model
the three processes (production, workforce and cash-flows) in a single
framework, resorting to a discrete-time formulation. We also incorporate new strategies for financing labor, using a sequence of flexible
short-term loans. We discuss applications.
We present a system that is able to generate hybrid metaheuristics
by combining elements from metaheuristics such as variable neighborhood search, iterated local search, tabu search, simulated annealing, etc.. The proposed system is composed of two parts: a generative grammar that allows instantiating arbitrary combinations of their
components, and a method to generate a parameter description from
a grammar description, which allows us to apply automatic configuration methods. We have applied this approach to several combinatorial
optimization problems.
3 - Adaptation of Meta-heuristic Algorithms to Dynamic
Problems
Özcan Aytaç
In this study, we investigated updating of algorithm parameters depend
to problem structure during solution process. The effects of this approach to solution has been discussed. Genetic, particle swarm and
simulate annealing algorithms are considered in this study. We aim to
get better performance of meta-heuristic algorithms in dynamic environment.
4 - Genetic Algorithm Parameter Optimisation for Multiprocessor Task Scheduling using Design of Experiments
Sunita Dhingra, Ashwani Kumar Dhingra
The present work considers the designing of optimal parameters of
genetic algorithm for the multiprocessor task scheduling algorithm
such that minimum total execution time is achieved. The different
experiments using different parameters of genetic algorithm such as
crossover, crossover rate, selection etc. have been conducted for the
well known problem of Gauss elimination with 18 tasks and 4 processors with variable communication cost. From the analysis, optimal
parameters of genetic algorithm have been reported for the effective
solution of multiprocessor task scheduling problem.
HD-34
Thursday, 14:00-15:30 - Room 016
Financial Modeling 3
Stream: Decision Making Modeling and Risk Assessment in the Financial Sector
Invited session
HD-33
Thursday, 14:00-15:30 - Room 015
Algorithm Configuration: Black, White
and Gray Box
Stream: Hyperheuristics
Invited session
Chair: Patrick De Causmaecker
1 - Algorithm Configuration: Black, White and Gray Box
Patrick De Causmaecker, Nguyen Thi Thanh Dang
The task of automated (off-line) algorithm configuration includes finding a good parameter configuration for an algorithm based on some
performance measure and a problem instance distribution. This could
be considered as an expensive optimization problem. Currently, most
algorithms treat the target (configured) algorithm as a black-box, i.e.,
only the final result of each run of the target algorithm on a problem
instance is taken into account. If we "open the box", we could have a
gray-box or even a white-box configuration problem. We study conditions, features and techniques.
2 - Automatic Design of Metaheuristics from a Grammar
Description
Franco Mascia, Manuel López-Ibáñez, Marie-Éléonore
Marmion, Thomas Stützle
200
Chair: Josef Arlt
1 - Are there Gender Differences in Consumer Credit
Risk?
Galina Andreeva, Anna Matuszyk
The presentation analyzes gender differences in risk profiles in consumer credit. Gender is not normally used in credit risk assessment
due to legal and ethical considerations. It can be argued that gender removal leads to reduced predictive power of scoring models and lower
availability of credit for women, yet there is no definitive answer as
whether this is the case. Based on a unique proprietary dataset and on
a standard credit scoring methodology, the analysis provides insights
into potential role of gender in credit-granting environment.
2 - Estimate Aggregated Default: An Impirical Investigation on Brazilian Loans using Cointegration Vectors
Angela De Moraes, Galina Andreeva, Jonathan Crook
Brazil has experienced a robust expansion in consumer credit during
the last decade which raises concerns about the increase of vulnerabilities in the household sector. The purpose of this study is to develop
econometric models to predict the behaviour of the aggregate delinquency in Brazilian consumer loans. The model consists in testing
cointegrating relationships and then estimating a short run error correction model. The results based on monthly data from 2000 to 2012
show that the delinquency rate is particularly sensitive to shocks on
GDP and to the variation of workers’ income.
IFORS 2014 - Barcelona
3 - Modelling of Yearly Inflation Rate
Josef Arlt, Marketa Arltova
Inflation rate is a important macroeconomic indicator, which plays a
crucial role in monetary policy. The yearly inflation rate is not the appropriate measure of inflation. The spectral time series analysis shows
that it delays the information with respect to the monthly and annualized inflation rate about six months. This conclusion leads to the
proposal of a new nontraditional method for the yearly inflation rate
forecasting. This paper was written with the support of the Czech Science Foundation project No. P402/12/G097 DYME - Dynamic Models
in Economics.
4 - Standard & Poor’s Framework for Rating Banks
Mohamed Damak, Luigi Motti, Enrique de la Riva
This presentation covers Standard and Poor’s Ratings Services’
methodologies and criteria for rating banks. During the session, we
will articulate the steps we follow to determine the stand-alone credit
profile (SACP) and the issuer credit rating (ICR) for a bank, including
the consideration for additional direct support from the bank’s parent
group or sovereign government. We will also explain how, under our
methodology, systemic risks, including economic and industry risk,
can directly affect our view of individual banks’ creditworthiness.
HD-36
4 - Multistage Stochastic Model of Fuel Procurement for
Electric Generation with Logistic and Commercial
Constraints
Carlos Testuri, Bernardo Zimberg
In order to satisfy uncertain demand, fuels are acquired as discrete size
volume cargos under contract regulation, usually two months before
the arrival of the product. In the meantime, changes in demand determine extra costs such as delay or cancellation of cargos due to capacity
constraints. The multistage stochastic model depicts decisions on acquisition, delay and cancellation of discrete size volume cargos of fuel
at minimum expected cost, subject to uncertain demand, production
and stock constraints, contract regulation, material balance, and logistic and commercial constraints.
HD-36
Thursday, 14:00-15:30 - Room 132
Supply Chain in Agriculture
Stream: OR in Agriculture, Forestry and Fisheries
Invited session
HD-35
Thursday, 14:00-15:30 - Room 131
Simulation and Optimization for Robust
Supply Networks
Stream: Stochastic Modeling and Simulation in Engineering, Management and Science
Invited session
Chair:
Chair:
Chair:
Chair:
Erik Kropat
Silja Meyer-Nieberg
Ozlem Defterli
Jens Baudach
1 - Linking Mathematical Optimization and Stochastic
Simulation for Planning of Transshipment Terminals
in the Parcel Delivery Industry
Jens Baudach, Uwe Clausen, Daniel Diekmann
Mathematical optimization and discrete-event simulation represent
two powerful methods with different but complementary advantages.
However, both are mainly applied separately for logistical problems so
far. Planning parcel transshipment terminals contains a large number
of decisions, such as (un)loading dock or sorting destination assignments, as well as the consideration of complex automatic sorting systems and manual handling activities with lots of stochastic elements.
Therefore, we will present a new planning approach that closely links
optimization and simulation in an iterative way.
2 - Simulation based Study for Robust Supply Network
Design
Partha Datta, Pallab Dutta
Chair: LluisM Pla
1 - A Hierarchical Markov Decision Process Modelling
Feeding and Marketing Decisions of Growing Pigs
Reza Pourmoayed, Lars Relund Nielsen, Anders Ringgaard
Kristensen
Feeding is the most important cost in the production of growing/finishing pigs that has a direct impact on the marketing decisions
(decisions concerning when to slaughter) and the final quality of the
meat. In this paper, a hierarchical Markov decision process (HMDP)
is considered to model the feeding and marketing decisions simultaneously. The model finds the optimal decisions given the current state of
the pen. The state of the system is updated using a Bayesian approach
based on on-line data obtained from a set of sensors in pen and finally
the HMDP is tested on a set of numerical examples.
2 - Multi-Stage Model for a Real Instance in a Pig Production System
Esteve Nadal, LluisM Pla
The paper presents a two-stage stochastic model to optimize the pig
production system in a multi-site instance. The model maximizes the
benefit calculated from the incomes of the animals and the production
costs over the time horizon considered. It provides a schedule of transfers between farms, occupancy and trucks involved. The model uses
integer variables, but it is far to find an optimal solution due the time
spent. A further analysis has been done by relaxing the integrity of the
variables and studying the model behavior when parameters affecting
to the execution’s time are modified.
3 - Can Organic Agriculture Feed Turkey?: A Linear Programming Approach
Bulut Aslan, A. Yonca Demir
Studies on disruption are becoming even more relevant and important
as supply chains are becoming more globalised with companies sourcing materials from far-off sources. In this paper, design characteristics
of supply chains have been considered and their correlation with severity of disruption in the supply chains have been analysed employing a
simulation modelling method.
Conventional agriculture is a large-scale, monoculture intervention to
ecology requiring the use of agrochemicals having harmful effects on
natural resources, health and biodiversity. Organic farming can be a
solution to dissolve these problems of economy and ecology. In this
paper, we propose a linear programming model to study the viability
of organic farming in Turkey’s case. It aims to show that when all
agricultural resources are used for organic farming, the throughput can
still feed the population, surplus can be produced, endemicity and biodiversity can be retained.
3 - Shipment Transport via Transfer Ports: A Stochastic
Programming Approach
Yer Van Hui, Andy Lee
4 - An Optimization Model for Planning Fruits Transport
from Cold Storages to Packing Plants
Marcela Gonzalez-Araya, Wladimir E. Soto-Silva, LluisM Pla
This paper addresses the shipment planning problem with random processing times in intermodal logistics. Shipment activities are divided
into two groups according to regional settings. Activity processing
times in stage one are assumed to be random while those in stage two
are deterministic. In case a shipment delay is observed, an in-process
adjustment is implemented to reduce costs. We establish a two-stage
stochastic programming model using an integrated scenario generation
approach. An illustrative example with industry data is presented.
An important issue in the fruits supply chain is related to the kind of
storage where the fruits are kept and the transport used to carry them
to packing plants. In this work, an optimization model for supporting
fruits transport planning from cold storages to packing plants, aiming
to minimize opening costs of cold storages and transport costs is proposed. The model considers constraints about plants fruits demand,
plants capacity and stored fruits quantities. This model is applied to a
real case from a packing plant located at Region of Maule, Chile.
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HD-37
IFORS 2014 - Barcelona
HD-37
Thursday, 14:00-15:30 - Room 017
Advances on Recovery Inventory
Management Policies I
Stream: Recovery Inventory Management Policies
Invited session
Chair: Nihat Öner
Chair: Qi Fu
1 - Structuring Investment Decisions for Smart City
Transitions
Katharina Burger, Mike Yearworth, Leroy White
The study addresses the challenge of designing participatory decision
making processes for smart city transitions. A process combining Delphi and ANP was developed to engage stakeholders in the process
of prioritizing areas for investment and structuring delivery organizations. The study shows the impacts of converging IT systems and
infrastructures, local government and workplace structures. The interdisciplinary research contributes to current debates on soft OR with its
multi-method multi-paradigm approach and provides empirical contributions to studies of governance in smart cities.
1 - A Co-evolutionary Network Design Method for Strategic Alliance in Express Delivery Services
Kap Hwan Kim, Friska Natalia Ferdinand, Chang Seong Ko,
Ki Ho Chung
2 - Action Research using Soft Systems Methodology:
Exploring Alternative Intervention Modes
Giles Hindle
This study addresses small-sized express delivery service companies
suffering from their low demand service centers and suggests optimal strategic alliance models to overcome their difficulties: merging
service centers, opening/closing terminals, and also sharing consolidation terminals. The proposed approach allows an independent decision making process under the strategic alliance by each company. A
co-evolutionary genetic algorithm is developed, which may be implemented under a distributed decision-making scenario.
Soft Systems Methodology (SSM) is an approach to tackling messy,
ill-structured problems. Drawing on both the author’s own Action Research programme and a review of the existing literature, a taxonomy
of intervention modes for SSM is presented. The taxonomy includes
modes such as organisational project, individual sense making, qualitative research and executive coaching. Reference is also made to a
spectrum of consulting approaches from participative to expert.
2 - Optimization of Route Planning and Cost Allocation
in Truckload Shipper Collaboration
Nihat Öner, Gultekin Kuyzu
Truckload shipper collaboration is an example of horizontal collaboration in supply chain management. In truckload shipper collaboration, a
group of shippers purchasing the services of carriers come together and
jointly negotiate with carriers for better rates. Identifying the minimum
cost collaborative solution and allocating the calculated minimum cost
are typically treated as two successive but distinct phases. In this study,
we develop a new integrated optimization approach with the objective
of calculating the minimum cost collaborative solution which has a
good cost allocation.
3 - Coordinated Dynamic Pricing and Inventory Management for Perishable Products with Time-Dependent
Demand
Onur Kaya, Sajjad Rahimi Ghahroodi
We focus on the pricing and inventory decisions for perishable products in a stochastic setting in which the demand rate is affected with not
only the prices of the products but also with the freshness of the products. We model this problem through a dynamic programming formulation and determine the optimal inventory and pricing decisions. We
prove certain characteristics of the optimal solution and also analyze
the effect of different parameters on the optimal solution. This work is
supported by Tubitak grant #111M533.
4 - Evaluating the Effectiveness of Alternative Pricing
Policies for the Water Utility Sector under Uncertainty
Nurcan Demirok Donmez, Nahit Serarslan
In this study, we focus on the water utility sector because of the value
water has as a natural resource. By the effect of climate changes (e.g.,
global warming), the water reserves are reduced and for many cities,
use of water reserves may become an important issue. In order to use
this scarce resource more efficiently, different mark up or mark down
policies for pricing can be considered. For this reason, the policies
of an important municipal water distribution authority are evaluated
statistically and new policies are proposed to find some new solution
alternatives.
HD-38
Thursday, 14:00-15:30 - Room 214
Soft OR / Systems and Multimethodology
2
Stream: Soft OR / Systems and Multimethodology
Invited session
Chair: Giles Hindle
202
3 - Emerging Findings from a Review of an Intervention
Using the Lean Systems Methodology
Gavin Betts
This research seeks to evaluate the Vanguard Methodology. Used and
developed by Vanguard Consulting over thirty years, it has been labelled ’lean systems methodology’ in the literature. This methodology
is claimed to bring about improvements in service whilst also reducing
costs. The emerging findings from a case study in which this approach
was employed will be discussed.
HD-39
Thursday, 14:00-15:30 - Room 018
Advances in Discrete and Global
Optimization and on Graphs I
Stream: Discrete and Global Optimization
Invited session
Chair: Gerhard-Wilhelm Weber
Chair: Joao Lauro D. Faco’
Chair: José Paixão
1 - Optimal Regular Covering of the Plane with Equal
Sectors
Adil Erzin, Natalia Shabelnikova
In the regular cover, the area split into equal regular polygons, and all
the polygons are covered equally. In the paper a polygon is an equilateral triangle. We propose the new regular plane coverage models
with equal sectors in which the number of sectors per unit area is minimum. Such problem is closely related to the problem of finding the
least dense cover, but does not coincide with it due to the restrictions
on the sector’s parameters. We have found the optimum number of
sectors covering one tile in a special case.
2 - On the Class of (k, l) Partition Graphs
Hayat Issaadi
Partitioning the vertices of a graph is a problem that has generated
much interest, particularly when the partition is into l cliques and k
stable sets. This class of graph called (k, l) partition graphs was introduced by Branstadt in 1996. In our study we present all subclasses
relating to this class of graphs, which have been studied in recent years.
Moreover we present some results on a generalization of this class of
graphs.
IFORS 2014 - Barcelona
3 - On (a,d)-Antimagic Labelings of Generalized Petersen Graphs P(n,3)
Lingqi Zhao
A connected graph G = (V,E) is said to be (a d)-antimagic if there exist positive integers a, d and a bijection f of E to the set containing
1,2,...,|E|, such that the induced mapping gf from V to V, where gf(v)
is defined as the sum of f(uv) with respect to all uv in E(G), is injective
and gf(V) is the set containing a, (a+d),..., (a+(|V |1)d). In this paper,
we show that the generalized Petersen graph P(n,3) is ((5n+5)/2,2)antimagic for odd n greater or equal 7.
HD-40
Thursday, 14:00-15:30 - Room 019
Prescriptive Analytics: Smart Solutions to
Real-World Problems I
Stream: Meta-Analytics: A Marriage of Metaheuristics
and Analytics
Invited session
Chair: Stefan Voss
Chair: Stefan Lessmann
1 - Car Resale Price Prediction with Ensemble Selection
and Asymmetric Cost Functions
Stefan Lessmann, Hsin-Vonn Seow
Resale price prediction is important to inform decision making in the
used car business. We develop a prediction model that integrates the
principles of ensemble selection and asymmetric cost of error functions. This allows us to create prediction models that account for the
economic consequences of forecast errors, and avoid the more costly
errors type in particular. Empirical experiments on real-world data suggest that the new approach produces more accurate forecasts, is better
aligned with application requirements, and offers better decision support.
2 - Functional Principal Component Analysis in Revenue Management Data
Claus Gwiggner, Catherine Cleophas
One part of revenue management is to infer similarities between markets from observed customer behaviour. The underlying observations
are often high-dimensional and partly ordered in time. We performed
cluster and functional principal component analysis of revenue management (RM) booking data. Our results allow to manually complement automated RM systems and to improve the underlying forecasting components.
3 - An Empirical Comparison of Classification Algorithms for Mortgage Default Prediction: Evidence
from a Distressed Mortgage Market
Trevor Fitzpatrick, Christophe Mues
This paper evaluates the performance of a number of modelling approaches for future mortgage arrears status over a 12-month horizon.
Boosted regression trees, random forests, linear and semi-parametric
logistic regression models are applied to over 300,000 Irish owner occupier mortgages. The results indicate that the selected approaches
have varying degrees of predictive power and that boosted regression
trees outperform logistic regression. The findings suggest that boosted
regression trees can be useful additions to the current toolkit for credit
risk assessment for banks and regulators.
4 - Discrete Cyber Swarm Algorithm and Analytics
Strategies for the Quadratic Assignment Problem
Peng-Yeng Yin, Fred Glover, Shun-Chieh Yang
Quadratic assignment problem (QAP) includes the widely known traveling salesman problem (TSP) as a special case, but is considered much
harder than the TSP. A survey disclosed that many best QAP algorithms use multiple metaheuristics and include tabu search as a fundamental part. Yin et al. (2010) have developed the cyber swarm
algorithm (CSA) which shows the advantages of particle swarm optimization that incorporates tabu search principles. This talk presents a
discrete CSA for the QAP by showing the benefit of incorporating the
analytics strategies.
HD-42
HD-41
Thursday, 14:00-15:30 - Room 216
Stochastic Models in Production,
Manufacturing and Services
Stream: Stochastic Models for Service Operations
Invited session
Chair: Maria Elena Bruni
1 - Service Levels in Inventory Management
Stefan Minner
Many inventory control models optimize stock levels subject to service level constraints. One shortcoming of these measures and the way
they are applied is the use of expected values. As a consequence, performance measured empirically and for a given finite time horizon will
deviate from prescribed levels derived under steady-state conditions.
Further, there exist inconsistencies between certain types of service
measure and the materials flow assumptions. The paper provides analytical expressions for service levels and a numerical study to show the
potential for improvement.
2 - A Constraint Programming Approach for Computing
Robust Sequences of Tasks in Stochastic Scheduling
Jerome Rogerie, Philippe Laborie
Stochastic scheduling often involves computing robust sequences of
tasks on unary resources. In this context, Stochastic Programming usually consists of a two-stage formulation where sequencing decisions
are part of the first stage whereas tasks start time are fixed online in the
second stage. Scenario-based approaches benefit from high-level concepts to state that on each resource the same sequence is used across
all scenarios. We present the sequence variable and same-sequence
constraint introduced in CP Optimizer and show how they are used to
model and solve these stochastic problems.
3 - Managing Uncertainties in Hardware-Software Codesign Projects
Jones Albuquerque, Jordi Ferrer-Savall, Silvana Bocanegra,
Tiago Ferreira, Daniel Lopez-Codina, Claudionor Coelho Jr
This work presents a system-level methodology for managing and partitioning HW/SW codesign projects in presence of uncertainty at conceptual level. It uses a Stochastic Integer Linear Programming (SILP)
formulation to cast the partitioning problem of objects into technologies subject to team factors, risk analysis, execution and development
constraints. It also proposes an approximation to solve the SILP problem. This approximation is based on design scenarios in order to make
the problem computationally feasible. Results when applied in a real
project are also presented.
4 - Dynamic Pricing, Production, and Channel Coordination with Stochastic Learning
Suresh Sethi, Tao Li
We consider a two-period supply chain in which a manufacturer produces a product with benefits of cost learning, and sells it via a retailer
facing a price-dependent demand. The second-period production cost
declines linearly in the first-period production with a random learning
rate. We examine how mean and variance of the learning rate impacts
pricing, production and ordering decisions of the channel members.
We show that increases in the mean or variance of the learning rate
worsen the double marginalization problem. We find revenue sharing
contracts to coordinate the dynamic supply chain.
HD-42
Thursday, 14:00-15:30 - Room 215
Collaborative Decision Making (Social
Networks & Web Resources)
Stream: Decision Support Systems
Invited session
Chair: Adiel Teixeira de Almeida
Chair: Fatima Dargam
203
HD-43
IFORS 2014 - Barcelona
1 - Online Multidisciplinary Information Management
Software
Haris Doukas, Ilias Papastamatiou, George Mavrotas, John
Psarras
The Online Multidisciplinary Information Management Software
(OMIMS) is a decision support tool that offers a flexible, reliable
and transparent way to solve decision making problems using multidisciplinary data sources. The OMIMS transforms information into
2-tuples (Herrera et al.) and presents the solution to the user using
graphical methods. The algorithm’s implementation follows an objectoriented approach, giving the user the ability to store, edit, review or
discard problems. OMIMS is developed using open source programming languages. Multiple users can also work on shared problems.
2 - IT Service Selection in Cloud Computing — An Evaluation of Multiciteria Decsion Model Approaches
Holger Schrödl
The optimal selection of IT Services is of vital interest for industrial
practice. From an Information Systems perspective, frameworks are
provided to support this challenge. Most of these frameworks consist
of a set of relevant decision criteria, but there is a lack of research on
the question how to apply these criteria-based frameworks to model a
particular decision model. First, the authors describe several IT service
selection frameworks and transform them into appropriate MCDM formulations. Second, these MCDM formulations are evaluated with respect to their usefulness for industry.
3 - Exploring the multi-channel consumer decisionmaking journey
Sahar Karimi, K. Nadia Papamichail, Christopher Holland
Prior research has focused on consumers’ channel switching behavior;
however our current knowledge of multi-channel purchase processes is
limited. This research examines consumers’ choice of channel in each
stage of the decision making process. A conceptual model considering
the perceived value of each channel at all the stages is presented. A
mixed method research is designed including interviews and Internet
panel data. The result informs the current literature on multi-channel
purchase and provides guideline for retailers struggling to effectively
allocate sources to different channels.
4 - Multi-criteria Spatial Decision Making and Determining Location Score based on Geographic Zone with
GIS
Ceren Erdin Gundogdu
Criteria of choosing location are mainly spatial. Contemporary studies
confirm that determining location on GIS, which integrates geographical data and semantic data, is rational and more accurate. This study offers multi-criteria decision making conditions and models unique to a
particular type of business, which is a large scale enterprise, for choosing location in a country and geographic zone based on "Life Quality
Research" and "Socio-Economic Development Order of Cities and Regions" data.
HD-43
Thursday, 14:00-15:30 - Room 217
Medical Informatics
Stream: Optimisation in Health Care
Invited session
Chair: Adem Tüzemen
2 - Using GIS in Biology
Ceren Yağci, Ahmet Duran, Savas Durduran, Murat Sanda
The investigation of the biological structure of the plants in the nature,
their spatial distribution has great importance for the investigations. In
such kind of a studies GIS provides support to these applications for
solving their problems and achieving their objectives. The natural plant
taxa spread on Akseki (Antalya-Turkey) were detected by GIS method.
Their relationship with habitat was investigated by the help of spatial
analysis. The phytogeographical distribution, systematic features and
life form of plant demonstrated in maps and provided accuracy.
3 - Optimizing Automated Medical Dispensing Cabinets
through Voice of Customer
Jülide Nallioğlu, Sabri Erdem
As it is known, the pharmaceutical and medical supplies used in the
health sector have significant costs due to their material values. Also
some negative situations such as lost, reduced and expired supplies can
be seen very often and this makes the case management of stock; therefore material planning is difficult. In this study, our goal is to provide
redesigning the cabinets in the modular system in a more controlled
and systematic manner in terms of the data gained by observations and
customers’ needs.
4 - Design of a New Appointment System Using Bill of
Operation Case (BOC)
Adem Tüzemen, Şevkinaz Gümüşoğlu, Güzin Özdağoğlu
Surgical operating rooms are one of the most important decision centers in hospitals. Planning of these rooms are affected by many factors,
i.e., number of rooms, surgeons materials and equipment, patient bed
capacity, intensive care unit. This study focuses on inventory management for operating rooms and introduces a "bill of operation case"
(BOC) model for efficient use of materials in surgical operations. BOC
model is also supported with a new appointment information system
which can be customized by surgeons.
HD-44
Thursday, 14:00-15:30 - Room 218
Humanitarian Logistics, SCM Practices
and Sustainable Development
Stream: Quality and Performance Measurement in Humanitarian Relief Chains
Invited session
Chair: Sadia Samar Ali
Chair: Frank Meisel
1 - Ambulance Routing for Disaster Response with Patient Groups
Frank Meisel, Luca Talarico, Kenneth Sörensen
We consider a routing problem for ambulances in a disaster scenario.
The ambulances are used for serving two types of patients: slightly
injured persons who can be helped directly in the field and seriously
injured persons who have to be brought to hospitals. Two mathematical formulations and a Large Neighborhood Search metaheuristic are
proposed for minimizing the latest service completion time among the
people waiting for help. Our experiments show that the metaheuristic
produces near optimal solutions for a large number of test instances
within very short response time.
1 - Forecasting Negativity of BRCA1 / BRCA2 Genes for
High-Risk Breast Cancer Families
Şimal Aysever, Suzan Güreli, Fadime Üney-Yüksektepe,
Tülin Aktin
2 - A Production/Remanufacturing Inventory Model with
Multiple Recycled Components and Outsourcing Policy
Che-Fu Hsueh
The causes of breast cancer are classified into two groups as modifiable
and non-modifiable (genetic). Genetic risk factors for healthy individuals can be identified by BRCA1/BRCA2 gene tests which are costly
and time consuming. The negativity of the gene test implies absence
of non-modifiable breast cancer risk. In this study, past data of individuals who have undergone these tests will be obtained from Istanbul
University Oncology Institute, and data mining techniques will be used
to predict the test results beforehand. Thus, it is aimed to optimize the
incurred costs and required workforce.
A production/remanufacturing problem with multiple recycled components and outsourcing policy is considered. The remanufacturer purchases recycled components from the collector, and sells products after
production/remanufacturing. Remanufactured products are assumed to
be different from new products. Both the remanufacturer and the collector maximize their own profits. The equilibrium of the problem is
formulated as a variational inequality, in which products prices, production lot sizes, ordering quantities of components, and the costs to
stimulate return rates are determined.
204
IFORS 2014 - Barcelona
HD-45
3 - Performance Analysis of Quality Collaboration in the
Supply Chain
Hyun Jung Kim, Soo Wook Kim
4 - A Greedy Algorithm to Solve Large Equality Facilities
Location Problem
David Mauricio
The Korean Standards Association developed Quality Collaboration
Index for Supply Chain Management (QCI-SCM) for its ’Quality
Innovation-Based Building and Expansion of Business.’ This paper
analyses the performance difference of quality collaboration in the supply chain on the different types of supplier-buyer relationships, based
on the QCI-SCM survey results. The significance of this paper lies in
the analysis-based strategic direction it provides to promote supplierbuyer quality collaboration.
We introduce a greedy algorithm with computational low cost to solve
Large Facilities Layout Problem. The proposed algorithm iteratively
builds a solution, adds one facility to solution in the each iteration such
that its impact over facilities added is minimal, and this procedure is
repeats until all facilities are located. Numerical experiments on instance with up to 1000 facilities show that the proposed algorithm is
very fast and efficient.
4 - Performance Measures of Humanitarian Supply
Chain Network
Sadia Samar Ali
The humanitarian supply chain, a network of diverse players includes
military, Government, NGOs, Police, Aid agencies and Logistics service providers. The performance of a humanitarian supply chain is
measured in terms of lives saved. It must be agile to respond, designed
to move materials to the disaster hit areas to serve for those in need
in the shortest possible time and must possess the ability to return to
their original configuration.The supply chain agility and supply chain
resilience are two important determinants of the pre and post disaster
Supply Chain performance of this study.
HD-45
Thursday, 14:00-15:30 - Room 219
Location Problems
Stream: Hybrid Heuristics
Invited session
Chair: Gabor Nagy
1 - A Three-Stage Approach for Solving Large Unconditional and Conditional Vertex p-Centre Problems
Chandra Irawan, Said Salhi, Zvi Drezner
A three-stage approach is proposed for solving large unconditional and
conditional vertex p-centre problems. The first stage consists of some
aggregated problems which are then solved with an exact method to
produce promising facility sites. In the second stage, these promising facilities are used as potential facility sites for solving the p-centre
problem involving the original demand points by a VNS algorithm.
The obtained solution is then fed into the last stage where a VNS is
utilised to solve the original problem. The method is assessed on the
TSP dataset with competitive results.
2 - Adaptive Perturbation-Based Heuristics: An Application for the Continuous p-centre Problem
Abdalla Elshaikh, Said Salhi, Jack Brimberg, Nenad
Mladenovic, Gábor Nagy
A perturbation-based heuristic using both a gradual and a strong perturbation is proposed to solve the p-centre problem in the continuous
space. Efficient enhancements are proposed and a learning scheme is
embedded into the search. Empirical results, using several existing
data sets (TSP-Lib) with various values of p, show that our proposed
heuristics outperform both a multi-start heuristic and a discrete-based
optimal approach.
3 - The Partially Probabilistic Customer Choice Rule: A
New Competitive Location Model
Jose Fernandez, Juana López Redondo, Pilar M. Ortigosa,
Boglárka G.-Tóth
A chain wants to set up a single new facility in a planar market. In
the classical probabilistic (or Huff) model, a customer splits his/her
demand among all competing facilities according to their attractions.
We analyze this model versus the new partially probabilistic model,
in which a customer only patronizes those facilities for which he/she
feels at least a minimum level of attraction, and split his/her demand
among them proportionally to their attractions (determined by the customer’s view of the quality of the facility and its distance to it), through
a gravitational model.
205
HE-01
IFORS 2014 - Barcelona
Thursday, 16:00-17:30
HE-01
Thursday, 16:00-17:30 - Room 118
Scheduling and Rescheduling: Passenger
Focus
Stream: Railway and Metro Transportation
Invited session
Chair: Leo Kroon
1 - Ideal Train Timetabling Problem
Tomás Robenek, Jiang Hang Chen, Michel Bierlaire
1 - Practical Benchmarks for Location-Routing Decisions via Approximation Algorithms
Mozart Menezes, Vedat Verter
We aim in identifying opportunities for improvement in real-world
location-routing problems. Creating an approximation scheme for location and routing problems that is easy to implement, provides a reasonable good feasible solution, provides lower bounds on costs, and
provides procedures for adapting different real situations so the scheme
presented could be used. We present results discriminating measures
such as vehicles’ capacity utilization, technology, distance travelled,
and CO2 emissions.
2 - On Covering Location Problems on Networks with
Edge
Oded Berman, Jörg Kalcsics, Dmitry Krass
Given the recent changes in legislature allowing competitors in the railway industry, the current way of planning is not sufficient anymore.
The original planning is based on the accessibility/mobility concept
provided by one carrier, whereas the competitive market consists of
several carriers that are driven by the profit. And thus, we introduce
a definition of an ideal timetable and apply the scheduled delay concept (to cover the elasticity of the demand). The aim of the Ideal Train
Timetabling Problem (as MILP) is to minimize the passengers’ total
travel time (weighted by the demand).
Given that demand is distributed along the edges of a network we consider the Maximal Covering Location Problem and the obnoxious version where the coverage should be minimized subject to some distance
constraints between the facilities. We show that the finite dominating set for node covering problems does not carry over to the case of
edge demands. We present a solution approach for the single facility problem. Moreover, we discuss the multi-facility problem where
the demand is constant on each edge and present several discretization
results for tree networks.
2 - Shuttle Planning for Link Closures in Urban Public
Transport Networks
Evelien Van der Hurk, Nigel H.M. Wilson, Haris
Koutsopoulos, Leo Kroon, Gabor Maroti
3 - Partitioning a Graph into Connected Components
with Fixed Centers and Optimizing Different Criteria
Isabella Lari, Justo Puerto, Federica Ricca, Andrea Scozzari
Urban Public Transport Networks need to regularly close links in their
network for maintenance. These closures have significant effect on
the service provided to passengers. In practice, the effects of closures
are mitigated by replacing the link with a shuttle service. We present
an optimization-based approach for the link closure problem as a Line
Re-Planning problem. Our results show that using additional shuttles
routes significantly reduces delay over the standard solution, based on
the real life case of the Longfellow Bridge closure in the MBTA metro
network of Boston, USA.
3 - Controlling Passenger Flows in Networks
Marie Schmidt, Lisa Thom
Even if a public transportation system provides enough transportation
capacity in the long run, parts of it may be overcrowded, in particular
in peak hours. If transportation capacity cannot be increased on the
corresponding sections, an alternative way to avoid overcrowding is to
give passengers (financial) incentives to switch to less crowded connections. We investigate and compare different approaches to control
passenger flows in networks by modification of arc lengths and discuss
to what extent they could be used to control passenger flows in public
transportation systems.
4 - Minimization of Passengers’ Travel Time in Railway
Traffic Control
Dario Pacciarelli, Andrea D’Ariano, Francesco Corman,
Federico Sabene, Marcella Samà
This work addresses railway customer satisfaction by solving a joint
train scheduling and passenger delay management problem. A MILP
formulation is proposed and solved in exact and heuristic ways. The
heuristic approach iterates between two steps. First, the train scheduling problem is addressed with the minimization of a weighted train
delay, the weights being equal to the number of passengers per train.
Second, a passenger assignment problem is solved. Computational results on a Dutch practical case study show that the heuristic computes
good quality solutions within a short time.
Given a graph with n vertices, p of which are centers and n-p are units,
we consider the problem of finding a centered partition of the graph,
i.e., a partition into connected components each containing exactly one
center. For each pair unit-center, there is a fixed assigning cost to be
incurred if they belong to the same component. Basing on these costs,
we consider different objective functions. The obtained optimization
problems are NP-hard on general graphs, and we present efficient polynomial time algorithms for trees.
4 - Component Commonality: The p-Median Solution to
a Product Design Problem
Renato Guimaraes, Mozart Menezes
Component commonality is an important problem that permeates the
manufacturing industry. Serving multiple members of a product family
with a single component design reduces the amount of different SKUs
one has to manage with reduced inventory cost, allows achieving high
service level, but introduce inefficiencies. As it is common in supply chain management, making the right trade-offs allows the decision
maker to better manage the supply chain in terms of efficiency and responsiveness. We present a model for analyzing this trade-off that has
an underlying structure of a p-Median problem.
HE-04
Thursday, 16:00-17:30 - Room 119
O-D Estimation
Stream: Traffic Flow Theory and Traffic Control
Invited session
Chair: Hesham Rakha
1 - OD-Matrix Estimation Based on Plate Scanning
Alexander Krylatov, Victor Zakharov
HE-03
Thursday, 16:00-17:30 - Room 001
Discrete Location
Stream: Location
Invited session
Chair: Mozart Menezes
Chair: Oded Berman
206
The problem of OD-pairs reconstruction based on plate scanning technique is considered. Comparison of plate scanning (route identification) and traditional link count approaches is made. The greater informative potential of plate scanning method is demonstrated. In addition,
elements of path flow reconstruction and optimal plate scanning devices allocation are introduced. Original method of analysis of traffic
data gained from plate scanning devices is presented. The developed
method is illustrated by its application to the traffic network of SaintPetersburg city.
IFORS 2014 - Barcelona
2 - A Practical Proposal for Dynamic OD Matrix Estimation in Terms of a Bilevel Approach
Manuel Bullejos Gonzalez, Jaume Barceló, Lídia Montero
Traffic management applications have to be feeded with real-time demand matrices to efficiently find solutions in the short-term horizon.
OD matrices are estimated from historic or real-time data collection
and prior matrices. In this work, we present a simulation-optimization
bilevel-DUE approach for Dynamic OD matrix estimation, in which
the lower level is a dynamic user equilibrium problem solved by a
mesoscopic simulator. Time-sliced OD matrices generated off-line
with the former procedure are efficient initializations for the on-line
dynamic OD estimation methods based on Kalman filtering
3 - Information Provision for Passengers in Underground Railways Using Smart Card Data
Emily Digges La Touche, Nick Tyler
This project focuses on the London Underground network and the
Hong Kong MTR network as case studies, looking at the data produced from the automated ticketing systems. The data shows to be a
valuable source of information about the current conditions of the network for both operators and passengers. This information can lead to
passengers knowing optimal routes, a realistic travel time and the number of minutes a delay may cost them; when the delay may be caused
by congestion or service problems. Operationally this can allow for
delay statuses to be more realistic and dynamic to crowding.
4 - Estimation of Dynamic O-D Matrices using Synthetic
Time-Dependent Static O-D Estimators and Microscopic Traffic Simulation
Hesham Rakha, Hao Yang
The paper develops a dynamic Origin-Destination (O-D) estimator that
combines a maximum likelihood time-dependent static O-D estimator
with a dynamic traffic assignment and simulation software. The algorithm first estimates the time dependent O-D and then uses the microscopic simulator to create the dynamic O-D table while accounting for
the intricacies of vehicle-to-vehicle and vehicle-to-control interaction.
The algorithm is tested using a simulated network. The simulation results using the time-dependent static O-D table and the dynamic O-D
table are compared to field observations.
HE-05
Thursday, 16:00-17:30 - Room 002
Port Operations - Miscellaneous
Stream: Port Operations
Invited session
Chair: Deniz Ozdemir
Chair: Gokberk Ozsakalli
1 - Solving the Pre-Marshalling Problem to Optimality
with A* and IDA*
Kevin Tierney, Dario Pacino, Stefan Voss
We present a novel solution approach to the container pre-marshalling
problem (CPMP) using the A* and IDA* algorithms combined with
several novel branching and symmetry breaking rules that significantly
increase the number of pre-marshalling instances that can be solved to
optimality. The CPMP is a key problem for container terminals to reduce delays of inter-modal container transports. The goal of the CPMP
is to find the minimal sequence of container movements to shuffle containers in a set of stacks such that the resultig stacks are arranged by
the time each container must leave the stacks.
2 - Hybrid Heuristic Approaches for Tactical Berth Allocation Problem
Cagatay Iris, Allan Larsen, Dario Pacino, Stefan Ropke
Tactical berth allocation problem deals with: the berth allocation (assigns and schedules vessels to berth-positions), and the quay crane
(QC) assignment (finds number of QCs that will serve). In this work,
we strengthen the current mathematical models (MM) with novel lower
bounds and valid inequalities. And, we propose a hybrid heuristic
which combines MM with greedy and search heuristics. Results show
that problem can be solved efficiently respect to optimality and computational time.
HE-06
3 - Optimal Sequencing of Parking Operations at an Automotive Maritime Terminal
Marcello Sammarra, M. Flavia Monaco, Gregorio Sorrentino
The yard management of an automotive maritime terminal often requires the consolidation of parking areas, via reallocation of cars, usually of the same brand, to predefined destination lanes. These operations are performed by a set of drivers that are transferred back from the
parking areas to the pick-up points by a set of shuttle vehicles. We focus on the problem of sequencing the cars to be moved by each driver,
defining the shuttle routes, taking into account the labour agreements,
while minimizing both the number of drivers and shuttles needed to
perform the task.
4 - Stochastic Bi-Objective Berth Allocation and Quay
Crane Assignment for Quayside Operations
Gokberk Ozsakalli, Hüseyin Gençer, Deniz Ozdemir
Traditional planning of quayside operations cause unnecessary waiting of vessels and inefficient utilization of resources. Moreover, most
of the integrated approaches consider deterministic vessel arrivals and
quay crane handling time which is actually not realistic in practice. To
this end, an integrated stochastic bi-objective model has been developed to minimize the vessel service time and quay crane movement.
The mixed integer model was solved by using disjunctive decomposition algorithm and applied at Izmir Container Terminal based on the
historical data. It has shown promising results.
HE-06
Thursday, 16:00-17:30 - Room 211
Learning, Resilience, Competition and
Congestion
Stream: Social and Economic Networks
Invited session
Chair: Alex Teytelboym
1 - Dynamic Congestion Games: The Price of Seasonality
Marco Scarsini
We propose a model of discrete time dynamic congestion games with
atomic players. This approach allows to give a precise description of
the dynamics induced by the individual strategies of players and to
study how the steady state is reached, either when players act selfishly,
or when the traffic is controlled by a planner. We model also seasonalities by assuming that departure flows fluctuate periodically with time.
We focus mostly on simple networks and give closed form formulas
for the long-run equilibrium and optimal latencies, as functions of the
seasonality.
2 - Learning what Matters
Manuel Mueller-Frank, Itai Arieli
We consider a generalization of the strict sequential social learning
model and analyze asymptotic learning for general state, signal and action spaces. Our main result provides a sufficient condition for asymptotic learning.
3 - Network Resilience Against Epidemic Spread
Kimon Drakopoulos, Asu Ozdaglar, Asu Ozdaglar, John
Tsitsiklis
We study the problem faced by a network defender when an epidemic
is evolving on a known network. We assume that the network defender
has full information on the state of the epidemic and can allocate curing rates to nodes under a budget constraint. The goal is to minimize
the expected extinction time of the epidemic. We find necessary and
sufficient conditions on the graph structure under which curing policies
that achieve sublinear extinction time exist.
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IFORS 2014 - Barcelona
4 - Knowledge Leadership: A Systems Approach
Uttarayan Bagchi, Amitava Dutta, Jack Hayya
Knowledge leadership seeks to make the process of knowledge exploitation cheaper, better and faster. We contend that accomplishing
this tall objective requires a shift of mind along the lines articulated
by Peter Senge in his writings on systems thinking. On one hand, the
process perspective must be supplemented with an explicit recognition of interrelationships. On the other hand, practitioners will benefit
by thinking of knowledge leadership at three distinct levels: essence,
principles and practices.
HE-07
Thursday, 16:00-17:30 - Room 003
Fuzzy Optimization in Supply Chain
Management, Production and Logistics
Stream: Fuzzy Optimization - Systems, Networks and
Applications
Invited session
Chair:
Chair:
Chair:
Chair:
Ozlem Defterli
Silja Meyer-Nieberg
Erik Kropat
Mehmet Burak Şenol
1 - Supplier Selection in a Fuzzy and Probabilistic Environment
Sarah Bakhtiari, Ahmad Makui
In this paper, the supplier selection problem is investigated. It is important to consider how uncertainty influences the decision-making
process. Ranking alternatives using Fuzzy variables and probabilistic
variables is a realistic approach. In this research, two approaches are
presented for the supplier selection problem in which criteria are both
fuzzy and probabilistic. The first approach is proposed based on the
Borda ranking method and the second approach is proposed based on
the probability-possibility transformation. The proposed approaches
are evaluated using computational results.
2 - Modified FCM Method to Explore Variations in a
Multi-Variable Field
Metin Ger
FCM method has been in use for quite some time, to determine a stable future state of a multi-variable field. Modifications made to FCM
method, presented in this study, facilitate the exploration of variation in
time of variables constituting the field. As demonstrated, the modifications made to FCM method make it possible to carry out a comparative
analysis of a multi-variable field subject to different scenarios. (Joint
work with H. Fatih Aydın)
3 - Decision Making in Interface Selection
Mehmet Burak Şenol, Metin Dagdeviren, Mustafa Kurt
Different approaches (Goal programming, ANP, F-PROMETHEE) are
offered for the selection of cockpit interfaces in terms of usability.
Most of usability evaluation techniques are not analytical; characteristics and number of evaluators affect results. In order to overcome these challenges an Integrated Approach with ANP and Fuzzy
PROMETHEE is employed. Goal programming approach is also applicable to the problem, in which objective function weights should
be determined by ANP. A user-friendly interface design will improve
aircraft usability and safety.
4 - Team-Oriented Assembly Line Balancing Problem: A
Fuzzy Approach
Hamid Yılmaz, Mustafa Yılmaz, Merve Kayacı Çodur
In recent years with the advantage of the technology it has become possible to produce goods which are more complex.Therefore line designers allow stations to have several workers in the same station which is
called team-oriented assembly line. However, in real life assembly line
problems assembly time of tasks can be uncertain. Fuzzy sets theory is
frequently used to represent uncertainty of information. This study addresses the team-oriented assembly line balancing problem with fuzzy
processing time and a fuzzy linear programming model is formulated
for the team-oriented assembly line.
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HE-08
Thursday, 16:00-17:30 - Room 120
Case Teaching
Stream: Teaching OR/MS
Invited session
Chair: Peter Bell
1 - The Perspective of an Instructor New to "Case Teaching"
Mehmet Begen
This presentation will focus on the challenges of some new faculty
member learning to teach with cases for the first time.
2 - OR/MS Case Teaching in Engineering Programs
Fredrik Odegaard
In this talk I will discuss some issues and strategies for teaching
OR/MS using cases in engineering programs. Case teaching is usually associated with business school programs, but designed properly
can (and should) be included in engineering programs as well.
3 - A Review of some of the many Ways to Include Cases
in the OR Course
Peter Bell
This presentation will put forward many different ways that cases can
be used in the context of teaching OR illustrating the variety of cases
available and the richness that these case can bring to the OR course.
HE-09
Thursday, 16:00-17:30 - Room 121
Energy Markets
Stream: Technical and Financial Aspects of Energy
Problems
Invited session
Chair: Angelica Gianfreda
1 - A Two-Step Day-Ahead Electricity Market Model for
the Market Coupling between Central Southern, Central Western and Northern Europe
Dario Siface, Alberto Gelmini, Emanuele Maltempi,
Emanuele Tresoldi
Coupling the European Electricity Markets is the only way to optimally allocate the cross-border transmission capacity. Computationally, it is impossible to solve the exact mathematical model describing
altogether the Italian Uniform Purchase Price and the Central Western
and Northern Europe block offers. Thus, the approach developed in
this work computes the optimal solution for the Italian market for each
import/export level (Net Export Curve - NEC). The NEC is then the
input for the Central Western and Northern Europe market solution.
The result is the optimal market coupling solution.
2 - A Leader-Followers Model of Power Transmission
Capacity Expansion in a Market Driven Environment
Paolo Pisciella, Marida Bertocchi, Maria Teresa Vespucci
A bilevel program with mixed integer structure in both upper and lower
level is introduced for analysing the upgrade of the national transmission grid. The upper level defines the transmission company problem and the lower level models the reactions of generating companies,
which take a decision on new facilities and power output, and market
operator, which strikes a new balance between demand and supply by
providing new Locational Marginal Prices. We illustrate our methodology by means of an example based on the Garver’s 6-bus Network.
IFORS 2014 - Barcelona
3 - Comparative Analysis of Pricing Schemes in Markets
with Non-Convex Costs
George Liberopoulos, Panagiotis Andrianesis
In markets with non-convex costs (e.g., electricity markets), classical
marginal cost pricing may fail to provide sufficient revenues to the market participants, who may not recover their fixed costs. To address this
problem, different pricing schemes that lift the price above marginal
cost and/or provide side-payments (uplifts) have been proposed. We
analyze and compare several of these schemes for a model of two suppliers with symmetric capacities and asymmetric marginal and fixed
costs, who compete to satisfy a deterministic inelastic demand of a
commodity in a single period.
HE-11
This paper introduces a television grid optimization model for optimum television programming and scheduling. The methodology we
use in our research is to combine both academic work and practitioners’ experiences in order to build an innovative model for optimizing
the programmes grid and maximizing viewership. The problem has
been formulated as an integer program, and the software package used
gives us the ability to solve large scale optimization models with thousands of variables and constraints which will certainly help media planners to plan for months ahead, if not years.
HE-11
Thursday, 16:00-17:30 - Room 113
4 - Power Price Forecasting with Wind Effects
Angelica Gianfreda, Derek Bunn, Dipeng Chen
We present a nonlinear regime switching method for short term power
price forecasting to reflect the effects of increased wind generation on
price risk. We show that the stochastic nature of wind generation poses
a new set of distributional properties for the power price risks. We
compare alternative regime switching methods as well as linear methods, and control for the price formation fundamentals of demand and
fuels. The approach is applied to the main reference market for Europe,
the EEX, with extensive out-of-sample testing.
Topics in Linear Programming and
Combinatorial Optimization
Stream: Combinatorial Optimization
Invited session
Chair: Valentina Cacchiani
Chair: Sergio B. Villas-Boas
1 - Dual-Guided Pivots Rules for Linear Programming
Jean-Bertrand Gauthier, Jacques Desrosiers, Marco Lübbecke
We describe a generic primal algorithm for LPs guided by dual feasibility considerations. The resolution process moves from one solution
to the next according to an exchange mechanism that is defined by a
direction and a step size. The core component of this direction is obtained via the smallest reduced cost that can be achieved upon dividing
the set of dual variables in two subsets: one being fixed while the other
is optimized. The Primal Simplex, the strongly polynomial Minimum
Mean Cycle-Canceling algorithm devised for network problems and
the Improved Primal Simplex are special cases.
HE-10
Thursday, 16:00-17:30 - Room 122
Workforce Optimization
Stream: Timetabling and Rostering
Contributed session
Chair: Mike Wright
1 - Near-Optimal MIP Solutions for Preference Based
Self-Scheduling
Eyjolfur Asgeirsson, Gudridur Lilla Sigurdardottir
We look at a variation of preference based scheduling where the schedule is based on a preliminary schedule that is created by the employees. We formulate a mixed-integer program (MIP) to find a feasible
schedule that satisfies all hard constraints while minimizing the soft
constraint violations as well as satisfying as many of the employees’
requests as possible. We show the result from four real world companies and institutions, and compare the results with those of a local
search based algorithm that is designed to emulate the solution strategies when the schedules are created manually.
2 - Optimal Sequencing of Unpunctual
Provider’s Wait-Preempt Dilemma
Subhamoy Ganguly, Michele Samorani
Patients:
Even though it is known that patients often arrive early and out of turn
for scheduled appointments in outpatient clinics, no research has been
undertaken to establish whether an available provider should see an
early patient right away (preempt) or wait for the patient scheduled
next. In this work, we analytically determine the time intervals where
it is optimal to preempt and those where it is optimal to wait. Our analysis indicates that an always-preempt policy is never optimal, although
it is a good heuristic under certain circumstances.
3 - Call Centers with a Callback Option
Benjamin Legros, Oualid Jouini, Ger Koole
We consider a call center model with a callback option, which allows
to transform an inbound call into an outbound one. The objective of the
system manager is to define the optimal call scheduling that minimizes
the total expected waiting cost of inbound and outbound calls. Using
a Markov Decision Process approach, we numerically characterize a
switching curve of the agent reservation for inbound calls.
4 - Optimizing Television Programming and Scheduling
Mike Wright, Mhd Hani Alshami
2 - The Size Robust Multiple Knapsack Problem
Denise Tönissen, Marjan van den Akker, Han Hoogeveen
The size robust multiple knapsack problem is a variant of the multiple
knapsack problem where the knapsack sizes can decrease with a certain probability. We consider this as a recoverable robust optimization
problem, where we allow recovery by removing items. Our goal is
to maximize the expected value. We consider two decomposition approaches and use branch and price to solve the model. We investigate
different variants of the algorithm by solving thousands of instances.
We show that the column generation process can be accelerated by a
factor ten compared to naive approaches.
3 - A Benders Decomposition Approach for the Minimum Weight Maximal Matching Problem
Z. Caner Taşkın, Tinaz Ekim, Merve Bodur
We investigate the problem of finding a maximal matching having minimum total edge weight on an undirected graph, which is known to be
NP-hard. We formulate the problem as an integer programming problem and devise a Benders decomposition approach. The master problem in our approach turns out to be a vertex cover problem while the
subproblem is a perfect matching problem that is solvable by combinatorial matching algorithms. Our computational tests on a large suite
of randomly generated graphs show that our decomposition approach
significantly improves solvability of the problem.
4 - Solving Mixed-Integer Programming with Unconstrained Optimization and Hyperbolic Penalty
Sergio B. Villas-Boas, Renan Pinto, Adilson Elias Xavier,
Nelson Maculan
Several practical problems fall into Mixed-Integer Programming problems. In this work we propose a method to solve a class of MixedInteger Programming problems by converting the original problem to
a set of Unconstrained Optimization problems where the integer decision variables are transformed into specially defined penalty components based hyperbolic function. The unconstrained optimization with
special penalty functions produce a solution with real variables, but the
integer variables are very close to integer variables.
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IFORS 2014 - Barcelona
HE-12
Thursday, 16:00-17:30 - Room 004
Project Scheduling and Scheduling
Stream: Project Management and Scheduling
Invited session
Chair: Meral Azizoglu
1 - A Project Payment Scheduling Problem with Discounted Cash Flows
Alican Coemert, Meral Azizoglu
We consider a project payment model with discounted cash flows. We
assume that the client payment times are defined in the project contract. The activities are characterized by their processing times and
costs that are incurred at their completions. Our problem is to find the
client payment amounts and activity completion times so as to minimize the net present value of the client payments and activity costs.
We formulate the problem as a nonlinear MIP and solve small problem
instances. For moderate to large sized problem instances we propose
B&B.
2 - Optimal Bid Unbalancing for Projects with Unit Price
Contracts: Time Preferences, Risk Preferences, and
the Client’s Perspective
Joseph Szmerekovsky, Vera Tilson, Napoleon Tiapo
For the contractor we determine prices on different units of work, given
the uncertainty about the final amount of work of different types that
will be needed in completing the project. We obtain both the optimal bid quantity and the corresponding optimal unit prices accounting
for time and risk preferences. For the client we analyze the client’s
ability to detect bid unbalancing and adjust estimated work quantities
accordingly. Our results are validated using data from North Dakota
Department of Transportation construction projects.
1 - Mixed Model Sequencing Procedure in Case of Paced
Assembly Line and Jolly Operators
Marco Bortolini, Maurizio Faccio, Mauro Gamberi
Considering mixed model assembly lines,variations in process times
are considered. In un-paced buffered assembly lines these variation are
absorbed by buffers with high WIP costs and space utilization. Many
companies try to adopt paced assembly line, where the cycle time is
controlled by the continuous moving of the products from the first to
the last assembly station. Jolly operators support the station’s single
operator to complete the assembly when the cycle can be exceeded.
We aim to introduce an innovative sequencing model for mixed-model
paced assembly line using jolly operators.
2 - An Enumeration Procedure for the Assembly Line
Balancing Problem with Resource Constraints
Mariona Vila Bonilla, Jordi Pereira
This work studies an assembly line balancing problem in which the
assembly work must be assigned to the stations of the line subject
to linear constraints on the availability of resources on each station.
This work proposes three new classes of lower bounds for the problem. These bounds and some new dominance rules are then used on
a station-oriented enumerative procedure. The efficiency of the final
algorithm is tested with a series of computational experiments on different benchmark sets and the results are compared with previous enumerative procedures.
3 - Disassembly Line Balancing Problems with Resource Dependent Task Times
Seda Hezer, Yakup Kara
In disassembly line balancing problems (DLBP), it is basically considered that every task’s time is fixed. However, there may be different
processing alternatives for a task with different times. This problem
can be called resource dependent DLBP (RDDLBP). The problem is
to assign tasks and resources to workstations that minimize total cost of
disassembly. To the best of our knowledge, this study is the first RDDLBP study. The model’s performance is evaluated using test problems.
3 - Reinforcement Learning Strategy for Solving the
Multi-Mode Resource-Constrained Project Scheduling Problem by a Team of Agents
Ewa Ratajczak-Ropel, Piotr Jedrzejowicz
4 - A Multi-Objective Algorithm for Balancing Reconfigurable Transfer Lines
Xavier Delorme, Alexandre Dolgui, Sergey Malyutin
In the paper the strategy for the A-Team with Reinforcement (RL)
Learning for solving the MRCPSP is proposed and experimentally
validated. To solve the problem a team of asynchronous agents (ATeam) has been implemented using a multiagent system. An A-Team
is the set of objects including multiple agents and the common memory which through interactions produce solutions of optimization problems. These interactions are usually managed by the static strategy. In
this paper the dynamic learning strategy is proposed. To validate the
approach a computational experiment has been carried out.
A multi-objective line balancing problem for reconfigurable transfer
lines is studied. These lines are paced and serial, and each station corresponds to one or several parallel CNC (Computer Numerical Control) machines. The objective of this problem is to find a trade-off between the investment cost (mainly the number of stations and of CNC
machines) and the throughput (i.e., cycle time). A heuristic algorithm,
using several mixed integer programs to solve sub-problems, is proposed to approximate the Pareto front. This algorithm takes advantages
of some specific properties of the problem.
4 - Single-Machine Earliness-Tardiness Scheduling with
Periods of Machine Unavailability
Safia Kedad-Sidhoum, Kerem Bulbul, Halil Şen
The addressed problem is a one-machine earliness-tardiness scheduling where a job cannot be executed in some time intervals called
breaks. A job can start before and end after a break assuming an increase of its processing time. Preemption is only allowed if it occurs
on a break. Each job has a due date and the objective is to minimize
the total earliness and tardiness penalties. We will present a complexity
analysis as well as exact solving methods based on structural properties
of the optimal solutions for some specific cases such as the common
due-date, resumable and non-resumable cases.
HE-13
Thursday, 16:00-17:30 - Room 123
Balancing and Sequencing of Assembly
Lines 2
Stream: Scheduling
Invited session
Chair: Alexandre Dolgui
Chair: Alberto García-Villoria
Chair: Xavier Delorme
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HE-14
Thursday, 16:00-17:30 - Room 124
Advances in Nonlinear Optimization:
Theory and Applications IV (contributed)
Stream: Nonlinear Programming
Contributed session
Chair: Nima Rabiei
1 - A Partially Observable Markov Decision Process under Stochastic Convexity as an Optimal Maintenance
Problem
Toru Nakai
Consider an optimal maintenance policy for products. During their life
cycle, a condition of this item changes according to a Markovian transition rule based on stochastic convexity. On the other hand, a decision
also makes a transition, which is determined by a function with convexity and supermodularity. This problem is formulated as a partially
observable Markov decision process. The objective of a problem is
how much to expend to maintain this item to minimize the total expected cost. A dynamic programming formulation implies a recursive
equation about optimal value.
IFORS 2014 - Barcelona
2 - A Continuous Time Semi-Markov Decision Process
on Electricity Supply Problem
Adewoye Olabode
Markov decision processes are models for sequential decision making
when outcomes are uncertain. The MDP consists of solution strategies, states, rewards and transition probabilities. SMDP is a special
type of MDP widely used in solving problems in the field of engineering, economics and others. In this work we undertook some study
on optimality criteria over an infinite horizon. Application on solving
an electricity problem is considered using policy iteration methods on
SMDP.
3 - A Stochastic PDE-Constrained Optimization Approach to Vibration Control of a Composite Plate
subjected to Mechanical and Electromagnetic Loads
Olesya Zhupanska, Dmitry Chernikov, Pavlo Krokhmal
We consider the problem of optimization and control of "smart", or
"multifunctional" mechanical structures under uncertainty. In particular, a PDE-constrained optimization model for vibration control of a
composite plate due to an impact load through an application of electromagnetic field is presented. To account for uncertainty in the impact
load, a two-stage stochastic PDE-constrained programming problem is
formulated. A solution method is presented, and the results of computational study are discussed.
4 - AAR-Based Decomposition Algorithm for Nonlinear
Convex Optimization
Nima Rabiei, Jose J Muñoz
We here propose a method for decomposing a class of convex nonlinear programs which are frequently encountered in engineering plastic
analysis. These problems have second-order conic memberships constraints and a single complicating variable in the objective function.
The method is based on finding the distance between the feasible sets
of the decomposed problems, and updating the global optimal value
according to the value of this distance. The latter is found by exploiting the method of Averaged Alternating Reflections (AAR), which is
adapted here to the optimization problem at hand.
HE-16
3 - The Influence of Corporate Norms and Misconduct
on Employee Decision Making
Swetlana Dregert, Peter Letmathe, Ramji Balakrishnan
We study a sender-receiver game in which the sender has to decide
whether to share information for a given level of cost and if yes which
kind of information (productivity enhancing or decreasing). The receiver decides whether to accept the offered information without knowing the kind of transferred information. We conduct a 2x2 experiment
with the existence of a code of conduct (yes-no) as one dimension and
reports about misconduct (yes-no) as the other. We find that individual behavior is influenced by intrinsic motivation and inconsistencies
between expressed norms and actual firm behavior.
4 - Honesty and Reciprocity in Capital Budgeting: An
Experimental Investigation
Andreas Ostermaier, Markus Brunner
Budgets are widely used in firms to control costs, but they may also
lead to underinvestment as they prevent costly but profitable projects.
We find, in a lab experiment, that this problem is exacerbated by
managers who exhibit negative reciprocity and turn down profitable
projects to punish superiors for setting budgets. However, managers
are reluctant to lie about the costs of projects to make them fail. Cost
reports incorporate honesty into budgeting and thus mitigate the effects
of negative reciprocity. These findings imply that it is reasonable for
firms to combine budgets with reports.
HE-16
Thursday, 16:00-17:30 - Room 127
Combinatorial Methods for Data Analysis
HE-15
Thursday, 16:00-17:30 - Room 125
Experimental Research in Management
Accounting and Management Control 1
Stream: Experimental Perspectives and Challenges in
Management Accounting and Management Control
Invited session
Chair: Stephan Leitner
1 - Coordination and Learning in an Experimental Queuing System
Ann van Ackere, Erik Larsen, Santiago Arango
How do people make repeated choices in a service environment where
waiting time is a key decision element? Are people in a distributed system with limited information able to coordinate to approach optimal
system performance? We study this issue in an experimental queuing
setting, with teams of 18 subjects, varying both information and system complexity. While information has little impact on the average
system performance there are significant implications for the behavior
at the individual level. We also observe that the average performance
deteriorates when complexity is increased.
2 - The Impact of Queue Features on Customers’ Queue
Joining and Reneging Behavior: A Laboratory Experiment
Busra Gencer, Zeynep Aksin, Evrim Didem Gunes, Ozge Pala
In many service settings, customers encounter waits in queues and have
to decide between joining and balking, waiting and reneging. This
study investigates customers’ queue joining and reneging behaviors
by using laboratory experiments in which participants experience several observable queues with different characteristics in terms of queue
length and service times and decide to join, balk or renege. Findings
of this study provide insight into how customers make their decisions
in queuing systems and how queue length and waiting time uncertainty
affects their joining and reneging behaviors.
Stream: Intelligent Optimization in Machine Learning
and Data Analysis
Invited session
Chair: Nikita Ivkin
1 - Fast Logical Predictors for Genotype-Phenotype
Mapping
Galina Iofina, Yury Maximov, Andrey Minaev, Yury
Polyakov
In this study we analyse different ways to improve quality of genotype
phenotype mapping in RNA viruses problems. We develop learning
algorithms that attempt to construct predictors as logical functions of
covariates. An important point of our study is metric optimization of
the set of initial features using convex programming. We demonstrate
the learning algorithm’s consistency and effciency on simulated and
real sequences. The reported study was supported by RFBR, research
projects No. 14-07-31241 _a, 14-07-31277 _a and by RF government
grant, ag. 11.G34.31.0073.
2 - Laplacian Matrixes Based Graph’s b-Coloring for
Clustering
Houria Hablal, Hacene Ait Haddadene, Nabil Belacel
In this work we have developed a clustering method based on graph bcoloring algorithm and Laplacian graph which is a graph associated to
Laplacian matrixes. Our method performs clustering into two steps:the
construction of a graph based on eigenvectors of Laplacian matrixes
and the b-coloring of Laplacians graph in order to divide the vertexes
set into clusters. We will perform a comparative study between our
algorithm, the spectral clustering and the b-coloring based clustering
methods using UCI data sets. The results show that our algorithm has
a great potential to solve clustering problem.
211
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IFORS 2014 - Barcelona
3 - A Density and Connectivity Based Decision Rule for
Pattern Classification
Tulin Inkaya
In this study we propose a novel neighborhood classifier. Traditional
Nearest Neighbor classifier is a distance-based method, and it classifies a sample using a predefined number of neighbors. In this study
neighbors of a sample are determined using not only the distance, but
also the connectivity and density information. One of the well-known
proximity graphs, Gabriel Graph, is used for this purpose. The proposed decision rule is a parameter-free approach, and it yields good
results in artificial and real data sets.
HE-17
Thursday, 16:00-17:30 - Room 005
Enumeration of Combinatorial Structures
Stream: Graph Searching
Invited session
Chair: Jan van Vuuren
1 - Edge Stability and Edge Criticality in Secure Graph
Domination
Anton de Villiers, Alewyn Burger, Jan van Vuuren
A subset X of the vertices of a graph G is a secure dominating set of
G if X is a dominating set of G and if, for each vertex u not in X,
there is a neighbouring vertex v of u in X such that the swap set (Xv)+u is a dominating set of G. The secure domination number of G is
the cardinality of a smallest secure dominating set of G. A graph G is
q-critical [p-stable] if the smallest [largest] arbitrary subset of edges
whose removal from G necessarily [does not] increase the secure domination number has cardinality q [p]. A framework is established for
enumerating q-critical and p-stable graphs.
2 - Using Volunteer Computing for the Enumeration of
Mutually Orthogonal Latin Squares
Johannes Gerhardus Benade, Alewyn Burger, Jan van Vuuren
Orthogonal Latin squares have application in various scheduling problems. The enumeration of main classes of sets of mutually orthogonal
Latin squares, however, remains computationally very difficult. It is
proposed that this computational barrier may be overcome by means of
a volunteer computing project, which distributes a computation across
a number of volunteer hosts. A backtracking algorithm for the enumeration of sets of mutually orthogonal Latin squares is adapted for use in
such a large, distributed volunteer computing project and the results of
a pilot study are reported.
3 - On a Two-Phase Approach to Enumerating Sets of
Mutually Orthogonal Latin Squares
Martin Kidd
In this talk the problem of enumerating equivalence classes of sets of
mutually orthogonal Latin squares is considered. An algorithm is presented which determines the number of classes covered by a so-called
template, where a template is said to cover a class if its members satisfy a set of class-invariant constraints described by the template. The
effectiveness of the algorithm is shown, and some ideas are put forth
for finding a set of templates large enough for all possible classes to be
enumerated, yet small enough to be tractable in a realistic time-frame
using the presented algorithm.
4 - On the Minimum Number of Moves for Solving the
WrapSlide Puzzle
Alewyn Burger
WrapSlide is a slide-puzzle consisting of a 6 by 6 grid of tiles in
which each quadrant of 3 by 3 tiles are coloured differently. The
puzzle can be scrambled into different states by performing a number of moves involving wrapping of tiles. A move consists of sliding either the top, bottom, left or right two quadrants of tiles 1 to 5
units horizontally or vertically. We discuss our attempt to partition the
111733085472015089 non-isomorphic states of the puzzle according
to the minimum number of moves to solve each state.
HE-18
Thursday, 16:00-17:30 - Room 112
Interactive MCDM
Stream: Multiobjective Optimization - Theory, Methods
and Applications
Invited session
Chair: Murat Koksalan
1 - The Layouts of Supported and Unsupported Nondominated Solutions in Multi-Objective Integer Programs
Gökhan Ceyhan, Murat Koksalan, Banu Lokman
We address the problem of characterization of nondominated solutions
in different multi-objective integer programs. We work on problems
with three or more objectives. We study the number of supported and
unsupported nondominated solutions, their distributions in the objective space, and the representativeness of supported solutions for different problems. We conduct computational experiments on random
instances to demonstrate the effects of objective function types and
problem parameters on the efficient sets of these problems.
2 - Probabilistic Sorting under Multiple Criteria
Sinem Mutlu, Murat Koksalan, Yasemin Serin
We consider placing alternatives that are assessed by multiple criteria
into preference ordered classes. We develop an interactive probabilistic
sorting approach that calculates the probability of each alternative being in each class. We place alternatives into classes if the probabilities
of misclassification of all alternatives are below a specified threshold.
We demonstrate the performance of the approach on several problems.
3 - Bi-Objective Route Planning for Unmanned Air Vehicles in Continuous Space
Murat Koksalan, Diclehan Tezcaner Ozturk
We consider the route planning problem of unmanned air vehicles
(UAVs). We consider the case where a UAV visits all targets and returns to base in a two dimensional continuous terrain. The objectives
are to minimize the distance traveled and the radar detection threat.
This problem is a bi-objective traveling salesperson problem (BOTSP)
with multiple efficient paths between targets. We develop both an exact and a heuristic approach to find the efficient arcs between the target
pairs. Using the approximated efficient frontiers of the arcs, we reach
the overall efficient frontier of the BOTSP.
4 - Exploiting Robustness Analysis for Triggering Interactive Feedbacks in Multicriteria Disaggregation Aggregation Approaches
Athanasios Spyridakos, Yannis Siskos, Denis Yannacopoulos,
Nikos Tsotsolas, Nikos Tsotsolas
The analysis and picturing of preference models’ robustness in Disaggregation - Aggregation approaches can provide useful information
about DM’s preferences structure and lead to feedbacks for estimating
of a representative preference models which is accepted by the DMs.
This research work presents a new approach which utilises additional
preference information gathered indirectly, 3-D visual techniques and
two new types of interactive feedbacks in order to estimate more consistent and robust preference models.
HE-19
Thursday, 16:00-17:30 - Room 128
Demand Planning and Pricing
Stream: Demand and Supply Planning in Consumer
Goods and Retailing
Contributed session
Chair: Argon Chen
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1 - Determining an Optimal Hierarchical Forecasting
Model Based on the Characteristics of the Data Set
Zlatana Nenova, Jerrold May
High-dimensional pyramidal databases are common in the supply
chains of large manufacturing companies. Such organizations often
forecast shipments and consumption patterns at different hierarchical
levels. In multiple-level supply chains, determining the most appropriate forecast aggregation approach is often a very computationally
intensive task. Using data from a large food-processing firm, we built
a model that requires, as input, only correlation metrics, and produces
an accurate prediction of the optimal forecasting approach.
2 - Agricultural Cooperative Pricing of Premium Product
Nur Cavdaroglu, Burak Kazaz, Scott Webster
We consider the problem of pricing by a cooperative for an agricultural product where: (1) the open-market price for the product depends
on yield and on quality and (2) the quality of the product is influenced by farmer investments over the growing season. The cooperative
purchases product from its members according to a quality-dependent
price schedule, which largely mimics the open market, as observed at
a major cooperative we study. We identify a simple pricing scheme
that shows potential to improve performance, and we characterize the
drivers and the magnitude of performance improvement.
3 - Optimal Demand Planning Hierarchy and Its Applications
Argon Chen
For efficient production and logistic planning and scheduling, an OnLine Analytical Processing (OLAP) tool is often used for analysis of
multi-perspective (multi-dimensional) demand aggregation and disaggregation. Demand planners can use the tool to quickly roll up demands to an aggregated level for a total demand or drill down a total
demand to detailed demands by different perspectives. For example,
a demand planner can roll up (or aggregate) the detailed demand to
calculate the total demand of a certain product in North America and
Europe for the second half of the year.
4 - Advance Selling in a Supply Chain
Xubing Zhang
This paper develops a bilateral-monopoly supply chain model to investigate advance selling by a seller. It shows that the supplier has an
important impact on the seller’s advance selling strategy. The seller
will use advance selling only if it is able to yield a positive margin,
whereas advance selling’s ability to expand the market affects the supplier’s wholesale price and its decision as to whether to induce the
seller’s adoption of advance selling. Moreover, a seller in a supply
chain may have greater incentives to adopt a spot and advance selling
strategy than does a direct seller.
HE-21
2 - Battery Storage Bidding with Battery-Life Effects
Boris Defourny, Yuhai Hu
We use dynamic programming to derive bidding strategies for Lithiumion battery storage where the physical characteristics of the batteries
can be irreversibly degraded by extreme but highly profitable chargingdischarging patterns.
3 - Grid Integration of Wind and Electric Vehicles
Valerie Thomas, Dong Gu Choi, Frank Kreikebaum, Deepak
Divan
We develop serial models to optimize generation capacity over multiple decades, simulate the unit commitment and economic dispatch
processes, and solve for the fuel economy of conventional vehicles
based on US fuel economy rules. We apply the models to analyze implications of electric vehicles (EVs) . With baseline uncontrolled EV
charging, total GHG emissions do not substantially decrease even with
high EV adoption. GHG impacts of EVs can be reduced by controlling
the time of charging. Consumer expenditures are examined; controlled
charging substantially reduces costs.
HE-21
Thursday, 16:00-17:30 - Room 006
Cutting and Packing 4
Stream: Cutting and Packing
Invited session
Chair: José Fernando Gonçalves
1 - Exact Resolution of the Cover Printing Problem with
a Branch and Bound Algorithm
Arnaud Vandaele, Daniel Tuyttens
The Cover Printing Problem is a combinatorial optimization problem.
For each book cover we have to produce a given number of copies.
On templates, there are four positions that can accommodate covers.
A particular number of copies is made of each template to meet the
demands. This problem can be linked with cutting problems where
the cost increases when a new pattern is used. We study different formulations and the results obtained. In the second part, we developed
a specific branch and bound algorithm to solve larger instances. We
were able to find optimal solutions of unsolved instances.
2 - A Dominance Criterion for Packing Problems
Michaël Gabay, Hadrien Cambazard, Yohann Benchetrit
HE-20
Thursday, 16:00-17:30 - Room 129
Controlling Electric Vehicles and Battery
Storage
Stream: Stochastic Optimization in Energy
Invited session
Chair: Pavankumar Murali
1 - Scheduling and Long-Term Pricing of Electric Vehicle Charging in Parking Lots with Shared Resources
Ajay Deshpande, Pavankumar Murali
With the growth in the use of electric vehicles (EVs), management of
shared charging infrastructure under uncertain customer demands and
schedules, and under time-varying electricity prices presents a novel
servicing opportunity. We formulate a combined pricing-scheduling
model to handle these inherent uncertainties and propose a tractable
algorithm to find long-term charging permit prices for different arrivaldeparture-demand bundles and the corresponding charging schedules.
We present an algorithm which we use to identify easy subproblems
for packing problems. The algorithm is polynomial in the number of
bins and item types and is based on a flow computation in a bipartite
compatibility graph. It outputs the largest subproblem satisfying the
dominance criterion and a feasible solution to this subproblem. The
algorithm is well suited to be integrated in a branch-and-bound solver
for packing problems and can be adapted to work on many problems,
including single or multi-dimensional bin packing, vector packing, cutting stock, packing with conflicts, etc..
3 - An Integrated Facility Layout and Product Range
Planning Problem
Bernd Hillebrand, Grigory Pishchulov
We consider a problem of integrated facility layout and product range
planning (FLPRP) where material flow may differ across products. To
this end, we extend the facility layout problem (FLP). The FLP leads to
a quadratic assignment problem for which several linearizations have
been proposed in the literature. None of these formulations can however be readily employed for solving the FLPRP with conventional
methods. For this reason we introduce a new linearization approach
for the FLP that naturally carries over to FLPRP and allows to solve
the latter with methods of mixed-integer programming.
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IFORS 2014 - Barcelona
4 - A Biased Random Key Genetic Algorithm for the Facility Layout Problem
José Fernando Gonçalves
This paper presents a biased random key genetic algorithm (BRKGA)
for the facility layout problem where a set of facilities has to be packed,
without overlapping, on a rectangular floor. The objective is to find
a packing that minimizes the sum of the weighted distances between
the centroids of the facilities. A BRKGA defines the order of placement of each facility, and a local search is used to position each facility. Tests validate the quality of the approach. Supported by Fundação para a Ciência e Tecnologia (FCT) through projects PTDC/EGEGES/117692/2010 and NORTE-07-0124-FEDER-000057.
HE-22
Thursday, 16:00-17:30 - Room 007
Agent Behavior in Markets and Related
Subjects
Stream: Algorithmic Game Theory
Invited session
Chair: Sebastien Lahaie
Chair: Giorgos Christodoulou
1 - Information Aggregation in Exponential Family Markets
Sebastien Lahaie
We design prediction markets via the mold of exponential family distributions, a popular probability distribution template used in statistics,
leading to a variety of market makers for continuous outcome spaces.
We analyze the information aggregation performance of such markets under a range of behavioral models, including risk-averse agents,
Bayesian agents, and agents who are budget-constrained.
2 - On Manipulation in Prediction Markets when Participants Influence Outcomes Directly
Mithun Chakraborty, Sanmay Das
We introduce a two-stage game-theoretic model of prediction markets
where agents directly influence the outcome that the market is designed
to forecast but some of the agents may not take participate in the market. We show that this game has two different types of perfect Bayesian
equilibria, one collusive and uninformative, and the other partially revealing, depending on the values of certain belief parameters.
3 - Characterization of SMON Mechanisms with Additive
Valuations over the Real Domain
Annamaria Kovacs, Angelina Vidali
We are interested in the limits of characterizability of mechanisms with
multi-dimensional, additive player-valuations like unrelated scheduling or additive combinatorial auctions. We characterize decisive,
strongly monotone mechanisms for two tasks or items as either task
independent mechanisms or ’(player-)grouping minimizers’, a generalization of affine minimizers.
A highly constrained problem of scheduling nurses to shift duties and
off days with hospital requirements and individual nurse preferences
was studied. In this study, we propose a Memetic Algorithm with a
multi-stage procedure introducing a modified selection scheme along
with specialized crossover and mutation operators to acquire an efficient nurse work schedule satisfying all requirements including the
positive rhythm constraint. Result on the scheme’s performance is satisfactory. The schedule fulfills important nurse preferences and provides fairness as well as a balanced schedule.
2 - Firefly Algorithm for Continuous and Combinatorial
Dynamic Optimization Problems
Fehmi Burcin Ozsoydan, Adil Baykasoğlu
Firefly Algorithm (FA) is a recent population based metaheuristic technique, which simulates the flashing and communication behavior of
fireflies. In the current work, an adaptive FA is proposed to solve
continuous and combinatorial dynamic optimization problems. The
moving peaks problem is used as testing environment on continuous
domain whereas dynamic multidimensional knapsack problem is chosen for combinatorial domain because there exists numerous real life
related applications. According to results, adaptive FA achieves high
quality results.
3 - Coordinate Strategy to Reduce Computational Effort
for Supernova
Eddy Mesa, Juan David Velásquez Henao, Patricia Jaramillo
Computational effort for metaheuristic methods increases with dimensions. Supernova algorithm is a novel metaheuristic. This method
showed robustness and quality for different benchmark functions and
real-world problems; but the computational time increases exponential proportionally with dimensions and population size. In this work,
we present the decomposition by coordinates for supernova algorithm
as a strategy to reduce the computational effort. As a result, we compare the computational effort for original and new version using known
benchmark functions.
4 - An Evolutionary Algorithm for Check-In Desk Allocation
Miguel Mujica Mota
The work presents an evolutionary approach for the allocation of
Check-In Desks in an Airport Terminal. This algorithm has been developed in collaboration with an airport Terminal. The main characteristics of the evolutionary algorithm are presented and the description of
the methodology to perform the allocation. The results indicate that a
good performance is achieved in order to optimize the level of service
inside the terminal.
HE-24
Thursday, 16:00-17:30 - Room 212
Algorithms for Stochastic Games
Stream: Dynamic and Repeated Games
Invited session
Chair: Hugo Gimbert
HE-23
Thursday, 16:00-17:30 - Room 008
Genetic and Population Based Algorithms
Stream: Metaheuristics
Contributed session
Chair: Miguel Mujica Mota
1 - A Modified Selection Scheme in Memetic Algorithm
for a Nurse Scheduling Problem with Positive Rhythmic Cycle
Razamin Ramli, Ahamad Tajudin Khader, Adli Mustafa
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1 - Combinatorial Simplex Algorithms Can Solve Mean
Payoff Games
Pascal Benchimol, Xavier Allamigeon, Stephane Gaubert,
Michael Joswig
A combinatorial simplex algorithm is an instance of the simplex
method in which the pivoting depends on certain combinatorial data
only. We show that any algorithm of this kind admits a tropical analogue which can be used to solve mean payoff games. Moreover, any
combinatorial simplex algorithm with a strongly polynomial complexity (the existence of such an algorithm is open) would provide in this
way a strongly polynomial algorithm solving mean payoff games. Our
algorithm relies on a tropical implementation of the simplex method
over a real closed field of Hahn series.
IFORS 2014 - Barcelona
HE-26
2 - Analysis of Stochastic Systems Based on Approximation
Blaise Genest
3 - Software Project Scheduling Problem using Metaheuristics with Autonomous Search
Franklin Johnson, Broderick Crawford, Ricardo Soto
Automata based methods can be used in the analysis of real life system, granted that powerful abstraction refinement techniques are used.
Our aim is to propose such an abstraction refinement for stochastic systems, in particular POMDP. The idea is to approximate probabilities.
The refinement step will be triggered only if the error made is too big
to conclude. An important tool for analyzing the error is the contracting factor. This can be used while approximating the transient values
generated by large systems, and also for the steady state behavior.
The Software Project Scheduling problem consists of making the appropriate assignment of employees to tasks. This allocation should
minimize the duration and cost of the whole project. The main idea
is to solve this problem using metaheuristics. Metaheuristics is an incomplete method to solve combinatorial problems. The process to tune
and adapt the metaheuristics to a specific problem is very hard work to
do, for this reason we introduce the Autonomous Search technique to
control and adapt its own parameters or heuristics.
3 - Two-Player Perfect-Information Shift-Invariant Submixing Stochastic Games Are Half-Positional
Hugo Gimbert
4 - A New Algorithmic Approach for Solving an Inventory Optimization Model
Fernando Paredes, Javier Pereira, Claudio Fuentes, Broderick
Crawford, Ricardo Soto
We consider zero-sum stochastic games with perfect information and
finitely many states and actions. The payoff is computed by a payoff
function which associates to each infinite sequence of states and actions a real number. We prove that if the the payoff function is both
shift-invariant and submixing, then the game is half-positional, i.e., the
first player has an optimal strategy which is both deterministic and stationary. This result relies on the existence of epsilon-subgame-perfect
equilibria in shift-invariant games, a second contribution of the paper.
4 - Exact Algorithms for Stochastic Games and Real Algebraic Geometry
Elias Tsigaridas
Shapley’s discounted stochastic games and Everett’s recursive games
are classical models of game theory describing two-player zero-sum
games of potentially infinite duration. We present an exact algorithm
for solving such games based on separation bounds from real algebraic
geometry. When the number of positions of the game is constant, the
algorithm runs in polynomial time and is the first with this property.
HE-25
Thursday, 16:00-17:30 - Room 009
Metaheuristics in Autonomous Search
Stream: Applications of Heuristics
Invited session
Chair: Ricardo Soto
Chair: Broderick Crawford
1 - The Role of Metaheuristics in Constraint Programming with Autonomous Search
Ricardo Soto, Broderick Crawford, Fernando Paredes
Constraint programming is a programming paradigm for solving
constraint-based problems that has been successfully used in different
application domains. The main idea under this paradigm is to model
the problem in terms of variables and constraints and then to launch it
in a search engine, usually called solver. Recently, Autonomous Search
appeared as a new technique that enables a solver to control and adapt
its own configuration based on self-tuning. In this abstract, we illustrate how metaheuristics are able to optimize this self-tuning process
of constraint programming solvers.
2 - Self-adaptive Systems: Towards Usable Combinatorial Problem Solvers
Broderick Crawford, Ricardo Soto, Eric Monfroy, Fernando
Paredes
New methods in Combinatorial Problem Solving can solve larger problems in different domains. They also became more complex, which
means that they are hard to use and fine-tuning to the peculiarities of
a given problem, limiting the its use to a small set of experts, and instead black-box solvers with automated search procedure are needed
for its broad applicability. We review recent progress on Self-adaptive
Systems from the standpoint of the requirement for solver systems accessible and easier to use. A new research field defined to precisely
address the above challenge is Autonomous Search.
In this work, we develop a new method in order to solve an inventory
optimization model which is defined by minimization of the expected
value of lost sales for a defined investment and number of order levels,
per year. The optimal solution of this optimization model is obtained
by solving the associated Karush-Kuhn-Tucker system. Thus, applying the penalty lagrangian method that using autonomous search in the
parameters definition. The objective function of the model is pseudoconvex and the constraints are defined by quasi-convex functions, ensuring the existence of the global minimum point.
HE-26
Thursday, 16:00-17:30 - Room 010
Nonsmooth Optimization for Learning and
Classification
Stream: Nonsmooth Optimization and Variational Analysis
Invited session
Chair: Antonio Fuduli
1 - Illumination by Cones and Outliers Detection
Annabella Astorino, Manlio Gaudioso, Alberto Seeger
Given a finite set of points in the n dimensional space, we tackle the
outliers detection problem as an illumination one. In particular we
want to illuminate the dataset by means of a suitable revolution cone.
The specific challenge at hand is to determine the sharpness coefficient, the axis and the apex of the cone. These parameters have to be
selected in such a way as to fulfill two conflicting requirements: The
cone captures as many points as possible and, at the same time, it has a
sharpness coefficient as large as possible. Some numerical experiences
are reported.
2 - A New Incremental Piecewise Linear Classifier based
on PCFs
Gurkan Ozturk, Adil Bagirov, Refail Kasimbeyli
In this paper, a piecewise linear classifier based on polyhedral conic
functions (PCFs) is developed. This classifier finds nonlinear boundaries between classes. Since the number of PCFs separating classes is
not known a priori, an incremental approach is proposed to build separating functions. These functions are found by minimizing an error
function which is nonsmooth and nonconvex. An incremental procedure is proposed to generate starting points to minimize the error function. The proposed classifier is applied to solve classification problems
on 12 publicly available data sets.
3 - Projecting onto Lines Using the L-1 Norm
José Dulá, Paul Brooks
In the case of the L-1 norm, a point in m dimensions projects onto a
line by following at most m-1 independent unit directions. Different
points may follow different sets of these directions. One objective of
this work is to characterize the set of points that use the same set of directions for this projection. Another objective is the characterization of
the lines a point can project onto with the L-1 norm using the same directions. These results represent progress towards solving the problem
of finding the best-fit line for a point set using the L-1 norm.
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IFORS 2014 - Barcelona
4 - A Robust Approach for Spherical Separation
Antonio Fuduli, Annabella Astorino, Immanuel Bomze,
Manlio Gaudioso
We propose a robust spherical separation technique aimed at separating two finite sets of points. Robustness is related to the possibility
to have some uncertainties or perturbations in the data sets. This may
occur, for example, when the data are corrupted by noise or are influenced by measurement errors. Starting from the standard spherical
separation, we come out with a model characterized by a non-convex
non-differentiable objective function, which we minimize by means of
a bundle type algorithm. Numerical results are provided on small and
large data sets drawn from the literature.
HE-27
Thursday, 16:00-17:30 - Room 213
Decision Analysis for Risk Management
Stream: Decision Analysis, Decision Support Systems
Contributed session
Chair: Martin Waitz
1 - Design of a Mobile Spatial Decision Support System
for Group Decision-Making on the Analysis of Changing Risk
Roya Olyazadeh, Cees van Westen, Marc Derron, Wim
Bakker
In the ongoing CHANGES Project (changes-itn.eu) and the INCREO
project (increo-fp7.eu) a spatial decision support system is under development with the aim to analyze changes in hydro-meteorological
risk, and support decision makers in selecting the best alternative. Public contribution is the main part of this group decision making. So this
paper presents a prototype of a mobile version where public indicates
their preference anywhere and anytime. The application is being tested
through a case study affected by flooding hoping to have the group decision making more precise and transparent.
2 - Applying Stochastic Analytical Network Process in
Strategic Decisions of Portfolio Management
Hannaneh Rashidi Bajgan, Elham Esmaili Najafabadi
Respecting the interrelationship between knowledge areas of projects,
advantages form analytical network process (ANP) could be derived
to proceed in this stage. The aim of this paper is to use ANP method
to solve this problem, in which there is some uncertainty around the
input data as well as the portfolio manager’s intuitions. Noteworthy,
based on my best knowledge, the existing approaches of ANP method
are restricted to deterministic environments. Therefore, this paper is
presenting a novel approach to be investigated in complex decision
making models.
3 - A Methodology for the Integration of Risk Management in R&D Project Selection
Claudio Santos, Maria Madalena Araújo, Nuno Correia
R&D project selection is a key process in organizations. R&D projects
have also many associated risks, so their consideration early on
projects’ life cycle provide more time for managers to act and manage
risks. However, reviewed methodologies present few approaches that
integrate risk management in project selection. A new multi-criteria
R&D project selection methodology that incorporates risk driven by
the maturity rate and scale of R&D projects is proposed. It is expected
that the methodology will contribute to an improved homogenization
of organizational policies towards risk management.
4 - Overcoming the Inability of Private Lenders to Set
Proper Interest Rates on Unsecured Peer-to-Peer
Lending Markets
Martin Waitz, Andreas Mild
On a typical peer-to-peer lending market, borrowers present their
projects and non-institutional lenders decide under what terms they are
ready to provide the requested capital. We show that investors fail to
transform the available information into proper market activities (i.e.
requesting the appropriate interest rates), threatening the sustainability
216
of this new lending concept. We present and test a decision support
tool to support users in the estimation of borrowers’ risk of default and
demonstrate that our system is able to improve investors return significantly.
HE-28
Thursday, 16:00-17:30 - Room 130
Applied Aspects of MINLP
Stream: Mixed-Integer Nonlinear Programming
Invited session
Chair: Inken Olthoff
1 - A Multi-Objective Mixed Integer Nonlinear Optimization Model for the Aircraft Collision Avoidance
F. Javier Martin-Campo, Antonio Alonso-Ayuso, Laureano
Fernando Escudero
The aircraft collision avoidance consists of providing a new aircraft
configuration such that every conflict situation is avoided. A conflict
takes place when two or more aircraft violate the minimum safety distances that must be kept during their flights. We present a mixed integer nonconvex nonlinear optimization model where three different
multi-objective criteria are studied in order to compare comfort versus
economic impact. The three possible maneuvers are allowed to be performed. An extensive computational experiment is presented where
Minotaur has been the engine solver of choice.
2 - e-OA for the Solution of Bi-Objective Generalized
Disjunctive Programming Problems in the Synthesis
of Nonlinear Process Networks
Metin Turkay, Ali Fattahi
Although decision making in nonlinear process networks involve more
than one criterion, there has been no study in the literature considering the multiple objective case. In this paper, we investigate the
bi-objective nonlinear network synthesis problem. We propose an efficient algorithm based on augmented e-constraint and logic-based outer
approximation. We provide theoretical characterization of the algorithm and show the efficiency of the solutions generated. We conduct
experiments on two benchmark problems to show the performance of
our novel algorithm and illustrate the solutions found.
3 - Optimizing Battery Load Schedules
Inken Olthoff
As the influence of renewable energy grows, also the flexible storage of
energy in batteries gains in importance. One aspect is the construction
of battery load schedules which provide charging and discharging periods while considering the battery and power grid properties. Thereby,
our main challenge is to deal with the non-convex loss of energy while
discharging the battery. In this talk, we describe the Battery Scheduling
Problem and discuss different solving strategies. Taking into account
sudden parameters changes, the aim is to find a strategy which finds
good solutions in a short time.
4 - Preconditioning of Linear Systems Arising from Interior Point Methods
Luciana Casacio, Aurelio Oliveira, Christiano Lyra Filho
In this work, iterative methods are applied to solve linear systems
arising from interior point methods for linear programming problems
through a hybrid approach. In the first phase, the PCG is used to solve
the normal equations. In the last iterations, the augmented system
is rearranged exploiting the basic-nonbasic partitions and a preconditioned Gauss-Seidel method is applied. Computational experiments
with problems from Netlib collection have shown promising good performance of the new approach.
IFORS 2014 - Barcelona
HE-29
Thursday, 16:00-17:30 - Room 011
Logistics and Blending in Natural Gas and
Mining
Stream: OR in Petrochemicals and Mining
Invited session
Chair: Natashia Boland
Chair: Asgeir Tomasgard
1 - Dynamic Blending with Penalties and Bonuses
Natashia Boland, Amir Salehipour, Martin Savelsbergh
Blending problems are textbook exercises in LP modelling: source
materials, each with a given vector of qualities, must be mixed to
yield final products having qualities within specified ranges. However
when blending in real mining contexts, demand for final products is not
static; it arrives over time. Source materials are not available instantaneously, but must be produced at a feasible rate and stockpiled until
needed. The cost structure can be complex, with bonuses available for
"over spec" and penalties for "under spec" product. Results for LP and
MILP models on iron ore data are given.
2 - Simulation Models for Planning an Iron Ore Mine
Jim Everett
In planning an iron ore mine we have a block model of the prospect
(comprising hundreds of thousands of rectangular blocks, with grade
vectors estimated by interpolation of drilling data), and a target grade
(not only in iron but also in a number of contaminants) for a marketable
product. The objective is to select ore blocks so as to maximise the tonnage at target grade, and then to find an operationally feasible sequence
of the ore blocks so as to mine a stream of ore consistently close to target grade. The paper will describe a set of simulation models designed
to achieve these objectives.
3 - Adding Flexibility in a Natural Gas Transportation
Network Using Interruptible Transportation Services
Asgeir Tomasgard, Marte Fodstad, Kjetil Midthun
We present a modeling framework for analyzing if the use of interruptible transportation services can improve capacity utilization in a natural gas transportation network. The network consists of two decision
makers: the transmission system operator (TSO) and a shipper of natural gas. There are two different types of transportation services: firm
and interruptible. Only firm services have a security of supply measure, while the interruptible services can freely be interrupted. The
results indicates substantial increased throughput with the introduction
of interruptible services.
4 - Constraint Programming for LNG Ship Scheduling
and Inventory Management
Vikas Goel, Marla Slusky, Willem-Jan van Hoeve, Kevin
Furman, Yufen Shao
We present a constraint programming approach for the optimization
of inventory routing in the liquefied natural gas industry. We present
two constraint programming models that rely on a disjunctive scheduling representation of the problem. We also propose an iterative search
heuristic to generate good feasible solutions for these models. Computational results on a set of large scale test instances demonstrate that
our approach can find better solutions than existing approaches based
on mixed-integer programming, while being 4 to 10 times faster on
average.
HE-31
1 - Better Excel Optimisation using OpenSolver &
SolverStudio
Andrew J Mason
Excel is an ideal tool for teaching & delivering optimization models.
We present two free packages that improve Excel’s optimisation capabilities. OpenSolver, http://opensolver.org, is an open-source LP/IP
solver that solves large Excel models using the COIN-OR Cbc solver.
SolverStudio, http://solverstudio.org, allows modelling languages such
as AMPL, GAMS, PuLP or COOPR/Pyomo to be easily used within
Excel to specify and solve advanced optimisation models. SolverStudio also supports Gurobi models, the SimPy simulation environment,
& cloud-based solving via NEOS.
2 - Dip and DipPy: A Decomposition-based Modeling
System and Solver
Ted Ralphs
DIP is a framework for implementing decomposition-based algorithms
for solving mixed-integer linear programs. The latest release includes a Python-based modeling language and a fully generic, parallel
decomposition-based solver that the user can customize with callbacks
for cut and column generation written in Python. We review the framework and give computational results on a variety of instances.
3 - CmplServer - An Open Source Approach for Distributed and Grid Optimization
Mike Steglich
CMPL can be used with the CMPLServer which is an XML-RPCbased web service for distributed optimization. After an overview of
the main functionality, the XML-based file formats for the communication between a CMPLServer and its clients are described. Since
a CMPL model can be solved on a CMPLServer synchronously and
asynchronously, both modes are explained in the next step. Furthermore, it will be discussed how CMPLServers from several locations
can be coupled to one "virtual CMPLServer", how a client can connect with it and how optimization jobs are coordinated within the CMPLServer grid.
HE-31
Thursday, 16:00-17:30 - Room 013
Location Problems in Networks
Stream: Telecommunications and Networks
Contributed session
Chair: Ivana Ljubic
1 - A Column Generation Approach for Modelling Deployment of Multi-Tier Cloud Services
Anders N. Gullhav, Bjørn Nygreen
In the provision and deployment of cloud services, the provider must
take decisions on where to place the virtual machines of the services,
but also decide on the amount of resources allocated the services such
that the quality of service is in accordance with the end-users’ requirements. In this work, we compare two model formulations of the problem: a direct formulation and a column generation formulation. The
results show that the column generation formulation provides better
solutions more quickly than the direct formulation.
2 - The Cycle Hub Location Problem
Moayad Tanash, Ivan Contreras, Navneet Vidyarthi
HE-30
Thursday, 16:00-17:30 - Room 012
Open Source & COIN-OR Optimisation
Stream: Open Source Optimisation
Invited session
Chair: Ted Ralphs
In this talk we present the Cycle Hub Location Problem, in which the
set of hubs have to be located and connected by means of a cycle. We
present a general family of mixed-dicut inequalities for a flow-based
formulation which are very useful to improve the LP bounds of this
formulation. These inequalities are embedded into a branch-and-cut
method to optimally solve the problem. We also propose a GRASP
metaheuristic to efficiently obtain high quality solutions for large-scale
instances. Computational results on instances with up to 100 nodes are
reported and analyzed.
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3 - Exact Approach for the Generalized Regenerator Location Problem
Xiangyong Li, Yash Aneja
We study the generalized regenerator location problem (GRLP) where
we are given a set S of candidate locations for regenerator placement
and a set T of nodes required to communicate with each other. This
problem is to find a minimal number of nodes for regenerator placement, such that for each node pair in T, there exists a path of which
no subpath without internal regenerators has a length greater than the
limit d. We present a formulation, discuss the facial structure, and develop branch-and-cut algorithms for the GRLP. Computational results
are presented to evaluate the proposed methods.
4 - The Recoverable Robust Facility Location Problem
Ivana Ljubic, Eduardo Álvarez-Miranda, Elena Fernandez
In this facility location problem, we search for a first-stage solution
which is robust against the possible realizations of the input data that
are revealed only in a second stage. Instead of looking for a solution
that is robust against all possible scenarios (which is the case for many
classical robust optimization approaches) we want a solution robust
enough so that it can be "recovered" promptly and at low cost in the
second stage. A Benders’ decomposition approach, incl. dual lifting
and zero-half cuts is proposed and tested on a set of carefully designed
realistic instances.
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Thursday, 16:00-17:30 - Room 014
Supply Chain Optimization
Stream: Production Management & Supply Chain
Management
Contributed session
Chair: Danny Segev
1 - Factory-Crane-Scheduling and Online Optimization
with Lookahead
Jan Necil, Stefan Nickel
We consider a system of factory cranes operating in a continuous casting plant of a steel mill. There are five cranes operating on one lane.
Due to physical reasons, some of the cranes can pass each other under
certain conditions. Our task is to compute a detailed schedule for the
cranes, in such a way that all orders can be processed on time and with
minimal effort. In practice this problem has a strong online character. Apart from the static optimization problem several questions arise:
What is the optimal lookahead? How often should the algorithm adapt
to the current situation and replan?
2 - Improving the Production Decision Making Process
of Frozen Foods Using Mathematical Modelling
Rodrigo Antonio Sánchez Ramírez, Carolina Urzúa
Managing the food supply chain is a complex process due to the perishable nature of products, where quality deterioration increases as time
passes that the product is consumed. For this reason, it is important
that the steps involved in the chain are made in a coordinated manner,
avoiding delays that reduce quality and cause product losses. For this
purpose, we developed a mixed linear programming model for planning the production of frozen berries, which seeks to reduce losses and
minimize operating costs in packing plants.
3 - A Quasi-PTAS for Assortment Planning with Nested
Preference Lists
Danny Segev
We address a fundamental question raised by Goyal, Levi, and Segev
(2009) regarding assortment planning under dynamic substitution,
with nested preference lists. Here, eps-optimal solutions consisting
of roughly 1/eps products were shown to exist, assuming an IFRdistributed number of customers. This leads to an approximation
scheme via direct enumeration. Without the IFR assumption, the general problem is wide open. I will present a new approach to compute
eps-optimal assortments without probabilistic assumptions, based on
approximate DP, condensed distributions, and some additional tricks.
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Thursday, 16:00-17:30 - Room 015
Hyperheuristics: General; and Related
Topics
Stream: Hyperheuristics
Invited session
Chair:
Chair:
Chair:
Chair:
Andrew J. Parkes
Patrick De Causmaecker
Daniel Karapetyan
Shahriar Asta
1 - Parameter Sweep for the Simplex Method
Péter Tar, József Smidla, István Maros
Optimization software systems capable of solving large-scale linear
programming problems have a wide range of parameters. These parameters are crucial for the performance of the solution algorithm; they
heavily affect speed and accuracy. In order to provide the rules of a
good parameterization we have implemented our own linear programming solver in a workflow on a desktop grid system for a parameter
sweep. Our results are very promising and can be used as a guideline
for parameterizing LP systems. „This publication has been supported
by the project TÁMOP-4.2.2.C-11/1/KONV-2012-0004"
2 - Competition Winning Hybrid Heuristic for an Extension of the Resource-Constrained Project Scheduling Problem
Daniel Karapetyan, Shahriar Asta, Ahmed Kheiri, Ender
Özcan, Andrew J. Parkes
This talk presents the algorithm winning the MISTA 2013 Scheduling
Challenge. Our approach is a hybrid heuristic addressing an extension
of the resource-constrained project scheduling problem. It comprises
a Monte-Carlo tree search technique, very large scale neighbourhoods,
meta- and hyper-heuristics and highly optimised schedule generator.
Finally, the algorithm effectively exploits the features of the problem.
We discuss the main components of our method as well as insights into
the success of the approach.
3 - A Simulation Approach to Analyse Rail Capacity at
Sydney’s Port Botany
Pascal Van Hentenryck, Daniel Guimarans, Daniel Harabor
We employ a simulation approach to analyse the operations of
container-freight trains in and around Sydney’s Port Botany. Our objective is to evaluate the current performance of rail, as well as investigating the peak rail capacity of both current and proposed infrastructure. Contrary to popular perceptions, we found that there exists significant unrealised capacity at the port and achieving it depends only
on operational changes. Moreover, proposed infrastructural upgrades,
including a centralised terminal and duplication of some track, appear
to yield little benefit over the medium term.
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Thursday, 16:00-17:30 - Room 016
Decision Making in Finance
Stream: Decision Making Modeling and Risk Assessment in the Financial Sector
Contributed session
Chair: Tomás Tichý
Chair: Stewart Robinson
1 - Average Time Until First Income Protection Claim
Isabel Cordeiro
In this paper we calculate the average time until first claim for different
deferred periods and ages at which policies are effected. These times
are calculated using the most recent graduations of the transition intensities defined for a multiple state model for Income Protection (IP)
insurance. We compare these average times with similar times calculated with graduations for an earlier period. All this information can
be very useful for insurance companies selling IP policies.
IFORS 2014 - Barcelona
2 - Analysis of integer programming approaches for index tracking
Jose Mauricio Brasil Goncalves, Eduardo Uchoa
Stock indices are indicators of the average performance of a stock market. Some funds seek to replicate this performance, adopting a policy
of "follow the index". While it could simply acquire all the stocks
according to their index proportions, this could be too costly. Alternatively, a mathematical model can be used for selecting a small
subset of the stocks that still yields a performance similar to the index. This paper presents extensive comparisons of the practical performance of three different integer programming models on tracking
indexes as Bovespa, S&P500, Hang Seng and DAX.
3 - Efficiency Measurement of investment profiles of
Savings Funds using DEA
Arik Sadeh
The long term savings is considered to be a safe, stable and with a relatively low return. This savings is intended for retirement years. In an
applied DEA research, a series of 100 long term savings funds available in capital markets are investigated. Their investment policies are
compared with respect to several quantitative financial indices. The results show that small funds are more efficient than large funds. There
is a strong positive correlation between the rate of investment in stocks
and funds’ return. On the other hand the investment in stocks does not
lead to efficiency.
4 - Risk Assessment of Energy Performance Contracting (EPC) projects of the Russian Energy Service
Companies
Maria Garbuzova-Schlifter, Reinhard Madlener
The current development of the Russian ESCOs industry is rather slow
and most of the ESCOs lack the expertise and experience for an effective risk management of Energy Performance Contracting (EPC)
projects. Due to this perception, we interviewed several Russian experts and identified the relevant risk factors of EPC projects in three
sectors: industrial, state-financed, and multifamily housing. In order
to quantify these risk factors, we conducted a questionnaire-based survey among 230 companies with EPC related businesses in Russia by
applying the Analytical Hierarchy Process (AHP) method.
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computationally prohibitive problem sizes. We develop a mathematical reformulation for the two-stage problems whose size is polynomially bound to the problem size, but can implicitly obtain the worst-case
performance among the extreme scenarios which are exponentially
many. Numerical experiments for well-known applications showing
the efficiency of the proposed method will be also given.
3 - A Study on Dual-Command Operations in a Mobile
Rack (AS/RS)
Amine Hakim Guezzen, Amina Ouhoud, Sari Zaki
In this paper our interest is concerned with the mathematical modeling of dual-command operations in a Mobile rack Automated Storage
and Retrieval Systems (M- AS/RS). The S/R machine could operate
either in single command or in dual command. In a dual command,
the S/R machine executes a storage operation followed by a retrieval
operation in the same cycle. We developed a closed form analytical
expression allowing an approximate calculation of the travel time of
a Mobil Racks-AS/RS. This expression was compared with an exact
discrete expression developed previously by one of the authors.
4 - Maintenance Policies for A System Subject to Continuous Time Markovian Deterioration with Non-SelfAnnouncing Failures
Büşra Keleş, Salih Tekin, Onur Bakir
In this study, we comparatively evaluate various maintenance policies
for systems subject to continuous time Markovian deterioration which
may result in non-self-announcing failures. The decision maker inspects the system periodically at the decision epochs, identifies the
current state; good, poor, failed and chooses an available action; donothing, repair, replace. When the system fails, failure will not be
detected until the next inspection epoch. We provide a numerical example to analyze the effect of various cost parameters on the optimum
inspection period and policy.
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Thursday, 16:00-17:30 - Room 132
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Forest Value Chain Optimization
Planning and Control
Stream: OR in Agriculture, Forestry and Fisheries
Invited session
Thursday, 16:00-17:30 - Room 131
Stream: Stochastic Modeling and Simulation in Engineering, Management and Science
Invited session
Chair: Erik Kropat
Chair: Silja Meyer-Nieberg
Chair: Rudi Verago
1 - Power-Aware Routing
Defined Networks
Wenguo Yang
Algorithms
in
Software-
The feature of centralized network control logic in Software-defined
networks (SDNs) paves a way for green energy saving. In this paper, we study global power management optimization at whole network level with consideration of network reliability by rerouting traffic through different paths to adjust the pave of links when the network
is relatively idle. A 0-1 integer linear programming model is formulated and two algorithms, i.e., alternative greedy algorithm and global
greedy algorithm, are proposed. Simulation results show the effectiveness of our algorithms.
2 - An Extreme-Case Scenario Approach for Data Uncertainty
Rudi Verago, Chungmok Lee, Martin Mevissen, Nicole Taheri
We propose a novel mathematical approach for problems with uncertain right-hand-side data in the constraints. Traditional stochastic approaches often require a large number of scenarios, which results in
Chair: Marc McDill
1 - Routing and Transportation at the Forest Industry
Mikael Rönnqvist, Patrik Flisberg, Marc-André Carle
We describe two transportation applications for a large forest company
in Canada. One deals with tactical planning of wood chips between
sawmill and paper and pulp mills. Special consideration must be taken
into account for the production and assortment mix at the mills. The
second deals with detailed truck routing of lumber between sawmill
depending on their capacities for drying and planning. Many practical and complex restrictions must be dealt with. We report on savings
when comparing manual and optimized plans.
2 - Role of Optimization in Medium to Short-Term Planning of Forest Operations
Bruno Oliveira, Alexandra Marques, Mikael Rönnqvist,
Sophie D’Amours
This presentation focuses on the forest management decisions concerning medium- and short-term forest planning. Firstly, the scope of forest
tactical and operational planning (FTOP) is bounded by comparison
with strategic planning. A classification framework for FTOP problems is presented. Then, the results of a thorough literature review
identify the solution approaches commonly used for FTOP. Lastly, the
research needs are discussed.
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IFORS 2014 - Barcelona
3 - "More than the Sum of its Parts?" — Enhancing Optimisation for the Forest Based Value Chains by Integrating Process Specific Optimisation Solutions
Johannes Scholz, Jussi Rasinmäki, Alexandra Marques,
Christian Rosset, Germano Veiga
The state-of-the-art in optimisation for forest-based value chains is to
target specific processes along the supply chain, but optimisation covering the whole supply chain is a rarity. The objective of the FOCUS
project is to address this issueand develop solutions based on pilot
cases in several countries across Europe for supply chains covering
end products timber, pulp & paper, bioenergy, and cork. This article explores the proposed distributed system architecture for coupling
independent process specific optimisation solutions as an integrated
system for supply chain wide optimisation.
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Thursday, 16:00-17:30 - Room 017
Advances on Recovery Inventory
Management Policies II
Stream: Recovery Inventory Management Policies
Invited session
Chair: Andrés Acevedo
1 - Optimal Ordering Policies and Sourcing Strategies
with Supply Disruption
Ke Liu
We discuss a model to facing of demand uncertainty and supplier reliability uncertainty at the same time in a single selling season. In the
model, we have two instants to order from two suppliers: the unreliable supplier’s reliability is uncertain at instant 1 and is completely
observed at instant 2. We present the optimal supplementary order
quantities with the realized reliability and give the optimal ordering
policies and sourcing strategies at instant 1 under certain conditions.
2 - A Multi-Criteria Collaborative Model for Flood Preparedness
Oscar Rodriguez-Espindola, Pavel Albores, Christopher
Brewster
Given the increasing trend of people affected by disasters globally,
this research will introduce a bi-criteria preparedness model aiming
to maximize the service provided to people affected by floods while
making efficient use of resources. The multi-commodity optimization
model encompasses the use of resources for multi-agency collaboration in facility location, stock pre-positioning and service allocation to
satisfy the immediate needs of affected people. The model is solved to
obtain the Pareto frontier seeking to show its application and to provide
conclusions about its performance.
3 - Production Planning with Perishable Raw Material
Considerations
Andrés Acevedo, Ivan Contreras, Ming Yuan Chen
In many types of industries, it is common to face significant rates of
product and/or raw material deterioration. These items are referred to
as perishable products. In this study, we discuss about various ways
in which perishability can occur in production processes and how this
aspect enforces specific constraints on a set of different management
decisions. We also propose new modeling approaches to manage product and raw material perishability in production planning problems.
Numerical results on a set of instances are reported.
4 - Optimizing the Collection Period of Product Returns
in a Closed-Loop Supply Chain
Nizar Zaarour, Emanuel Melachrinoudis, George Kozanidis
We consider the problem of the collection of returned products from
consumers and their shipping to manufacturers through initial collection points under freight quantity discounts. The optimal collection
period is sought in order to minimize the total inventory carrying costs
and shipping costs. Both deterministic and probabilistic models are
proposed and solution algorithms are developed.
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Thursday, 16:00-17:30 - Room 214
Multi-Criteria Performance of Funds and
Banks
Stream: Operational Research and Quantitative Models in Banking
Invited session
Chair: Enrique Ballestero
Chair: Mila Bravo
1 - Multicriteria Approach to Bank Credit Scoring
Enrique Ballestero, Sonia Zendehzaban
A Weighted Goal Programming is proposed to help bank managers
score credit applications, especially concerning with interest rates. Criteria are guarantees, profile and projects of the applicant, accounting
performance, and others. Preferences of the bank manager for these
criteria are elicited by Analytic Hierarchy Process. An example in
Spain is numerically developed. Potential extensions are: (a) to consider credit characteristics other than interest rates; and (b) to fix prices
by companies from quality in competitive markets with product differentiation.
2 - Ranking Spanish Banks from Stress Tests: A Multicriteria Model of Moderate Pessimism
Mila Bravo, Antonio Benito, Germán Benito-Sarriá
This paper deals with a wide set of Spanish banks which should be
scored from a multicriteria perspective. Criteria are: (a) results of
stress tests defined by The European Banking Authority; (b) expectations elaborated by a Governance committee whose members are Spanish and International authorities. The multicriteria method is Moderate
Pessimism Decision Making with veto, as an objective rule which is
not colored by the analyst’s opinions and preferences. The model is
numerically applied through tables.
3 - Compromise Programming Approach to Performance of Bank Funds
David Pla-Santamaria, Javier Reig
This paper aims at evaluating performance of mutual funds managed
by banks from the investor’s preferences. To score, a Compromise Programming (CP) model is designed with an infeasible ideal representing the best in profitability and safety. Since the CP metric equal to
1 (which involves linear utility) and the infinity norm (which involves
degenerate utility) lead to inappropriate utility functions in economics,
we use the linear-quadratic metric which satisfies suitable economic
properties. The proposal can be extended to corporate performance
from accounting and stock market information.
4 - Multicriteria Approach to Socially Responsible
Funds Managed by Banks
Ana Garcia-Bernabeu, Blanca Pérez-Gladish
This paper concerns with mutual funds whose bank managers pursue
social and environmental (SRI) policies. To measure SRI levels, we
design a multicriteria technique, based on screening intensity. This
technique helps bank managers advice clients on their investments to
select investments in funds from their preferences for SRI criteria. An
actual case concerning 110 USA large cap equity mutual funds is developed for some investors’ profiles.
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Thursday, 16:00-17:30 - Room 018
Discrete Optimization I
Stream: Discrete and Global Optimization
Contributed session
Chair: Imke Joormann
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1 - Piecewise Relaxation of Fractional Powers of Linear
Fractional Terms
Rosa Iris Núñez-Serna, Juan Zamora-Mata
The mixed integer nonlinear mathematical programming problem addressed in this paper is non-convex due to the presence of fractional
powers of fractional terms in the objective function. Its solution using
deterministic global optimization techniques requires rigorous methods for obtaining lower bounds for the value of the objective function.
The impact of introduce a not equidistant piecewise relaxation scheme
of such terms for obtaining tight lower bounds is explored. The use
of the proposed strategy is illustrated in the context of efficient use of
thermal energy in industrial processes.
2 - Branch Decomposition Techniques for some Matroidal Problems
Illya Hicks
This talk gives a general overview of practical computational methods
for computing branch decompositions for matroids and their usage for
solving some combinatorial optimization on matroids like integer programming. The concept of branch decompositions and its related invariant branch width were first introduced by Robertson and Seymour
in their proof of the Graph Minors Theorem and have been generalized
for any symmetric submodular set function which connectivity functions of matroids.
3 - On the Relation of Flow Cuts and Irreducible Infeasible Subsystems
Imke Joormann, Marc Pfetsch
Infeasible network flow problems can be characterized via cutinequalities of the Gale-Hoffman theorem. Written as a linear program,
irreducible infeasible subsystems (IISs) provide a different means of
infeasibility characterization. We answer a question left open in the
literature, by showing a one-to-one correspondence between IISs and
Gale-Hoffman-inequalities in which one side of the cut is connected.
We also give a polynomial-time algorithm that computes some IIS using a single max-flow computation and show strong NP-hardness of
finding a minimal cardinality IIS in this special case.
4 - A Problem Related to the Integer Partitions
Zahra Yahi, Sadek Bouroubi
In our presentation we study the number of some kinds of nonisometric quadrilaterals inscribed in a regular n gon for which we give
a closed formula with some auxiliary results using a partition function.
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2 - Matheuristics Applications in Maritime Shipping
Stefan Voss
We describe a generic framework to apply matheuristics for combinatorial optimization. In a first part this framework is discussed using
various technologies that may efficiently be hybridized in one way or
another. Examples incorporate the idea that a metaheuristic acts at a
higher level and controls the calls to the exact approach, or that the
exact method acts as a guiding process and calls and controls the use
of a metaheuristic. Examples are provided using, e.g., POPMUISIC.
Specific results outperforming best known literature benchmarks are
provided for some problems in maritime shipping.
3 - Multicriteria Optimization for Cost-Sensitive Ensemble Selection in Business Failure Prediction
Koen W. De Bock, Stefan Lessmann, Kristof Coussement
Business failure prediction (BFP) remains a key instrument for financial decision makers. In BFP, misclassification costs are usually asymmetric and hence, expected misclassification cost (EMC) is often a
more appropriate metric to focus upon than accuracy for the evaluation and comparison of algorithms. In this study, multi-criteria optimization through NSGA-II is deployed as a meta-heuristic in ensemble
selection (ES) to produce both diverse and cost-conscious ensemble
classifiers. Experiments conducted on a large set of datasets demonstrate and benchmark the proposed technique.
4 - Adaptive Hypermedia Model for Generation of Interactive Interfaces Applied to Digital TV
Arthur Gomez, Luan Carlos Nesi
Nowadays, with the technological advances the users need for individualization in the supply and access to multimedia content. Thus, this
paper proposes a system for generating adaptive interfaces for Digital TV through a user model made with the formalism of networks
stochastic automata learning, together with a process of generating the
layout using metaheuristics. As a result, we contemplate a range of
devices, being able to follow not only a market-trend, but also socially.
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Thursday, 16:00-17:30 - Room 216
Stochastic Vehicle Routing
Stream: Stochastic Models for Service Operations
Invited session
Chair: Michel Gendreau
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Thursday, 16:00-17:30 - Room 019
Prescriptive Analytics: Smart Solutions to
Real-World Problems II
Stream: Meta-Analytics: A Marriage of Metaheuristics
and Analytics
Invited session
Chair: Stefan Voss
Chair: Stefan Lessmann
1 - Loan Recovery Modelling: Challenges for Predictive
and Prescriptive Analytics
Christophe Mues, Lyn Thomas, Mee Chi So
Under Basel II and III, banks are building models to estimate LGD,
i.e., the percentage of the loan exposure that they won’t be able to recover in the event of a loan default. Similarly, within the collections
department of the bank, predictive models are used to estimate either
the probability of a certain recovery post-default or its size, to allocate
resources and decide on the collection strategy. This talk will address
some of the challenges in building recovery prediction models and how
they may be used as inputs to a prescriptive analytics task: optimising
the collections process.
1 - Stochastic Single Vehicle Routing with Pickups and
Deliveries, Continuous Demands and a Predefined
Customer Sequence
Epaminondas Kyriakidis
We study a particular capacitated vehicle routing problem with pickups
and deliveries in which the demands for a material that is delivered to
N customers and the demands for a material that is collected from the
customers are continuous random variables. The customers are served
according to a particular order. The optimal policy that serves all customers has a specific threshold-type structure and it is computed by a
suitable efficient dynamic programming algorithm that operates over
all policies having this structure. The structural result is illustrated by
a numerical example.
2 - Single-VRP with Simultaneous Delivery and Uncertain Pickup Data
Nadine Wollenberg, Michel Gendreau, Rüdiger Schultz
In this talk we will present an exact algorithm for a stochastic extension
of the VRP with simultaneous delivery and pickup. The quantities to
be delivered are fixed, whereas the quantities to be picked up are given
by a limited number of scenarios. Due to possible route failures, compensation strategies need to be considered. The stochastic model is
formulated as a two-stage stochastic program with recourse and solved
by means of the integer L-shaped method. To strengthen the lower
bound on the recourse cost the concept of partial routes is adapted.
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3 - The Vehicle Routing Problem with Stochastic TwoDimensional Items
Jean-François Côté, Michel Gendreau, Jean-Yves Potvin
We consider a stochastic vehicle routing problem where a discrete
probability distribution characterizes the two-dimensional size of a
subset of items to be delivered. The sizes of these items become known
when it is time to load the vehicles. A penalty is incurred if not all of
them can be loaded in a vehicle. The objective is to minimize the
sum of the routing and expected penalties. The problem is modeled as
a two-stage stochastic program and solved with the integer L-shaped
method. Some new inequalities and lower bounds are proposed. Computational results are reported on new instances.
4 - A Priori Optimization with Recourse for the Vehicle Routing Problem with Hard Time Windows and
Stochastic Service Times
Fausto Errico, Guy Desaulniers, Michel Gendreau,
Louis-Martin Rousseau
The VRPTW-ST differs from other routing problems with stochastic
times for the presence of hard time windows. We model the VRPTWST as a two-stage stochastic program and define two recourse policies
to recover first stage infeasibility. We solve the VRPTW-ST by exact
branch-cut-and-price algorithms. Our development included finding
tight bounds on partial route reduced costs to efficiently prune dominated labels in the column generation subproblem. Results on benchmark data show that our methods are able to solve instances with up to
50 customers for both recourse policies.
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time, the value of utility functions deteriorate over time, and decision makers could examine information once before making a decision.
Moreover, the model describes human behavior under the assumption
of "Bounded rationality", by suggesting that a decision maker sticks to
a rigid decision rule. The model sets an analytical framework for an
adaptation process of a decision rule over time.
4 - Decision Making and the Big Data Era
Fatima Dargam
Currently data heavily, constantly, and globally flows into all areas of
our economy. Individuals and mainly organizations have to tackle
the problem of processing large data in support of their respective
needs and operations, aiming at improving their manageability and efficiency. Big Data urges for advances in technology and cannot count
anymore with classical database tools to manage and analyze information data-sets. This work positions the importance of Decision Making
and DSS to exploit Big Data analysis so that organizations can get
ready to compete with high productivity.
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Thursday, 16:00-17:30 - Room 217
Scheduling Problems in Water
Distribution System Management
Stream: OR in Water Management
Invited session
Chair: Maddalena Nonato
Thursday, 16:00-17:30 - Room 215
Decision Analysis & Decision Making
Approaches
Stream: Decision Support Systems
Invited session
Chair: Isabelle Linden
Chair: Shaofeng Liu
1 - Use of Contabilometria as a Decision Making in the
Sector Accounting in VL Technology Company LTDA
the Municipalities Princesa Isabel - PB
José Jefferson Marques de Sousa
The Contabilometria is a new area of accounting knowledge, that seeks
the application of quantitative methods in the solution of financial
problems, which can be seen as a provider of tool information. Within
this context, the aim of this study was to identify what improvements
the use of Contabilometria brings to the accounting information to support the management process, the Company VL TECHNOLOGY LTD
in the town of Princesa Isabel- PB. We conclude that the Contabilometria enables the use of accounting data, such as information tool designed for the future.
2 - Using the Analytic Hierarchy Process Decision Analysis to Better Understand Consumers Intentions to
Revisit a Green Hotel
Chiao-Chen Chang
The purpose of this study was to examine the influencing factors of
green hotel revisiting intentions from a hotel perspective. The survey
data were conducted from a selection of green Taiwanese hotels, and
were analyzed by the analytic hierarchy process (AHP) decision analysis to explore revisiting intentions in the context of green hotels. The
results of the AHP decision analysis revealed that "communication and
involvement" and the "green commitment of top managers" were the
most important factors for green hotels from a hotel’s perspective.
3 - Timing and decision making
Gil Greenstein
This research presents a model and an analysis of timing aspects of decision making under uncertainty. The model is built under the following assumptions: information resources become more accurate over
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1 - A Practical Approach for Large Scale Optimal Pump
Scheduling with Operational Constraints
David Raz, Ariel Daliot
Optimizing the operation of water distribution systems through
scheduling of pumps with operational constraints, to minimize energy
costs, usually results in highly nonlinear or mixed integer optimization problems which are impractical for large setups, especially where
near real-time operation is required. We propose an approach to solve
this problem, involving an iterative heuristic and a linear programming
model. The approach is demonstrated and evaluated on a practical
setup. An extension for the case of cost structure involving multiple
suppliers and aggregative costs is also presented.
2 - The Operational Costs Minimization in Water Supply
Systems (WSS) Using Cascade Optimization Techniques
Bernardete Coelho, António Andrade-Campos
Operational costs in WSS constitute a large quota of the global costs.
Pumps control optimisation can provide considerable improvements on
the WSS efficiency since, most of the times, their operation reveals to
be inefficient. A methodology to optimise the speed and the operating
time of variable-speed pumps is proposed. For the automatic application of such methodology in distinct WSS, a numerical tool combining
EPANET 2.0 with an optimisation module was developed. Sequential
optimisation techniques are applied to benchmarking networks, which
are also tested with each algorithm individually.
3 - Path Relinking and MILP Hybridized Genetic Algorithms for Scheduling Countermeasures to Contamination Events
Maddalena Nonato, Andrea Peano, Marco Gavanelli
Once a drinking water network is contaminated, teams of technicians
are dispatched on site to close valves and open hydrants to deviate water flow, isolate contaminated sectors, and expel contaminated water, so
that the volume of consumed contaminated water is minimized. The
schedule of these operations has a great impact on such volume, but
realistic solutions must take into account the team traveling time from
one site to the next. We present a genetic algorithm hybridized with
Mixed-Integer Linear Programming and enhanced by path-relinking.
Computational results on realistic data are shown.
IFORS 2014 - Barcelona
4 - Simulation Optimization Approach
Scheduling in Water Networks
Joe Naoum-Sawaya
for
Pump
We present a simulation optimization appraoch for the pump scheduling problem in water networks. The proposed approach combines
CPLEX and EPANET simulator. CPLEX is used to efficiently find
candidate pump schedules that are then evaluated for cost and feasibility using EPANET. The proposed approach overcomes the difficulty
of using the typcial nonlinear equations that model the hydraulics of
water networks. Results from real water networks are reported.
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as well as the EMEP/EEA emission inventory guidebook in order to
support both energy as well as activity-based calculations. A benchmarking tool has also been developed to provide emission analytics at
company, sector, corridor, and country level.
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Thursday, 16:00-17:30 - Room 219
Location Problems / Supply Chain
HE-44
Thursday, 16:00-17:30 - Room 218
Optimization Practices for Sustainable
Community Development
Stream: Quality and Performance Measurement in Humanitarian Relief Chains
Invited session
Chair: Sadia Samar Ali
Chair: Gerhard-Wilhelm Weber
1 - Energy:
Environmental Impact and Economic
Growth in Developing Economies (Nigerian experience); An Operational Research Approach
Aniefiok Udo, Kingsley Imoh
Economic growth requires larger inputs of energy and materials and
these generate larger quantities of waste by-products. Increased extraction of natural resources, accumulation of waste and concentration
of pollutants will overwhelm the carrying capacity of the biosphere
and result in the degradation of environmental quality. Are there tradeoff between economic growth and environmental quality? This paper
attempts to answer this question using systematic econometric technique. It reveals that energy promotes economic growth, environmental degradation; therefore, energy efficiency is needed.
2 - Industrial Heritage and Educational Polygon for Development Strategies
Vladimir Hain
Industrial heritage provides one of the most important records on development during the last two centuries. Currently, it is a complex
multidisciplinary and multi-criteria societal problem with a dynamic
process of future development. Educational Polygon is a model and
operational tool, to stimulate social, economical and political decisions
for the purpose of protection of heritage in a new creative way. By application of "polygonal method" and OR we can effectively learn and
explore new values in order to educate the general public and develop
city in the spirit of local cultural diversity.
3 - Closed-Loop Supply Chain Decision Models with
Trade-in
Zhaowei Miao
Three kinds of closed-loop supply chain decision models with trade-in
are developed in this paper, including the centralized return model (C),
the retailer return model (R), and the manufacturer return model (M).
By Stackberg game, we find under different conditions of parameters,
there may exist three kinds of optimal return strategies, i.e., no return,
partial return, and full return. Moreover, for the profits obtained by the
manufacturer and the whole supply chain system, Model C dominates
Model M and Model M dominates Model R; for the retailer’s profits,
Model M is dominated by Model R.
4 - Carbon Footprint Calculation and Monitoring in
Freight Transport Operations: A Systemic Approach
Vasileios Zeimpekis, Konstaninos Mamasis, Dimitris Drosos,
Ioannis Minis
Stream: Hybrid Heuristics
Invited session
Chair: Nader Azizi
1 - A Comparison of Heuristics Approaches to the Reliability Redundancy Allocation Problem
Edward Pohl, Thomas Talafuse
The Redundancy Allocation problem (RAP) involves selecting the optimal combination of components and redundancy levels to maximize
system reliability subject to a variety of constraints such as weight,
volume, and cost. This problem has been shown to be NP-hard in the
literature. The use of genetic algorithms and ant colony optimization
(ACO) has been shown to be effective for this problem. In this talk
we compare the performance characteristics of an ACO on the RAP
with those of a particle swarm optimization algorithm and the recently
developed bat-inspired algorithm.
2 - A Hybrid Genetic-Simulated Annealing Algorithm for
the Supply Chain Network Design
Beyzanur Cayir, Bilal Ervural
The structure of SCN problems are combinatorial and NP hard. In this
study the problem has a non-linear structure and an optimum solution
could not be found in a polynomial time with using exact algorithms.
To solve this NP-hard problem, an effective hybrid genetic simulated
annealing algorithm is developed. This paper proposes a new Hybrid
Genetic and Simulated Annealing Algorithm to find the set of optimal solutions for the multistage SCN design problem. Computational
results show that the hybrid algorithm achieves a better solution than
produced by simulated annealing or genetic algorithm.
3 - A Hybrid Particle Swarm Optimization with Genetic
Mutation for the Supply Chain Network Design
Bilal Ervural, Beyzanur Cayir
In this study, to solve such a hard SCN design problem a hybrid particle swarm optimization algorithm that uses the mutation process of
GA to improve the basic particle swarm optimization (PSO) algorithm
is proposed. The main idea of the hybridPSO is to combine the particle swarm with genetic algorithm mutation operator. Consequently,
the proposed hybrid algorithm has balance capability between global
and local searching. The validity of the hybridPSO algorithm is tested
and compare with basic PSO. Computational results show empirically
that the proposed hybrid method outperforms significantly
4 - Hub-and-Spoke Network Design with Reliability Consideration: A Particle Swarm Optimization Approach
Nader Azizi, Said Salhi
Many enterprises including airlines and package delivery companies
have adopted the topology of hub-and-spoke for their networks. In
such networks, even a minor disruption in hubs may lead to significant
revenue loss as well as customer dissatisfaction. To maintain network
operations following an unexpected hub failure, we propose new models to consider a backup facility for each demand point in the network.
Due to complexity of the problem, two particle swarm optimization
algorithms are developed to solve some problem instances.
To meet the EU carbon targets for 2020, it is required to reduce CO2
emissions from transport operations substantially. To this end, we
present a web-based platform for carbon footprint calculation that can
be used by shippers, carriers, 3PL providers, and forwarders that operate in PECs IV, V and VII. The platform adopts the EN 16258 standard
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FA-01
IFORS 2014 - Barcelona
Friday, 8:30-10:00
FA-01
Friday, 8:30-10:00 - Room 118
Network Capacity and Utilization
Stream: Railway and Metro Transportation
Invited session
Chair: Leo Kroon
1 - Simultaneous Network Expansion and Global Frequency Setting on Railway Systems
Francisco Lopez-Ramos, Esteve Codina, Ángel Marín
This work presents a mathematical model which integrates the railway network expansion (RNE) and frequency setting (FS) phases. The
RNE builds the new lines considering a set of points that can work either as stations or just as pass-through points, whereas the FS assigns
vehicles and frequencies to the whole railway lines while meeting capacity constraints. The model is applied to two real-sized underground
networks and is solved by means of a Specialized Benders Decomposition which takes advantage of some state-of-the-art enhancements as
well as some ad hoc techniques.
2 - Allocating the Railway Capacities to Extra Trains
Soon-Heum Hong, Bum Hwan Park
We suggest an optimization model and a column generation based approach to allocate the residual railway capacities to extra trains. Our
model considers a railway network where the various kinds of rolling
stocks are operated together which needs the model capable of separately setting the operational allowances for the shift of times to
each train type. For our model, we developed a solution approach to
combine a generic column generation with a heuristic for diversified
columns and faster convergence. Finally, we present some experimental results applied to the Korean railway network.
3 - The Application of Complex Structures to the Analysis and Design of Railway Networks
Juan A. Mesa, Gilbert Laporte, Alicia De Los Santos Pineda
In this presentation we will see how hypergraphs, hypernetworks, linear and primal graphs and hyperstructures are not only useful for representing complex railway networks but also for getting insight into
properties of them such as connectivity, efficiency and robustness.
4 - Integer Programming Model for Planning Accompanied Combined Transport Operations in India
Amit Upadhyay, Nomesh Bolia
Roll-on-Roll-off (RORO) is the name for Accompanied Combined
Transport service in India. Given its resounding success in Konkan
Railway, RORO services are planned on a large scale on the dedicated
freight corridors in India. We consider peculiar operational constraints
to optimally design RORO services. We propose an integer programming model to design RORO train services with multiple handling
points and assign the demands to the trains with focus on resource utilization. Computational experiments with realistic data are presented
and show that substantial gains are possible with our model.
We propose a solution approach for the inventory routing problem that
is based on column generation. We propose a mathematical formulation based on a subset of all possible routes. For solving the mathematical model we used column generation for generating attractive routes
iteratively. We relaxed the mathematical formulation and obtain the
dual information. With the dual information we solve the subproblem
that is formulated as a shortest path problem but we generate multiple routes for each iteration. The routes added are the ones that have
negative reduced costs.
2 - A Multi-Depot Vehicle Scheduling Problem in a Public Transportation System in Quito
Luis Torres, Ramiro Torres
We propose an integer programming model to solve a vehicle
scheduling problem in a real-life public transportation system, the
METROBUS in Quito. This model is formulated as a multicommodity flow problem, minimizing the total operational cost and
the unused vehicle time at the terminals. We present a heuristic method
to obtain feasible solutions, as well as a lower bound derived from a
mincost flow relaxation. Computational results for real data with up to
1500 timetabled trips are reported, which show a remarkable potential
in resource savings with respect to the current schedule.
3 - An Unsupervised Fuzzy Clustering Approach to the
Capacitated Vehicle Routing Problem
Henrique Ewbank, Peter Wanke, Abdollah Hadi-Vencheh
This paper uses unsupervised fuzzy clustering as the cornerstone of a
proposed three-stage heuristic to solve the capacitated vehicle routing
problem with homogeneous fleet. Results for eighty-five known instances in literature indicate 5% error in average. They also suggest a
relationship between the most adequate fuzziness parameter m and the
descriptive statistics of the demands of each point and their distances
to the central depot within each instance. The neural network trained
to predict the most adequate m-parameter based on these descriptives
reported a pseudo R-squared of 90.6%.
4 - A Kind of Rollout Algorithm for N-Vehicle Exploration
Problem
Xiaoya Li
This paper studies a kind of exploration problem with N vehicles,
which is transformed to a sequential decision problem within a dynamic programming framework with complexity of factorial of N. By
introducing two types of heuristic algorithms, the author proposes a
kind of rollout algorithm that can greatly improve the performance of
the base heuristic. Numerical examples show that the rollout algorithm
using the second base heuristic always obtains the optimum, so the author discusses the relationship between rollout algorithm and optimal
algorithm of N-vehicle exploration problem at last.
FA-03
Friday, 8:30-10:00 - Room 001
Hub Location
Stream: Location
Invited session
Chair: Francisco Saldanha-da-Gama
FA-02
Friday, 8:30-10:00 - Room 111
Vehicle Routing Problems 1
Stream: Combinatorial Optimization
Invited session
Chair: Irene Loiseau
1 - A Decomposition Approach for the Inventory Routing
Problem
Carlos Franco, Verena Schmid
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1 - Hub Location with Profits
Armaghan Alibeyg, Ivan Contreras, Elena Fernandez
We present Hub location Problems with Profits, where it is not necessary to provide service to all demand nodes. A profit is associated
with each flow between pair of nodes. The goal is the simultaneous
optimization of the collected profit, the set-up cost of the hub network
and the routing cost for routing the flow. Potential applications appear
in the design of airline and ground transportation networks. Mathematical models and a unifying Lagrangean relaxation approach are
presented to solve this class of problems. Numerical results on a set of
benchmark instances are reported.
IFORS 2014 - Barcelona
2 - Formulation and Solution of an Unreliable Hub Location Problem
Trung Hieu Tran, Jesse O’Hanley, Maria Paola Scaparra
We investigate the uncapacitated single allocation p-hub location problem with independent hub failures. A mixed integer nonlinear programming model is formulated to support planners to obtain robust
optimal solutions. A linearization technique is developed to solve the
problem to optimality. Our approach is based on the use of a specialized flow network to evaluate compound probability terms. A tabu
search algorithm with parallel computing is proposed to find optimal
to near optimal solutions for large instances. Preliminary results show
the efficiency of our linearized model and algorithm.
3 - Capacitated Multiple Allocation Hub Location with
Service Level Constraints for Multiple Consignment
Classes
Sachin Jayaswal, Navneet Vidyarthi
We present a model for designing a capacitated multiple allocation hub
location problem with a service level constraint, defined using the distribution of time spent at hubs, for each of two priority classes of consignments. The network of hubs, given their locations, is modeled as
spatially distributed preemptive priority M/M/1 queues. The problem
is challenging to solve, especially in absence of any known analytical
expression for the sojourn time distribution of low priority customers
in a preemptive priority M/M/1 queue.
4 - Multi-Period Hub Network Design Problems with
Modular Capacities
Francisco Saldanha-da-Gama, Sibel A. Alumur, Stefan
Nickel, Yusuf Seçerdin
We propose a MILP modeling framework for multi-period capacitated
hub location. We include hub network design decisions and address
both the single and multiple allocation cases. Capacities are modular.
The objective is to minimize the total cost over the planning horizon
while determining, in each time period, the location and capacity of
the hubs, the allocation of the demand nodes to the located hubs, the
hub links that should operate between hubs, and the routes of flow between the origin-destination pairs. We report the results of extensive
computational tests using the CAB data set.
FA-04
Friday, 8:30-10:00 - Room 119
Strategic Traffic Planning
Stream: Traffic Flow Theory and Traffic Control
Invited session
Chair: Gideon Mbiydzenyuy
FA-06
3 - Analysing Design Alternatives for Services Based on
Intelligent Transport Systems using an Integer Linear
Optimization Model
Gideon Mbiydzenyuy
This article proposes an Integer Linear Optimization Model (ILOM)
for supporting strategic decisions related to design, implementation,
and integration of services based on Intelligent Transport Systems
(ITS). The model involves abstracting ITS services as collections of
mandatory and optional functional elements and the service value as
a collection of impacts elements. Impacts and functional elements are
abstracted to sub-elements with each abstraction layer creating hierarchical and non-hierarchical dependencies. By modeling various layers,
ITS service designs are analyzed using ILOM.
FA-05
Friday, 8:30-10:00 - Room 002
Yardside Operations
Stream: Port Operations
Invited session
Chair: Iris F.A. Vis
1 - Integrated Crane Scheduling and Yard Allocation for
Indented Berths
Iris F.A. Vis, Evrim Ursavas, Hector Carlo
Indented berths are a structural innovation in container terminals that
allow simultaneous loading and unloading of vessels from both sides.
Recent indented berth implementations have been limited by special
requirements and challenges for the management of quay cranes and
the yard area. In this study, a mixed integer programming model tackling the problem of scheduling quay cranes and the yard allocation is
formulated. The model is tested using real and internally generated
data.
2 - Container Yard Template Planning under Uncertainty
Lu Zhen
A yard template determines the assignment of spaces (subblocks) in
a yard for arriving vessels. The fluctuation of the demand for freight
transportation brings new challenges for making a robust yard template
when facing uncertain maritime market. A model is proposed for yard
template planning with considering random numbers of containers that
will be loaded onto vessels that visit the port periodically. Traffic congestions in the yard and multiple cycle time of the periodicities for
vessel arrival patterns are also considered in the model. Moreover, a
meta-heuristic method is developed.
1 - Estimation of European Freight Logistics Network
Using an Integrated Multistage Logistics Network
Model
Ronald Halim, Lorant Tavasszy
3 - White Box Optimization of Container Transport Planning
Bart Van Riessen, Rudy Negenborn, Rommert Dekker
While there are many logistic models developed to design the global
production networks of individual firms, there are very few models developed to estimate the international freight network in a region. This
research puts forward an integrated multi-stage logistic model used to
estimate the European freight network. In particular, the model estimates 1) the number and locations of the distribution centers in Europe
2) the freight transportation network between the ports, DCs and consumption regions. Using an evolutionary metaheuristic, a promising
estimation of the network has been generated.
An integral approach of the routing of inland container transportation
is vital in order to maintain reliable and sustainable inland connections.
We propose an online method for allocating incoming transport orders
directly to available inland services, resulting in a stable solution without the necessity of continuous planning updates. In our research we
use a supervised learning algorithm to find structural patterns in the
shadow prices of offline optimal plans. This allows a substantive analysis of the offline optimization results and translates the offline model
into online decision rules.
2 - Price of Anarchy for Non-atomic Congestion Games
with Stochastic Demands
Bo Chen, Chenlan Wang, Xuan Vinh Doan
We generalize the notions of user equilibrium and system optimum to
non-atomic congestion games with stochastic demands. We establish
upper bounds on the price of anarchy for three different settings of
link cost functions and demand distributions, namely, (a) affine cost
functions and general distributions, (b) polynomial cost functions and
general positive-valued distributions, and (c) polynomial cost functions
and the normal distributions. All the upper bounds are tight in some
special cases, including the case of deterministic demands.
FA-06
Friday, 8:30-10:00 - Room 211
Matheuristics I
Stream: Matheuristics
Invited session
Chair: M. Grazia Speranza
225
FA-07
IFORS 2014 - Barcelona
1 - A Matheuristic for the Multi-Vehicle Inventory Routing Problem
Claudia Archetti, M. Grazia Speranza, Natashia Boland
quality and cost rise. For additive separable demand functions, price
dynamics emulates quality dynamics. For multiplicative separable demand functions, price dynamics mimics cost dynamics.
The Multi-vehicle Inventory Routing Problem (MIRP) is the problem
of determining for each time of a discrete horizon the quantity to deliver to customers and the routes at minimum cost. This includes the inventory costs at all nodes and the costs of the vehicle routes. No stockout is allowed at the customers and the vehicle capacity constraints are
satisfied. We present a matheuristic where three different mathematical
programming models are embedded in a heuristic scheme. Computational results are presented for a large set of benchmark instances and
compared with state of the art results.
2 - Necessary Conditions for Optimal Control Problems
in Discontinuos Dynamic Systems
Ekaterina Kostina
2 - Upper and Lower Bounding Procedures for the Optimal Management of Water Pumping and Desalination
Processes
Sandra Ulrich Ngueveu, Bruno Sareni, Xavier Roboam
We consider the problem of water production optimization for autonomous water pumping and desalination units supplied by renewable
energy sources, designed to be a viable solution to fresh water scarcity
for remote areas. Nonlinear gyrators as well as the nonlinear efficiency
of energy and flow transfers model the mechanical-hydraulic power
conversion systems involved. We present a generic formulation and
resolution algorithms based on piecewise bounding and integer linear
programming to solve to optimality the global optimization problem of
finding an optimal energy management strategy.
3 - A Matheuristic for a Long-Haul Freight Transportation Problem: Synchronizing Resources through
Multiple Transshipment Locations
Fábio Moreira, Pedro Amorim, Luis Guimarães, Márcio
Antônio Ferreira Belo Filho, Bernardo Almada-Lobo
Cost pressure fostered a change in the logistics paradigm and transfer points are being deployed for long-haul freight transportation to
introduce extra flexibility. In this talk we address the operational planning challenges emerging from this new paradigm, which has its potential benefits at risk by the additional difficulty to simultaneously
synchronize all resources, satisfy all constraints and fulfil all customer
orders in time. In order to tackle a real-world problem we developed a
matheuristic that explores the structure of a novel MIP to deliver superior quality solutions.
4 - Kernel Search: A General Heuristic Approach to
MILP Problems
M. Grazia Speranza
The Kernel Search has been successfully applied to several MILP problems. It is a general and simple heuristic framework. The basic idea is
to consider the problem variables through the solution of a sequence of
MILP problems, each restricted to a subset of variables. An overview
of the Kernel Search will be provided. Specific heuristics will be presented for the Capacitated Facility Location Problem and for the Single
Source Capacitated Facility Location Problem. Computational results
will be shown on a large set of benchmark instances with up to 1000
facilities and 1000 customers.
FA-07
Friday, 8:30-10:00 - Room 003
Optimal Control with Applications
Stream: Optimal Control
Invited session
Chair: Gernot Tragler
1 - When Does Better Product Quality Imply Higher
Price?
Régis Chenavaz
In an optimal control framework, we model the intertemporal behaviour of the firm that sets directly product pricing and indirectly
product quality through product innovation; the production cost is
based on product quality. We analyse the conditions under which better product quality implies higher price. For general demand functions, price dynamics is ambiguous, and price may decline even if both
226
Optimal control of systems of differential equations with state dependent discontinuities are widely used to describe numerous applications
in natural sciences and engineering, where, e.g., there is a necessity
to model dynamics with different scales or with jumps. We discuss
necessary optimality conditions for optimal control problems of such
systems with special attention to the case when an optimal trajectory
slides on the discontinuity surface. This is a joint work with Olga
Kostyukova.
3 - Dynamic Information Acquisition in LQG Control
Problems
Thomas Weber, Viet Anh Nguyen
This paper provides a solution to the linear-quadratic-gaussian (LQG)
control problem with dynamic information acquisition. At each time,
the decision maker determines whether to obtain an informative signal
about the state at a chosen costly confidence. Information collection
is optimal whenever the variance of the state estimate lies above a decision threshold. Analytical expressions are obtained for the optimal
feedback control law, the optimal state-control trajectory, including the
optimal variance of the observations. Several applications in management science are discussed.
4 - Optimal Control of Violence During Insurgencies
Gernot Tragler
We present an optimal control model for popular behavior in times of
insurgencies, during which the population supports either the regime
or the insurgents. The behavior of the affected people is influenced by
the rate of violence each of the conflicting parties involved may use.
The model is discussed from the regime’s point of view, where the control variables are the intensity and targeting accuracy of violent actions
against the insurgents. The state variables describe the dynamics of
supporters of the regime and of the insurgents. Several scenarios are
discussed.
FA-08
Friday, 8:30-10:00 - Room 120
Dynamic Programming
Stream: Dynamic Programming
Invited session
Chair: Frank Ciarallo
1 - Control Loop Elements in Fluid Systems via MixedInteger Linear Programming
Philipp Pöttgen, Lena Altherr, Thorsten Ederer, Ulf Lorenz,
Peter Pelz
To optimize technical systems with a reasonable accuracy, dynamic effects during their operation have to be considered. In particular, timedependent behavior of control loop elements has to be taken into account by the optimization model. We present a mixed-integer linear
program for the optimal control problem with binary control variables
exemplified by a fluid system. This formulation allows the inclusion
of combinatorial decisions such as variation of the network topology.
Furthermore, we are able to appraise feasible solutions using the global
optimality gap.
2 - Multiperiod Multiproduct Advertising Budgeting: A
Stochastic Optimization Model
Cesar Beltran-Royo, Laureano Fernando Escudero, Huizhen
Zhang
We propose a stochastic optimization model for the Multiperiod Multiproduct Advertising Budgeting problem, so that the expected profit
of the advertising investment is maximized. The model is a convex optimization problem that can readily be solved by plain use of standard
IFORS 2014 - Barcelona
optimization software. The model has been tested for planning a realistic advertising campaign. In our case study, the expected profit of the
stochastic approach has been favorably compared with the expected
profit of the deterministic approach, providing a quantitative argument
in favor of the stochastic approach.
3 - Decision Processes in Route Following with Imperfect Information
Frank Ciarallo, Victor Middleton
We study decision processes of an agent following a route, when the
knowledge of the network is imperfect. The agent has a parallel, imperfect representation of the network. Using a multiple criteria decision
framework the agent attempts to recognize its surroundings in the actual network. The agent must reconcile what it observes as it moves
in the network with its internal representation using network topology
and other features, assess the state of progress on the route, and choose
its next actions. We evaluate the character of information and decision
parameters needed to maximize success.
FA-10
4 - Electric Power Grid Interdiction: The Value of Spare
Transformers
Javier Salmeron, Kevin Wood
We develop a new attacker-defender (AD) model for an electric power
transmission grid having an inventory of high-voltage transformer
(HVT) spares. Under various states of repair and load, the defender optimizes (i) the quick, post-attack replacement of disabled HVTs with
spares, and (ii) power flows. Global Benders decomposition, with a
mixed-integer subproblem, solves the AD model; special enumerative
techniques can help solve both the master problem and subproblem.
Computational tests demonstrate how the model could help guide inventory strategies for spares in an adversarial setting.
FA-10
Friday, 8:30-10:00 - Room 122
Timetabling
FA-09
Friday, 8:30-10:00 - Room 121
Optimization of Electric Power Networks
Stream: Technical and Financial Aspects of Energy
Problems
Contributed session
Chair: Javier Salmeron
1 - The Structural Impact of Renewable Energy Support
Schemes on Electricity Markets — A Generation Capacity Expansion Model with Ramping and Strategic
Bidding
Ingmar Ritzenhofen, John Birge, Stefan Spinler
Renewable portfolio standards and feed-in-tariffs are widely used policy instruments to promote investments in renewable energy sources.
Regulators continuously assess these instruments along the main electricity policy objectives — affordability, reliability, and sustainability
of electricity supply. We quantitatively assess these policies along
these dimensions using a long-term electricity capacity expansion
model with ramping, strategic bidding, and price-elasticity of demand.
We compare the performance of our model to existing quantitative generation capacity expansion models.
2 - Optimal Management of Distributed Energy Resources Considering Power Flow Restrictions
Guillem Vinals
A generic energy management system for hybrid AC/DC microgrids is
presented consisting of renewable and conventional generation, energy
storage and electric vehicles. To minimize costs while considering the
power system limits, bus voltages and power restrictions in the electric lines are included, as well as capability curves of electrical machines. Under these constraints a mixed-integer nonlinear problem is
obtained. To solve it, an algorithm is designed to find a feasible initial
point reformulating the problem into a convex optimization problem
and a mixed-integer linear problem.
3 - Enhanced Optimal Power Flow for Real Time Application
Konstantin Vandyshev, Dion Gijswijt, Karen Aardal
The aim of the work is to develop a modular set-up of the OPF, which
may solve large real-life models within a very short time (15 minutes). We enhance OPF with transformer tap ratio and phase shift angle
optimization, HVDC lines and shunt elements. Additional modules
are heuristic topology optimization method and security constrained
OPF. Our methodology encompasses different flexibilities for sacrificing certain accuracy in order to get solution faster. For numerical experiments we apply our methodology to a test system, which describes
6 European countries.
Stream: Timetabling and Rostering
Contributed session
Chair: Öznur Şengel
1 - A Matheuristic Approach for Solving the High School
Timetabling Problem
Arton Dorneles, Olinto Araújo, Luciana S. Buriol
In this study, we propose a fix-and-optimize heuristic combined with a
variable neighborhood descent method using class, teacher and day decompositions to solve the high school timetabling problem. The experimental results show that our approach provides high quality feasible
solutions in a short computational time when compared with results obtained with the general-purpose integer programming solver CPLEX.
We have improved best known solutions of 7 out of 12 instances from
the literature. Among them, three are new optimal solutions for classical instances that have been available since 2000.
2 - Finding Robust Timetables for Project Presentations
of Student Teams
Can Akkan, M.Erdem Külünk, Cenk Kocas
An approach to identifying robust solutions to discrete optimization
problems is proposed through a timetabling problem faced by one of
the authors. The problem requires grouping of student teams considering a set of diversity criteria and then assigning these groups to feasible
time–slots to present their projects. An MIP formulation of the problem is developed which is then solved using CPLEX. A set of solutions
provided by the solution pool feature of CPLEX are mapped to a network and well-known social network analysis metrics are then used to
identify high quality robust solutions.
3 - A Linear Mixed-integer Model and Tabu-search
Based Improvement Procedure for Realistic Examination Timetabling Problems
Lisa Katharina Bergmann, Kathrin Fischer, Sebastian
Zurheide
An exam timetable has to satisfy a vast variety of requirements to be
feasible and convenient to all involved parties. Most of the literature
on this topic only covers the basic constraints. Here, a linear model is
presented which considers many additional requirements as soft constraints. Using a penalty-approach, it is assured that timetables meet
the actual demands of teachers and students. A tabu-search approach
is used to solve a real planning situation. It leads to feasible timetables
that satisfy many of the soft requirements and thus can enhance the
students’ and teachers’ contentment.
4 - Assistant Assignment to Final Exams
Öznur Şengel, Melike Günay
In this study, we develop a system that provides a solution to assign
assistants for each final exam in universities. One of the common problems about this scheduling system is deciding the most suitable assistant when more than two overseers were recommended and there is
more than one exam in the same time slot. Through the work, we consider few assumptions and constraints, related to final exam timetable
and weekly schedule of assistants. We use a search algorithm to find
which assistant is suitable for which exam and an optimization algorithm is used to find a best solution for assignment.
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FA-11
IFORS 2014 - Barcelona
FA-11
Friday, 8:30-10:00 - Room 113
Combinatorial Optimization Applications
in Industry and Services
Stream: Combinatorial Optimization
Invited session
Chair: José Fernando Oliveira
1 - Coffee Aggregate Production Planning
Diana Yomali Ospina Lopez, Maria Antónia Carravilla, José
Fernando Oliveira
Coffee is one of the most important commodities in the world trade.
It has been marketed by two ways: green coffee beans and processed
coffee. The general coffee production process includes: storage, roasting, grinding, blending and packaging. These processes must operate
appropriately and provide accurate information to obtain the best performance. Our research aims to model the aggregate production planning in the coffee company and evaluate the influence of acquisition
strategies of the green coffee beans on both the perecibility and on the
total production cost and demand satisfaction.
2 - A Mathematical Programming Approach to Mixed
Model Assembly Line Balancing and Sequencing
Doğan Aybars İlhan, Tuğçe Hoşgör, Fadime
Üney-Yüksektepe
In this study, mixed model assembly line balancing and sequencing
problems are aimed to solve simultaneously. Balancing is to assign
tasks to workstations subject to cycle time and precedence constraints
for minimizing work overload. Sequencing is to find launching sequence of models assembled on the line by minimizing total amount
of uncompleted work. A Mixed-Integer Linear Programming model
is developed to provide the solution of the problem. The developed
model is implemented in a real life automotive manufacturer’s assembly line balancing problem by using GAMS 23.0 and CPLEX 12.0
solver.
1 - A Matheuristic Approach to Capacity Planning Problem in Mineral Supply Chains
Yakov Zinder, Joey Fung, Gaurav Singh
Determining capacity improvement initiatives to meet a forecasted demand is a crucial problem for all supply chains. The cost and long
lead-time associated with building additional infrastructure makes this
problem even more crucial for mineral supply chains. Motivated by the
recent trend of matheuristics, this paper presents a hybrid optimisation
procedure that combines MILP and metaheuristics, where both complement and guide each other towards better solutions. Computational
results using data from the world’s largest coal supply chain based in
Australia are also presented.
2 - Solving some Discrete-Continuous Project Scheduling Problems with Discounted Cash Flows
Grzegorz Waligora
Discrete-continuous project scheduling problems with positive discounted cash flows and the maximization of the net present value
(NPV) are considered. Activities are nonpreemptable, and the processing rate of each activity is a continuous, increasing and concave function of the amount of the continuous resource allotted to the activity at
a time. Three common payment models are analyzed. Formulations of
mathematical programming problems finding optimal continuous resource allocations for the payment models are presented, and a general
methodology for solving the defined problems is discussed.
3 - Scheduling Computational Jobs with Varying Power
Availability
Rafal Rozycki
We consider a problem of scheduling preemptable, independent jobs
on parallel, identical machines under an additional, continuous, renewable resource to minimize the schedule length. The considered
problem is a generalization of discrete-continuous scheduling problems, where a total amount of the resource available at a time is constant. Here we assume that this amount varies over time. The lengths
of the availability intervals, as well as the amounts (nonnegative and
constant) of the resource in each intervals are known, in advance. We
propose a general methodology for solving the problem.
3 - A Mathematical Railway Model for Allocation of
Limited-Stop Service Stations to Minimize Total
Travel Time
Hidetoshi Miura, Toshio Nemoto
4 - Simulated Annealing Approach to Metascheduling of
Workflow Applications in Computational Grids
Marek Mika
We propose a mathematical model to study allocation limited-stop service stations to minimize total travel time. Travels of users are described on a single railway model with two terminal stations and n
way stations. Travel demand between any two stations are equal and
constant over the railway model. There are two trains types: local train
stopping at all stations and a limited-stop service skipping some stations. We show an optimal allocation of limited-stop service stations
and shortened total travel time. Furthermore, the model gives the optimal number of limited-stop service stations.
Computational grid is a computing environment dedicated to execute
applications with large computational requirements. An example of
such complex application executed in grid is a workflow. It consists of
various precedence-related transformations (tasks) performed on certain data. These tasks communicate with each other in order to transfer
some data files. Usually, workflow applications are very time consuming. Thus, it is very important to allocate tasks to resources and schedule them to minimize the makespan. We use simulated annealing as a
heuristic approach in this metascheduling phase.
4 - An Agent-based Approach to Schedule Crane Operations in Rail-Rail Transshipment Terminals
Sam Heshmati, Maria Antónia Carravilla, José Fernando
Oliveira
The study considers scheduling the cranes operation in Rail-Rail
Transshipment Terminals (RRTTs) from an operational point of view,
while minimizing the total transshipment time. The study introduces
an agent-based approach for the container transshipment processes in
RRTTs where intelligent crane agents decide and plan their own schedule. The idea is to put forward an agent-based approach by systematically analyzing cranes’ behavior. Finally a comparison of the agentbased system with more traditional approaches for real-time transport
planning based on OR algorithm is provided.
FA-12
Friday, 8:30-10:00 - Room 004
Discrete-Continuous Scheduling
Stream: Scheduling under Resource Constraints
Invited session
Chair: Jan Weglarz
Chair: Yakov Zinder
228
FA-13
Friday, 8:30-10:00 - Room 123
Scheduling Applications 1
Stream: Scheduling
Invited session
Chair: Dirk Briskorn
1 - Finding Optimal Tour Plans of a Cargo Ship under
Deadline Restrictions
Stefan Bock
In this talk, the finding of an optimal tour plan of a single cargo ship
is considered. Specifically, a schedule is sought that minimizes the total sum of request waiting times at the inland ports while all deadlines
are met. This problem is equivalent to the Line-TRP with general processing times and deadlines whose complexity status has been open
for a long time. It is shown that this problem is strongly NP-hard. In
order to generate an optimal tour, a new Branch&Bound algorithm is
introduced that applies a specific enumeration scheme as well as lower
bounds and dominance criteria.
IFORS 2014 - Barcelona
2 - Scheduling Set-Up Operations in a Multi-Machine Environment when only One Set-Up Operator is Present
Daniel Schnitzler, Dirk Briskorn
There are a limited number of machines which have pre-assigned tasks.
The tasks on a machine have to be processed in a given sequence. For
each task, the machine has to be set up. Only one machine can be set
up at a given time. Different goals are pursued (e.g., reduce makespan).
Since standard solvers are only able to tackle small problems, a genetic
algorithm and a tabu search were developed, which can solve problems
with up to 100 machines and 1000 tasks. Different variants of the metaheuristics were tested with the help of random instances and instances
from which the solution is known.
FA-16
3 - Impact of Information Overload on Escalation of
Commitment
Peter Rötzel
Escalation of commitment explains why decision-makers are tempted
to reinvest further resources in a losing course of action. While previous studies focus on the quality of information, there is a lack of
research on how different information quantities affect escalation of
commitment. Our study shows how information overload influences
escalation of commitment and how information overload interacts
with the decision-maker’s earlier decisions. Our results indicate that
decision-makers who face information overload increase their reinvestment even when the decision consequences are positive.
3 - Scheduling Part Feeding from Line-Integrated Supermarkets to Mixed-Model Assembly Lines
Simon Emde, Nils Boysen
Line-integrated supermarkets constitute a novel in-house parts logistics concept for feeding mixed-model assembly lines. In this context,
supermarkets are decentralized logistics areas located directly in each
station. Here, parts are withdrawn from their containers by a dedicated
logistics worker and sorted just-in-sequence (JIS) into a JIS-bin. From
this bin, assembly workers fetch the parts required by the current workpiece and mount them during the respective production cycle. This
presentation treats the scheduling of the part supply processes within
line-integrated supermarkets.
4 - Efficient Task Scheduling in Long-Term Care Facilities
Alexander Lieder, Dennis Moeke, Raik Stolletz, Ger Koole
Care workers in nursing homes are responsible for providing services
to clients and cause the largest share of operational costs. In order
to deliver high-quality service, it is important to assign each task to a
qualified care worker and to a point in time according to the client’s
preferences. We present a dynamic programming approach that generates optimal task schedules. Using data from practice, we evaluate
the runtime performance of this approach. A sensitivity analysis shows
effects of optimal task schedules on the required workforce.
FA-15
Friday, 8:30-10:00 - Room 125
Experimental Research in Management
Accounting and Management Control 2
Stream: Experimental Perspectives and Challenges in
Management Accounting and Management Control
Invited session
Chair: Stephan Leitner
1 - Heuristic Methods for Picking Items for Experimental
Sets
Rachel Bunder, Natashia Boland, Andrew Heathcote
Psychologists are often required to create sets of items to be used in
experiments. Such sets are used to test how factors affect some situation, e.g., to see how humans respond to short words compared to
long words. These sets must ’match’, i.e., be as similar as possible,
on all other attributes that could affect response. Previously, we have
explored definitions of similarity for experimental data sets and have
developed a MIP to solve this problem, which struggles when solving
larger problems. We explore a variety of heuristic methods, comparing
the results to existing metaheuristics.
2 - The Impact of Visualizing Causal Relations on Dynamic Decision Making
Michael Leyer, Jürgen Strohhecker
According to natural decision models, good decisions are mainly dependent on understanding the consequences of chosen options. Thus,
receiving information on causal relations between options and results
should be helpful. Using a capacity management simulator, we conducted laboratory experiments with two levels of complexity in which
participants had to make decisions repeatedly. Results are showing not
only key performance indicators on the user interface but also visualizing causal relations between them leads to better decisions. The results
are stronger in the more complex situation.
FA-16
Friday, 8:30-10:00 - Room 127
Pattern Recognition
Stream: Intelligent Optimization in Machine Learning
and Data Analysis
Invited session
Chair: Ivan Reyer
1 - On Fingerprint Image Compression Method based on
NMF
Congying Han, Tiande Guo
A new method for fingerprint compression is proposed. A general
model that can be used to describe many existing algorithms, such
as PCA, SVD and NMF is given. Based on the model, a modified
NMF algorithm is used to train and compress images of fingerprint. A
large number of tests show the new algorithm is valid for fingerprint
compression. In particular, the method has a good performance for
fingerprint with small size.
2 - Short-Term Forecasting of Musical Compositions
Using Chord Sequences
Mikhail Matrosov, Vadim Strijov
The objective is to predict a sequence of chords. It is treated as multivariate time series of discrete values. A chord is represented as an array
of half-tone sounds within one octave. We utilize a classifier based on
probability distributions over chord sequences that are estimated both
on a big training set and some revealed part of the forecasted melody.
It shows robust forecasting on a set of 50 000 midi files. The novelty is
model selection algorithm and invariant representation of chords. The
same technique can be used to predict or synthesize various types of
discrete time series.
3 - Parametric Shape Descriptor based on a Scalable
Boundary-Skeleton Model
Ivan Reyer, Ksenia Zhukova
A parametric shape descriptor containing the set of convex vertices of
a polygonal figure approximating the raster image and estimations of
significance for curvature features corresponding to the vertices is suggested. The significance estimations are calculated with use of a family
of boundary-skeleton shape models generated by the polygonal figure.
Applications of the shape descriptor to face profile segmentation and
content based image retrieval are presented.
4 - Customer Loyalty in Internet Service Provider Companies
Ilayda Ulku, Mehmet Yahya Durak, Fadime
Üney-Yüksektepe
Internet is a basic standart of life and there are numerous service
providers to make people safe, they try to service best quality and
performance. Due to competition, providers try to prevent losing customer. In this research, a questionnaire is applied to get and analyze
customer information, behavior and loyalty status of the churn possibility. This study deals with existing data mining algorithms to introduce the important factors for the churn prediction.
229
FA-17
IFORS 2014 - Barcelona
FA-17
Friday, 8:30-10:00 - Room 005
Graph Searching Games
Stream: Graph Searching
Invited session
Chair: Nancy Clarke
1 - Ambush Cops and Robbers on Graphs with Small
Girth
Nancy Clarke
In this variation of the game with two robbers, the cops win by moving onto the same vertex as one of the robbers after a finite number of
moves. The robbers win by avoiding capture indefinitely or by both
moving onto the same vertex as the cop. (Otherwise, the robbers are
on distinct vertices.) We present results on graphs with small girth.
2 - Structures and Strategies in the Game of Cops and
Robber
Kerry Ojakian
This work is in-progress. In the game of Cops and Robber a graph
is called k-cop win if k cops are sufficient to catch the robber. I will
discuss two research directions. First, is there a "nice graph-theoretic"
characterization of the k-cop win graphs, one that goes beyond the existing characterization, to refer more explicitly to the structural properties of graphs? Second, if k cops play in an optimal fashion, their position should get strictly "better" with every round of play. I consider
ways to make this intuition precise. In short, we want to understand
the nature of k-cop win graphs.
3 - An Algorithmic Method for Constructing Forbidden
Minors
Oznur Yasar Diner, Dariusz Dereniowski, Danny Dyer
The edge search problem is a combinatorial game played on graphs.
Our main interest lies on the edge search number which is an invariant
that is inherited by minors. This leads to the conclusion that the set
of forbidden minors for k-searchable graphs are finite when k is fixed;
however these minimal minors are not known except for just a few initial cases. In this talk we propose an algorithm that constructs the set of
forbidden minors for diconnected k-searchable reduced series-parallel
graphs and give the entire list for each k that is less than or equal to 4.
4 - A Variable Neighborhood Search for the k-Metric Dimension Problem
Mirjana Cangalovic, Jozef Kratica, Vera Kovacevic Vujcic
For a given connected graph G a set of vertices S is a k-resolving set
if any pair of vertices of G is resolved by at least k elements of S. A
k-resolving set of minimum cardinality is a k-metric basis and its cardinality is the k-metric dimension of G. The problem of finding the
k-metric dimension of G is known to be NP-hard. For this problem
we propose a Variable Neighborhood Search heuristic with a suitable
chosen neighborhood structure and an efficient local search procedure.
Experimental results are presented on two different ORLIB classes of
graphs: crew scheduling and graph coloring.
FA-18
Mehdi Telemsani, Angel Ruiz, Patrick Soriano, Nadine
Meskens
The daily operating room scheduling is a problem with highly constrained and different objectives to optimize. We seek to both minimize
the makespan, maximizing affinities in a surgical team and balance the
specialties in which nurses will work so that they acquire enough skills
to cope with a possible unscheduled urgent operational need. Lexicographic optimization is considered in the context of block scheduling
where a daily schedule is searched to determine the sequence of operations in each operating room, taking into account physical constraints
and availability of human resources.
2 - A Multi-Objective Mixed-Integer Mathematical Model
for one Dimensional Cutting Problem
Duygu Demirci, Nergiz Kasimbeyli
In this work, a one-dimensional cutting and assortment problem is
studied. The purpose of this paper is to develop a mathematical model
without the use of cutting patterns as model parameters. We propose
a new, multi-objective linear integer programming model in the form
of simultaneous minimization of contradicting objectives related to the
total trim loss cost and the total cost of using different lengths of stock
rolls to be maintained as inventory, in order to fulfill a given set of cutting orders. We also consider to minimize the total amount of excess
demand for cutting orders.
3 - Multiple Objective Energy and Environmental Policy
Research
Şahan Yıldız, Murat Koksalan, Ebru Voyvoda
Energy policy decisions require considering multiple objectives as energy sector is closely related with economy, environmental quality and
security of energy resources. We develop a multi objective decision
support system for Turkey. We first characterize the efficient set using
maximizing total consumption, minimizing greenhouse gas emission
and minimizing imported energy cost objectives. We next investigate
the effects of policy tools such as taxing, quotas, price subsidy to reach
the policy maker’s targets. We also investigate robust policies against
external energy price shocks.
4 - An Interactive Approach to Multicriteria Multi-period
Portfolio Optimization
Ceren Tuncer Sakar, Murat Koksalan
Portfolio optimization is the problem of allocating funds between investment instruments. We use stochastic programming with scenario
trees to model a multi-period portfolio optimization problem with expected return, Conditional Value at Risk and liquidity criteria. Our interactive approach in this setting produces an increasingly concentrated
set of solutions around the decision maker’s choices in successive iterations. Rolling horizon trees are considered for decision makers whose
preferences and financial conditions change over time. We experiment
with stocks traded on Borsa Istanbul.
FA-19
Friday, 8:30-10:00 - Room 128
Bi-objective Optimization: Methods and
Applications
Stream: Multiobjective Optimization - Theory, Methods
and Applications
Invited session
Friday, 8:30-10:00 - Room 112
Chair: Vladimir Korotkov
Applications of Multiobjective
Optimization I
1 - A Lexicographic Optimization Approach to the BiObjective p-cent-dian Problem
Sune Lauth Gadegaard, Lars Relund Nielsen, Andreas Klose
Stream: Multiobjective Optimization - Theory, Methods
and Applications
Invited session
Chair: Ceren Tuncer Sakar
1 - Multiobjective Scheduling Operating Room with a
Consideration of a Balanced Allocation of Competencies of Nurses
230
The p-median and the p-center problem are two of the most widely
studied facitlity location problems. The p-median problem seeks to
place a set of p facilities in such a way the total distance from customers to facilities are minimized, thus focusing on efficiency. The
p-center problem, however, minimizes the largest distance from a customer to a facility, whereby the focus is on equity. These two of objectives will be combined in a bi-objective model, and the entire set of
non-dominated outcome vectors is computed using an algorithm based
on lexicographic branch and bound.
IFORS 2014 - Barcelona
2 - A Bi-Objective Location-Allocation Model for Intermodal Terminals
Martine Mostert, Sabine Limbourg
Intermodal transport is an efficient solution for reducing greenhouse
gases of freight transport. Intermodal transport requires intermodal terminals where the transfer between modes can occur. The location of
these terminals is a key factor for achieving economic and environmental competitiveness. We present a bi-objective model for the intermodal
terminal location-allocation problem. The focus is on road and on intermodal rail and inland waterway transportation. Operational costs
and CO2 emissions are minimized. Intermodal global performances
are assessed for the Belgian case study.
3 - Surgical Team Rostering Problem Considering Break
Windows
Christine Di Martinelly, Nadine Meskens
Considering the established surgical schedule, the objective of this research is to build surgical teams and their weekly timetable considering
breaks. The surgical teams involve different categories of personnel,
including surgeons, anesthesiologists and nurses. The mixed-integer
programming model builds nurse rosters considering their availabilities and legal constraints. We are using a bi-criteria approach that
maximizes the team affinities while minimizing the nurses’ total waiting time. The model is solved using an e-constraint approach and is
tested on instances of a Belgian hospital.
FA-21
3 - Analysis and Enhancement of Practice-based Policies for the Real Option Management of Commodity
Storage Assets
Nicola Secomandi
Practitioners manage commodity storage assets using the rolling intrinsic (RI) and rolling basket of spread options (RSO) policies. This talk
provides novel structural and numerical support for the use of the RI
and RSO policies, and enhances them by developing a simple and effective dual upper bound to be used in conjunction with these policies.
Moreover, this talk emphasizes the superiority of the RI policy over the
RSO policy and proposes an improved variant of the RSO policy.
FA-21
Friday, 8:30-10:00 - Room 006
Cutting and Packing 5
Stream: Cutting and Packing
Invited session
Chair: Andréa Vianna
4 - Stability of Bi-objective Investment Problem with Extreme Optimism and Extreme Pessimism Criteria
Vladimir Korotkov, Vladimir Emelichev, Yury Nikulin
1 - Cutting Stock Problem with Rectangular and Irregular Pieces
Andréa Vianna, Adriana Cherri
We investigate stability of the bi-objective Boolean investment problem with criteria of extreme optimism for the profit and extreme pessimism for the risk, i.e., the cases when a Pareto optimal portfolio is
chosen either with the maximum profit in the best market situation or
the minimum risk level in the worst case market situation. We obtain
lower and upper bounds on the stability radius of the investment problem that is the supreme level of initial date perturbations for which
the Pareto set in the perturbed model does not contain new efficient
portfolios.
In this work we present a study and resolution method for the cutting stock problems involving rectangular and L-shaped pieces. To
solve this two-dimensional cutting stock-problem we modify and use
the AND/OR Graph approach and a heuristic procedure. Our strategy
consists in combine rectangular and L-shaped items in plates in order to minimize the waste. To verify the performance of the proposed
strategy, computational tests were realized with examples randomly
generated.
FA-20
Friday, 8:30-10:00 - Room 129
Energy Trading
Stream: Stochastic Optimization in Energy
Invited session
Chair: Nicola Secomandi
1 - Price Determinants and their Impact on Day-Ahead
and Intraday Market Prices: Explaining the Differences
Christian Pape, Simon Hagemann, Christoph Weber
The formation of spot electricity prices is influenced by a complex interaction between different determinants. Their identification is not
straightforward and challenges researchers and decision makers in the
same way. Compared to the literature about day-ahead prices, prices in
intraday markets have not been extensively studied so far. Therefore,
the determinants in the German electricity spot markets are analysed in
this work. The target is to enhance market understanding of price determinants in electricity spot markets and to build up a basis for further
intraday price modelling.
2 - Rethinking Risk Trading in an Electricity Market Context
Edward Anderson
Forward trading takes place at various time horizons in an electricity
market context. These financial transactions are used to reduce risk for
market participants. The forward contracts also turn out to be important in determining market power. We will review the frameworks that
can be used to analyse this risk trading and show how a small number
of traded instruments in a context with private information (different
firms have different forecasts) lead to outcomes that differ from a conventional analysis.
2 - A Partition-based Heuristic Algorithm for the Largescale Rectilinear Block Packing Problem
Yannan Hu, Hideki Hashimoto, Shinji Imahori, Mutsunori
Yagiura
The rectilinear block packing problem is a problem of packing a set of
rectilinear blocks into a larger rectangular container, where a rectilinear block is a polygonal block whose interior angle is either 90 degrees
or 270 degrees. This problem involves many industrial applications.
In this paper, we propose a partition-based heuristic algorithm based
on the bottom-left strategy. The computational results show that the
proposed algorithm is especially effective for large-scale instances.
3 - Approaches to Enhance the Efficiency of Cutting
Stock for Furniture Production
Socorro Rangel
A usual criterion to solve the cutting stock problem (CSP) is to minimize total waste. When the cutting stage becomes a bottleneck in a
production process, it is important to also maximize the cutting machine productivity. A review is made of recent contributions to the
CSP with both optimization criteria, taking into account that the cutting machine productivity can be improved if plates are stacked and
cut simultaneously according to the same cutting pattern. Mathematical models and procedures to solve the problem are presented in the
context of furniture production.
4 - Integrated Cutting and Production Planning in a
Home Textile Manufacturing Company
Elsa Silva, José Fernando Oliveira, Maria Antónia Carravilla
In this paper we consider the problem of minimizing the waste of textile material, while taking into account the overall costs of the production process, in a Portuguese textile manufacturing company. Planning
production comprises different decisions: the definition of the widths
and lengths of the fabric rolls to be produced, the number of fabric
rolls to use from stock or to purchase and the definition of the cutting patterns to apply to each width of the fabric roll, so that waste is
minimised. We propose an ILP model, solved by a column generation
method, to tackle the problem.
231
FA-22
IFORS 2014 - Barcelona
FA-22
Friday, 8:30-10:00 - Room 007
Game Theory and Customer Behavior in
Service Systems
Stream: Game Theory and Service Management
Invited session
Chair: Pengfei Guo
1 - Service Systems with Boundedly Rational Customers
Tingliang Huang, Ying-Ju Chen
We study service systems where customers lack full capability or ample opportunity to perfectly infer the service quality or waiting time,
and thus can only rely on past experiences and anecdotal reasoning to
make their joining decisions.
2 - Why Queues are often too Long or Too Short? Strategic Behavior of Loss Averse Customers in a Queueing System
Liu Yang, Pengfei Guo, Yulan Wang
We consider a queueing system where customers are loss averse wrt.
a reference point determined by their recent expectations. Customers
are reference dependent in both service price and waiting time. We first
study customers’ queue joining strategies and found that in the equilibrium, the queue length is polarized compare to the case without reference effect. In particular, when the traditional predicted queue-length
is long, the actual queue length with reference effect is longer, and vice
versa. We then study a server’s pricing decision in both monopoly and
duopoly markets.
3 - Equilibrium Queueing Strategies When Service Quality is Unknown to Some Customers
Pengfei Guo, Moshe Haviv, Yulan Wang
We study customers’ queueing strategy in a one-server system given
that service quality is unknown to some customers. We consider both
unobservable and observable queues and assume that customers are homogeneous on both service reward and delay sensitivity. We find that
the effective arrival rate for servers can at times be decreasing with
the potential arrival rate. Interestingly, under certain conditions a lowquality server has a higher incentive to reveal its queue length than a
high-quality server does.
4 - Seeking Stable Flows in a Multi-Agent Network with
Controllable Capacities
Cyril Briand, Nadia Chaabane, Marie-José Huguet
A multi-agent transportation problem is considered where a set of selfish agents is able to control the capacities of a set of arcs inside a
transportation network, incurring a cost proportional to the chosen capacities. A customer agent is willing to maximize the product flow
transshipped from a source to a sink node through the network. She
offers a reward proportional to the flow the other agents manage to
provide. This reward is shared among the agents according to a sharing policy. The focus is put on finding stable strategies (i.e., Nash
equilibria) and optimal sharing policies.
FA-23
Friday, 8:30-10:00 - Room 008
Metaheuristics for Vehicle Routing
Stream: Metaheuristics
Contributed session
Chair: Kenneth Sörensen
1 - The k-dissimilar Vehicle Routing Problem
Luca Talarico, Kenneth Sörensen, Johan Springael
232
In this work we define a new problem, the aim of which is to find a
set of k dissimilar alternative solutions for a vehicle routing problem
on a single instance. This problem has several practical applications in
the cash-in-transit sector and in the transportation of hazardous materials. A min-max mathematical formulation is developed that minimizes
the objective function value of the worst solution. An iterative metaheuristic to generate k dissimilar alternative solutions is also presented
and tested using large and medium size benchmark instances for the
capacitated vehicle routing problem.
2 - A Tabu Search Heuristic for the Vehicle Routing Problem with Time Deadlines and Asymmetric Distances
Pelin Ekmen, Necati Aras, Deniz Aksen
A metaheuristic method based on Tabu Search algorithm for The Vehicle Routing Problem with Time Deadlines and Asymmetric Distances
is proposed to determine near-optimal tours by formulating a mixed
integer linear model. The algorithm is tested on randomly generated
asymmetric instances derived from the Solomon benchmark problem
instances. Two mathematical models are constructed to solve this problem. They are solved by CPLEX 12.5 solver within GAMS suite 24.0
and compared with the results obtained by the Tabu Search heuristic.
3 - An Algorithm for the Traveling Salesman Problem
(TSP) using a Heuristic Selection of the Set of Solutions Based on a Relevance Matrix
Luis Moreno, Javier Diaz, Juan Esteban Calle Salazar
Based on the known priority rule for the TSP that searches the closest
not visited neighbor for each location (myopic strategy), a deterministic algorithm is proposed that goes over the whole solution space
(permutations) in order to look not only for the solution proposed by
the mentioned priority rule, but a set of them, ordered from the best to
the worst candidate solutions according to a function defined by a relevance matrix. The algorithm is adjusted to search for only a predefined
a priori number of solutions and then a 2-opt process is applied to each
of the selected solutions.
FA-24
Friday, 8:30-10:00 - Room 212
Dynamic Stochastic Programming and
Option Pricing
Stream: Actuarial Sciences and Stochastic Calculus
Invited session
Chair: Daniel Sevcovic
1 - Value of a Firm with Suspension and Exit Options
Manuel Guerra, Cláudia Nunes, Carlos Oliveira
We consider the problem of the optimal strategy for a company that
adapts to random fluctuations in demand by suspending/restarting its
activity, having also the possibility of irreversible cessation. Activity
and temporary suspension incur specific running costs, while change in
status have specific spot costs. We discuss the structure of the optimal
strategy and present some examples.
2 - Extensions of the Barles and Soner Model for Derivatives Pricing with Transaction Costs
Pedro Pólvora
The pricing of derivatives with transaction costs is one of the most important extensions of the traditional Black-Scholes model. The Barles
and Soner model is a model to price those derivatives, initially it was
developed for an European Call option and using an exponential utility
function. In this paper we shall explore extensions of this model.
3 - A Method of Solving Hamilton-Jacobi-Bellman Equation with Constraints via Riccati Transformation
Daniel Sevcovic, Sona Kilianova
We propose and analyze a method based on the Riccati transformation
for solving Hamilton-Jacobi-Bellman (HJB) equation, arising from a
problem of optimal portfolio construction. We show how the fully nonlinear HJB equation can be transformed into a quasi-linear parabolic
equation for which we prove existence, uniqueness and derive useful
bounds of classical Holder smooth solutions. We furthermore construct
a fully implicit iterative numerical scheme based on finite volume approximation of the governing equation. We compute optimal strategies
for a portfolio investment problem.
IFORS 2014 - Barcelona
4 - Modelling Returns Distribution by Adapting the Geometric Brownian Motion: An Empirical Study for Capturing Irrational Behaviour in Finance
Muhammad Bilal Shakeel, Gurjeet Dhesi
An innovative extension of Geometric Brownian Motion model is developed by incorporating extra weighted information factors represented by mixture of power and trigonometric functions. Simulations
based on these modified models, with optimal weighting factors selected by goodness of fit tests, outperform the basic Geometric Brownian motion model in terms of fitting the returns distribution of historic
data price indices. Furthermore we attempt to provide a schematic interpretation of the weighted information factors in relation to irrational
behaviour in Finance.
FA-27
FA-26
Friday, 8:30-10:00 - Room 010
Equilibrium and Variational Inequalities
(contributed)
Stream: Nonsmooth Optimization and Variational Analysis
Invited session
Chair: Mohammed Alshahrani
1 - A Projection Method for the Constrained Equilibrium
Problem
Susana Scheimberg, Paulo Sergio Marques Santos
FA-25
Friday, 8:30-10:00 - Room 009
Various Applications of Heuristics
Stream: Applications of Heuristics
Invited session
Chair: Geir Hasle
1 - Location and Relocation Models for Wildland Fire
Planning
Amelia C. Regan, Joseph Chow
In our earlier work, a location and relocation model were proposed for
air tanker initial attack basing in California for regional wildland fires
that require multiple air tankers that may be co-located at the same air
base. Based on input from US Forest Service researchers, this work
presents several modeling and algorithmic extensions of that k-server
p-median location model.
2 - Knapsack-Based Window Frame Cutting Plan Algorithm
Byung-In Kim, Youngmin Ki
A real-life window frame cutting problem, in which four types of bars
(U, B, L, R) for each order should be cut from raw bars, is solved.
The four types need to be assigned to the same raw bar if possible;
otherwise, they should be assigned to nearby bars. Furthermore, it is
not desirable to cut the same bar type continuously (e.g., B-B-B) from
a raw bar. We develop a knapsack based heuristic for the problem to
minimize the trim loss as well as the same bar type sequence, and raw
material bar spreading degree. The proposed approach performs well
and it is being used in a real-life company.
3 - An Adaptive Iterated Local Search for the Mixed Capacitated General Routing Problem
Geir Hasle, Mauro Dell’Amico, José Carlos Díaz Díaz,
Manuel Iori
We study the Mixed Capacitated General Routing Problem (MCGRP)
in which a fleet of capacitated vehicles has to serve a set of requests
by traversing a mixed weighted graph. The requests may be located
on nodes, edges, and arcs. We propose a new Iterated Local Search
metaheuristic for the problem. Computational experiments show that
the proposed metaheuristic is highly effective on five published benchmarks for the MCGRP. The metaheuristic yields excellent results also
on seven standard CARP datasets, and good results on four well-known
CVRP benchmarks.
4 - An Optimization Based Method for Designing Road
Networks that are Robust Against Incidents
Maaike Snelder, Ben Immers, Henk van Zuylen, Bart van
Arem
In many road networks all over the world unexpectedly large delays
occur as a result of unforeseen disturbances like incidents. Robustness
measures like adding spare capacity and buffers can be taken to reduce
these delays. In this paper a robust network design method is proposed
that considers these measures. The method combines optimization and
evaluation models. An application to a test network shows the quality of the method. An application to the road network of Amsterdam
shows that large improvements in the network performance can be realised with a positive benefit-cost balance.
We consider the Constrained Equilibrium Problem, CEP, which consists in finding a point x* in the intersection of two nonempty, closed
and convex subsets of a Hilbert space, C and D, such that x* is a solution of an equilibrium problem on C. It generalizes the Constrained
Variational Inequality Problem considered by Censor, Gibali and Reich
(Optimization, 2012). In this work, an algorithm based on a modified
Mann scheme, using projections onto each set is proposed to solve the
CEP. Convergence properties of the algorithm are established under
few assumptions. Numerical results are reported.
2 - On Vector Equilibrium Problems Given by a Sum of
Two Functions
Livia-Mihaela Miholca, Gabor Kassay
In 1994, Blum and Oettli obtained existence results for (EP) in the case
where the function involved is a sum of two functions, and the assumptions are required separately on each of these functions. Later, Kazmi
(2000) extended some of the results of Blum and Oettli for vector equilibrium problems. It turns out that many of the assumptions imposed
by Kazmi are too strong. The aim of this note is to relax several of
these assumption without loosing the results. The special case of reflexive Banach spaces is also studied, where we make use of the fact
that closed balls are weakly compact.
3 - On Gap Function for Variational Relation Problem
Anulekha Dhara
Recently in 2008, Luc introduced a class of problems, namely variational relation problems. A lot of work has been done towards the
study of solution for this class of problems using fixed point approach.
In this work, a gap function is constructed to study the existence of
solution for the class of variational relation problems. In gap function
approach, an optimization problem is constructed wherein the solution
of the optimization problem leads to the solution to the original variational relation problem. The properties of gap function are also looked
into.
4 - Nonsmooth Quasi-Variational-Like Inequalities under Generalized Brézis Pseudomonotonicity
Mohammed Alshahrani
We consider nonsmooth vector quasi-variational-like inequalities and
nonsmooth vector quasi-optimization problems. We then present
some existence results for solutions to nonsmooth quasi-variationallike inequalities under generlaized pseudomonotonicity in the sense of
Brézis.
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Friday, 8:30-10:00 - Room 213
Infrastructure Development and
Environment 1
Stream: Infrastructure Development and Environment
Invited session
Chair: Subhash Datta
Chair: Laura Lotero
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1 - Multi Criteria Multi Facility Location in Rajasthan
Subhash Datta
A problem-structuring method with MCDA was used to select different
facilities based on the needs of the rural area under consideration. A
facility location model was created and algorithms developed to provide a solution for locating facilities in 45 villages of Niwai block,
Tonk district, Rajasthan. 16 facilities were chosen for consideration,
each falling into 1 of 5 groups: healthcare, education, connectivity,
agriculture and drinking water. Alternative scenarios for locating facilities were generated and explored, providing a base for micro-level
planning at the block level in a district.
2 - Porous Network Characterization in Granular Assemblies: A Graph Theory Approach
Diego Recalde
The micro-scale porous network of numerically generated granular assemblies is characterized by using a novel and promising computational approach that exploits the capabilities of graph theory and computational geometry. The solution to a wide variety of problems ranging from CO2 sequestration to landslides mitigation, highly depends
on the understanding of the nature of the flow through the porous media. The methodology approximates edaphic qualities of agricultural
soils, specifically drainage capacity, as it is affected by fly ash coming
from the eruption of a nearby volcano.
3 - Analysis of the Robustness and Vulnerability of the
Urban Public Transportation in Medellin
Laura Lotero, Patricia Jaramillo, Rafael Hurtado
Transportation networks are critical infrastructure systems for human
beings, therefore the analysis of vulnerability or robustness of these
networks is a major issue, especially in engineering. In this presentation we take into account the fluxes and the topology of the transportation network in order to analyze the robustness and vulnerability of the
major urban public transportation system of Medellin, Colombia.
4 - Usability of the Structured MCDM Methodology in
Supporting Problem Structuring and Improving Participation in Tanzania Rural Communities
Joe Kakeneno, Cathal Brugha
We present the results of an empirical study on how the Structured
MCDM methodology could support problem structuring and improve
rural community participation in Africa. A model which is based on
a generic structure is flexible and transferable to similar problem contexts and various situations; and it can easily support distributed participatory decision-making or be integrated in a Participatory Decision
Support System. We question the current view of problem structuring.
The study adds to the emerging research and debate on participatory
process design, implementation and evaluation.
FA-28
Friday, 8:30-10:00 - Room 130
MINLP in the Oil and Gas Industry
Stream: Mixed-Integer Nonlinear Programming
Invited session
Chair: Andrew Conn
2 - Biobjective Optimization for General Oil Field Development Problems
Louis J. Durlofsky, Obiajulu Isebor
An approach for biobjective optimization of oil field problems is presented. The MINLP problem includes categorical (well type), discrete (location) and continuous (pressure) variables. A single-objective
product formulation, which systematically combines the two objectives in a sequence of problems, is applied for the biobjective problem. The core optimizer includes stochastic search (PSO) and local
convergence (MADS) characteristics. Results will be presented for
maximization of both long and short-term reservoir performance and
optimization of field development under geological uncertainty.
3 - Model-Based Production Optimization Applied to a
Gas Offshore Field
Thiago Silva, Alex Furtado Teixeira, Snjezana Sunjerga,
Eduardo Camponogara
The search for improvements in the production efficiency and operational cost is one of the main challenges for the production engineers. The use of a decision support system based on mathematical
optimization can help them to maximize the production, while at the
same time satisfying constraints imposed by the wells, subsea manifolds, pipelines and the platform process plant. This talk will present
the development of a decision support system based on mathematical
optimization designed to support the engineers responsible for an offshore gas field in the production optimization process.
FA-29
Friday, 8:30-10:00 - Room 011
Societal Complexity and Economy
Stream: Methodology of Societal Complexity
Invited session
Chair: Dorien DeTombe
1 - A Proposition of Thetical and Antithetical Business
Management
Eizo Kinoshita
The author discusses the theme of "Thetical and Antithetical Business
Management." The thetical business management signifies "a management style which enables such formulation as to make consumers’
minimum amount of service goods expenditure an objective function,
while making a minimum guaranteed level of expenditure concerning
service goods a constraint condition at the same time." On the other
hand, the antithetical business management is "a management style
which enables such formulation as to make consumers’ maximum satisfaction concerning service goods an objective function.
2 - Informatization of the money will impact the social
system and existing money value
Shunei Norikumo
This study is to clarify social impact. That rapid informatization of
money influences exiting money value along with the development of
information technology. On the surface, we can explain that electronic
money revitalize our economic activity, However the money we pay
when we buy a bread and the money we pay to buy some items on online games are different, This study is to define the difference between
them and how this influences in Our society.
1 - Modeling of Flow Splitting for Production Optimization in Offshore Oil Fields
Eduardo Camponogara, Thiago Silva, Alex Furtado Teixeira,
Snjezana Sunjerga
3 - Reporting and Misreporting Behavior — A Review of
Experimental Studies in Decision Theory
Ulrike Leopold-Wildburger
Unlike in satellite oil wells, the wells that produce to subsea manifolds are equipped with routing valves that can direct the production
to multiple headers. However, the existing models for production optimization do not account for splitting of flows and require the wells
to be connected to a single header. To this end, this work develops a nonlinear model of flow splitting which is approximated with
piecewise-linear functions, resulting in an MILP program which is
solved with optimization software available off-the-shelf. The accuracy of the splitting model is demonstrated by simulation.
This paper focuses on reporting behavior under information asymmetry within a company. Manipulation and misreporting of information are some of the central topics in operations research literature. We investigate our research from the experimental perspective
of management accounting and from behavioral research. Experimental studies are classified in a broad literature review, and the major
findings are discussed in the context of honesty in decision making.
The complexity indicates strong integration between economical and
non-economical (psychological and social) theories.
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4 - The Emancipatory Systems Methodology for Addressing Coercive Organizational Problems
Slavica P. Petrovic
Creatively dealing the with coercive management problem contexts,
in which power sources can be identified, implies the emancipatory
paradigm and employment of corresponding systems methodology.
Pursuant to its philosophical foundations and methodological development, Critical Systems Heuristics (CSH) enables to reveal the normative content of organizational systems designs. Through use of critically heuristic categories and dialectical debate between those involved
and those affected by the designs, CSH seeks to - in application - support the process of improving position of all stakeholders.
FA-31
Friday, 8:30-10:00 - Room 013
Networks and Queueing Systems
Stream: Telecommunications and Networks
Contributed session
Chair: Jorge Sá Esteves
1 - Performance Evaluation of a Computer Network
Salima Kendi, Salima Touati, Louiza
Bouallouche-Medjkoune, Djamil Aïssani
The purpose of this work is the performance evaluation of a specific
computer network (study of a practical case). For this, we have modeled the system by a Markovian queueing network (Jackson network).
The performances are obtained analytically and by simulation. Based
on the obtained results, we propose a resizing of the main router and
the main server (increasing of their transmission capacity).
2 - Multi-Class M/G/1 Queue with Exponentially Distributed Impatient Times
Yutaka Sakuma
We study a stationary multi-class single-server queue with impatient
customers. Customers in each class arrive according to an independent
Poisson process. Service times of customers are i.i.d. to a general distribution which may depend on customer’s class. Arriving customer
has a waiting time limit until his/her service begins, where the waiting time limit has a class-dependent exponential distribution. For this
queueing model, we obtain the waiting time and queue length distributions, and give a computational algorithm to compute the probability
mass function of the queue length.
3 - Diffusion Approximations and Optimality of Scheduling Algorithms for Processor-Sharing Queues in
Random Fading MIMO Channels
Wanyang Dai
We study the diffusion approximations and asymptotic optimality of
scheduling algorithms for generalized processor-sharing queues in a
random environment. Such a queueing system typically appears in
multi-input multi-output (MIMO) wireless channels under random fading with cooperation and admission control. Two service rate scheduling algorithms designed by the immediate queue length and the current
channel state information (CSI) are considered. How to use the optimality of the first algorithm to prove the counterpart of the second one
under certain constraint of RTR is presented.
4 - Server Allocation using an Analytic Generalization of
Erlang’s Functions
Jorge Sá Esteves
An analytic function which is a hybrid of Erlang B and C functions is
proposed. A fluid model describing the steady state of a generalized
multiserver queueing system is introduced. A bicriterion optimization
problem related to the server allocation between generalized Erlang
queueing systems is formulated. This model is useful in telecommunications networks design. Two objectives are considered: the overall
efficiency and a measure of equity among users. An algorithm for
traveling on the set of Pareto optimal solutions is proposed. Some
computational results are presented.
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FA-32
Friday, 8:30-10:00 - Room 014
Supply Chain Management
Stream: Production Management & Supply Chain
Management
Contributed session
Chair: Elodie Adida
1 - Does the Company Size Affect the Purpose of Patent
Application? Case of the Korean Electronics Industry
Seongtaek Park, Solyi Kim, Tae-Sung Kim
This article focuses on the patent application case study. Currently,
companies are aware of the need for the importance of the patent and
patent management. This research was started to get related appropriate data for the purpose of a patent application. So, it draws 5 influencing factors by using the Delphi method and analyzing the previous
studies. Then, the priorities were drawn out using the Delphi method
in the form of rankings for professionals in companies. As a result of
this analysis on the purpose of a patent application, there is a difference
between businesses.
2 - Capturing Dynamics and Integration in Supply Chain
Jian Cui
Capturing dynamics and integration in supply chain is a major challenge for companies to maintain the competitiveness in today’s global
market environment. An innovative two-stage stochastic mixed integer programming formulation in rolling horizon settings is employed
to capture the uncertainties and updates of the system, together with
developed models integrating production and sale, transportation networks with revenue management. The simulation results indicate the
significant reduction on the bullwhip effect on deterministic scenario
and further reduction on stochastic scenario.
3 - Evaluating the Supply Chain Cost of Strategic Product Platform Decisions
Maud Van den Broeke, Robert Boute, Behzad Samii
Our research provides a model to evaluate strategic product platform
decisions, such as how many and which platforms to develop and
which products to derive from which platforms. We consider the costs
originating from various supply chain activities: development, ordering, purchasing, inventory holding and customisation costs. The value
of our integrated cost model is demonstrated in a real business case at
a global electronics manufacturer.
4 - Competition and Coordination in a Two-Channel
Supply Chain
Elodie Adida, Amy David
We study competition and coordination in a supply chain in which a
supplier both operates a direct channel and sells its product through
multiple competing retailers. We study analytically the supply chain
with symmetric retailers and find that the supplier generally prefers
to have as many retailers as possible in the market. We find that the
two-channel supply chain may be subject to inefficiencies not present
in the single channel chain and study coordination. We propose a linear quantity discount contract and demonstrate its ability to perfectly
coordinate the asymmetric supply chain.
FA-34
Friday, 8:30-10:00 - Room 016
Managing Knowledge
Stream: Knowledge in Organizations
Invited session
Chair: A. D. Amar
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1 - Data Science: Best Practice & Governance
Sayara Beg
Data Science: Best Practice and Governance in Analytics — will describe how the Analytics, and the recent Big data revolution, has given
rise to the new role of the ’Data Scientist’. It will explore core elements such as expertise, knowledge of tools and interpersonal skills
that are expected from a Data Scientist today, and how those core elements have evolved over time. It will conclude with why the need
for best practice, ethic and governance has now become immediately
urgent and how this urgency can be addressed.
2 - What’s Wrong with Big Data?
Victor Tang
Conventional wisdom says that size, complexity, and technologies are
at the core of Big Data. We argue that there is something much more
fundamental and profound than these obvious symptoms. Were it not
so, we would call astronomy "Big Stars", physics "Big Atoms", and
medicine "Big Cells". This paper will explain why we don’t. We frame
and discuss our GigaNano Hypothesis to argue, illustrate, and help us
develop a deeper understanding of Big Data and its implications. Our
discussion will be grounded on precise and unambiguous definitions
and inter-disciplinary first principles.
3 - OR and Quality of Healthcare: An Application of DEA
to the South African private hospital industry
Kathryn Dreyer, Shivani Ramjee
We analyse the selection and inclusion of quality-of-care measures in
a risk-adjusted DEA model, which is used to evaluate the efficiency
of South African hospitals. One of the biggest challenges faced is addressing the multidimensional nature of quality and ensuring that the
quality measure included is representative of operational reality. Results reveal that omitting quality can bias individual efficiency scores.
Three different quality measures were examined. The choice of measure impacts efficiency scores, emphasising the need for a comprehensive quality measure.
4 - Managerial Perceptions in Knowledge Management
Implementation: Results from a Case Study and a
Survey
A. D. Amar, Souad Mohamed, Elayne Coakes, Andrew Leslie
Employing case study of an insurance company and a knowledge management (KM) survey of over 1000 respondents, we study managers’
perceptions of KM prior to its implementation. Using content analysis
to organize contextual data, we determine perceptions of benefits of
KM, barriers to its implementation, and the requirements for its practice; and find that managers strongly align KM with communication.
Organizational structure is not an issue. We narrate managerial misconceptions contrasting knowledge and communication, and indicate
how organizations can have the knowledge shared effectively.
2 - Investment in Reconfigurable Electricity Networks
under Uncertainty
Jonas Christoffer Villumsen, Jakub Marecek, Mathieu Sinn,
Martin Mevissen
We study investment into switching equipment and line capacity of
electricity networks, which employ dynamic reconfiguration of the network topology. We consider two models: Maximisation of reliability
indices under uncertainty about line failures and minimisation of capital and operational cost under uncertain load and injection from renewables. Both models result in two-stage stochastic programs with
discrete decisions at both stages. We demonstrate a novel framework
for hedging against uncertainty on both models.
3 - Recent Advances in Simulation Optimization Using
Direct Gradients
Michael Fu
We overview several recently proposed new methods for employing direct gradient methods such as perturbation analysis and the likelihood
ratio methods into existing simulation optimization approaches such as
response surface methodology, stochastic kriging, and stochastic approximation. The first two settings combine performance estimates
with the direct gradient estimates to obtain better functional fits. The
last setting can be viewed as a way to combine the traditional KieferWolfowitz and Robbins-Munro algorithms; for higher dimensions the
method of simultaneous perturbations is employed.
4 - Forecasting the Demand of Technical Resources
based on Project Pipeline Data
Ta-Hsin Li
In large enterprises, projects are often managed through a pipeline system in which work items are planned and scheduled for start in the
future. The planned work in the pipeline serves as a forecast of demand on different technical skills, based on which technicians with
the right skills are recruited. We propose an analytical model for the
statistical behavior of scheduled start date to produce a better forecast
of planned work. We also propose an analytical framework for incorporating unplanned work (future work which is not captured by the
present pipeline) into the forecast.
FA-36
Friday, 8:30-10:00 - Room 132
Applications in Agriculture
Stream: OR in Agriculture, Forestry and Fisheries
Contributed session
Chair: Concepcion Maroto
FA-35
Friday, 8:30-10:00 - Room 131
Advances in Forecasting and Stochastic
Programming Applications
Stream: Stochastic Modeling and Simulation in Engineering, Management and Science
Invited session
Chair: Gerhard-Wilhelm Weber
Chair: Jonas Christoffer Villumsen
1 - Impact of the Spatial Arrangement of Agricultural
Land Uses on Ecosystem Services at the Landscape
Scale.
Justice Nana Inkoom, Susanne Franke, Christine Fürst
The relationship between agricultural land uses and its impact on
ecosystem services including nutrient cycling is complex. Research on
the use of size, shape, and spatial interactivity to assess the impact of
agriculture land uses on the landscape’s capacity to provide ecosystem
services remains scanty. To formulate a methodology that corresponds
to this complexity, landscape metrics and mean enrichment factor approaches are explored as neighbourhood interactive assessment tools
to evaluate the mutually interactive impact of agriculture land uses on
ecosystems functioning using GISCAME.
1 - Forecasting Container Throughput at Tanjung Priok
Port, Indonesia, using Univariate Forecasting Models
Gu Pang
2 - Land Use Optimization to Meet Environmental and
Economical Demands
Tijana Vulevic
We forecast the container throughput at the Indonesia’s largest seaport
Tanjung Priok Port. We carry out the analysis by applying univariate
forecasting models. We test monthly data (2003-2013) and compare
the forecasts based on mean absolute error, mean absolute percentage
error and root mean squared error. Our aim is to find a model provides the most accurate forecasts of Tanjung Priok Port’s container
throughput, and specifically of each of the four terminals. Moreover,
our results provide essential insights into the port’s capacity planning
and construction of new container terminals.
Rational and efficient use of land in mountain region is possible
through land allocation to the different land uses (e.g., orchards, pastures, crops). The aim of this paper is to find optimal land use pattern for land in the Tresnjica Watershed in Western Serbia satisfying
economical and environmental demands. Required balance between
two objectives: profit maximization and soil erosion minimization is
achieved using linear programming method. To establish constraints
functions, land use suitability evaluation was determinate using information such as aspect, slope and elevation.
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3 - Branch-and-Price-and-Cut for Sustainable Crop Rotation Planning
Laurent Alfandari, Agnès Plateau, Xavier Schepler
We study a multi-periodic crop planning problem in agriculture. Crop
cultivation and fallow periods are scheduled on land plots so as to minimize the total surface area of land used, while satisfying crop demands
every period. We prove NP-hardness, and propose a 0-1 Linear Programming compact formulation based on crop-sequence graphs. An
extended formulation is then provided. A Branch-and-Price-and-Cut
algorithm is presented with adapted branching rules and cutting planes.
Numerical experiments on instances varying the number of crops, periods and plots show the efficiency of the approach.
FA-37
Friday, 8:30-10:00 - Room 017
Importance of Information In Inventory
Management
Stream: Recovery Inventory Management Policies
Invited session
Chair: Ozgen Karaer
1 - Enabling Horizontal Collaboration in Agricultural
Supply Chains under Incomplete Information
Andrew Mason, Rene Villalobos, Hector Flores
Recent tendencies on agricultural supply chains have forced small producers to form partnerships in order to compete with larger operations.
Unfortunately, such collaboration requires a significant degree of horizontal coordination, which is hard to attain when there is asymmetric
information and competitive behavior within the organization. In order to coordinate production and make the supply chain more efficient,
an auction based mechanism for horizontal coordination is proposed
such that the aggregate actions of farmers are aligned with demand,
and overall profits are maximized.
2 - Information Sharing in Competing Supply Chains
with Cost Reduction Efforts
Albert Ha
We investigate the incentive for vertical information sharing in two
competing supply chains where the manufacturers can take efforts to
reduce production costs. The retailers have private demand information and engage in either Cournot or Bertrand competition. We characterize the equilibrium information sharing decisions and conduct sensitivity analysis to investigate the impact of several parameters.
3 - Understanding the Risks and Benefits of Radio Frequency Identi
FA-39
FA-38
Friday, 8:30-10:00 - Room 214
Counterparty Risk and Decision Support
Systems
Stream: Operational Research and Quantitative Models in Banking
Invited session
Chair: Caslav Bozic
Chair: Markus Hoechstoetter
1 - Parametric and Nonparametric Modeling of LGD for
Third-Party Buyers
Abdolreza Nazemi, Markus Hoechstoetter, Caslav Bozic
In contrast to recovery rate modeling of bonds, research on personal
loans and retail credit is sparse which is of extreme interest, however,
for third-party buyers. This study is based on data from a leading German debt collector with over three million defaulted consumer credits
from two different industries. This paper analyzes statistical and data
mining methods such as GLM, neural network, K-nearest neighbor,
CHAID, CART, and Support Vector Machine.
2 - Stochastic Technical Analysis for Decision Making
on the Financial Market
Mher Safarian, Markus Hoechstoetter
The determination of change-points in regimes poses still one of the
greater problems in finance. While there exists an analytical solution
when the change-point distribution is known a-priori, the realistic situation, i.e., no such a-priori information is known, cannot be solved
for analytically. For this reason, we analyze distribution-free methods of ’immediate’ detection of change-points. We find that there are
non-parametric versions of some popular parametric methods.
3 - Regression Models for Censored and Ordered Dependent Variables Applied to Recovery Rates in Consumer Credit
Johannes Kriebel, Werner Stahel, Markus Hoechstoetter
This work discusses the modeling of recovery rates in the subfield of
consumer debt from a third-party buyer perspective. It is based on a
study conducted in the year 2013. Three linear models and two machine learning models were applied. Suggestions for model improvements were presented using residual analysis and using the Random
Forest. The models were evaluated using cross-validation and new
data sets. Errors were larger overall when predicting the outcome of
new data. The predictive quality on whole portfolios of observations
was decent and improved slightly using the tools suggested.
fication (RFID) for an Apparel Retailer
Ozgen Karaer
One of the main promises of Radio Frequency Identification Technology (RFID) is reduction in inventory record inaccuracy at retail stores,
which in turn will diminish stockouts and result in a more responsive inventory management system. Though reduction of stockouts is
widely accepted, the sales increase that could be observed, especially
in the long run is not that clear. In this work, we investigate the sales
impact of RFID for a retailer that sells seasonal merchandise, such as
apparel retailers. We also analyze the risks associated with imperfect
RFID performance.
4 - Information Technology Role in Sustainable Supply
Chains
Zeynep Ata
Sustainable SCs are essential to delivering long-term profitability and
are a crucial environmental and social responsibility for organizations.
Members of a SC are linked by information, material and capital flows.
Information is referred to as the glue that allows SC drivers to work together with the goal of creating an integrated, coordinated SC. The
aim of this study is to draw from previous studies that explore the areas of SCM, sustainability and IT, and then to contribute to literature
by examining the role and importance of IT strategy on achieving and
improving sustainability in SCs.
FA-39
Friday, 8:30-10:00 - Room 018
Discrete Optimization II
Stream: Discrete and Global Optimization
Contributed session
Chair: Frank Gurski
1 - Online Parallel Machine Scheduling with Equal Processing Times and Eligibility Constraints
Zhaohui Liu
We consider the online parallel machine scheduling problem with eligibility constraints. The jobs have equal processing times and arrive
over time. The objective is to minimize the makespan. We study the
cases of nested, GoS and tree-like eligibility constraints, and develop
optimal online algorithms for them.
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2 - Algorithms for the FIFO Stack-up Problem
Frank Gurski, Jochen Rethmann, Egon Wanke
Palletizers are widely used in delivery industry. We consider a large
palletizer where each stacker crane grabs a bin from one of k conveyors and positions it onto one of p pallets. Each pallet is destined for one
customer. A completely stacked pallet will be removed automatically
and a new empty pallet is placed at the palletizer. The FIFO stack-up
problem is NP-hard in general. We introduce a digraph model and linear programming models for the problem. Based on this characterizations we give fpt-algorithms and xp-algorithms for various parameters,
and approximation results for the problem.
3 - Maximum Generalized Assignment with Convex
Costs
Stephan Westphal, Marco Bender
We consider a generalization of the maximum generalized assignment
problem. We relax the hard constraints for the bin capacities, and introduce for every bin a cost function that is convex in the total load on this
bin. These costs are subtracted from the profits of assigned items, and
the task is to find an assignment maximizing the resulting net profit.
We show that even restricted cases of this problem remain strongly
NP-complete, and identify two cases that can be solved in strongly
polynomial time. Furthermore, we present a (11/e)-approximation algorithm for the general case.
4 - On Generalised Blossom Inequalities for the
Matchoid Polytope
Konstantinos Kaparis, Adam Letchford, Yiannis Mourtos
We generalise Edmond’s blossom inequalities for the b-matching polytope, to the so-called matchoid polytope and prove that any nondominated 0 1/2 cut with 0 or 1 coefficients, is a generalised blossom inequality (GBI). We establish that GBI separation is NP-hard in
the general case and we outline conditions under which GBIs define
facets. Finally, we present a heuristic separation scheme for GBIs and
a computational study that illustrates the strength of the proposed cutting planes.
FA-40
Friday, 8:30-10:00 - Room 019
Quantitative Models for Performance and
Dependability I
Stream: Quantitative Models for Performance and Dependability
Invited session
Chair: Vassilis Kostoglou
1 - Individual Choice and Payoff in Passenger Train Congestion: An Experiment
Clint Pennings, Paul Bouman, Jan van Dalen
To understand congestion in passenger trains, the heterogeneity of the
population is vital: individual characteristics and payoffs lead to different observed behavior. We conducted an experiment which is based
on an extension of the El Farol Bar Game, a popular minority game.
Our extension introduces multiple train services and individuals can
optimize a criterion of their own choice. Using psychological traits
of the respondents, we construct various dynamic models to explain
user behavior and assess the impact of additional information and their
previous experience on their choice behavior.
2 - Information Visualization and Cost-benefit Analysis
as Decision Support Tools in the CHANGES Spatial
Decision Support System
Irina Cristal, Julian Berlin, Wim Bakker, Cees van Westen,
Stefan Greiving
This research contributes to the development of the CHANGES Spatial Decision Support System, a web-based system aiming for natural
risk assessment and evaluation of optimal risk reduction alternatives.
The main concern of the study is to exploit the cost-benefit analysis in
the context of geo-visualization. Moreover, the large amount of riskrelated data is analyzed in accordance to its representational goal. Particular attention is paid to the comparison methods as being the key
visual instruments in facilitating the decision making process.
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3 - Personalized User Information on a Decision Support
System Supporting the Choice of Higher Education
Specialty
Vassilis Kostoglou, Nikolaos Ploskas, Michael
Vassilakopoulos
The vocational orientation of lyceum graduates and students is one of
their main priorities. A web based Decision Support System (DSS) has
been implemented, supporting youngsters in the choice of their higher
education profession and informs them about their department’s vocational prospects. This paper presents additionally the personalized
user information that such a system should provide. The DSS guides
the user through wizards and successive questions to enter his personal
information and then builds a user profile in order to present suggestions depending on the information provided.
4 - A Case Study of Compromising Prioritization Method
to Identify Key R&D Quality Criteria
Deok-Hwan Kim
This study aims to identify key R&D quality criteria (i.e., elements or
activities in R&D which affect the quality of the results critically) using the prioritization method proposed by Kim et al. (EJOR, 2010).
The prioritization method determines a priority sequence of alternatives based on paired comparisons to compromise type I and type II
errors so that may provide a relatively robust priority against the uncertainty in input information. In this study, the alternatives for R&D
quality criteria are prioritized based on a survey on eighteen experts on
R&D quality.
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Friday, 8:30-10:00 - Room 216
Auction Theory and Practice
Stream: Auctions
Contributed session
Chair: Brian Baisa
Chair: Martin Bichler
1 - Bundling Strategies in Online Auctions
Yingqian Zhang, Sicco Verwer
We study the bundling strategy for online auction with different types
of (multi unit) items. These items can be sold simultaneously or sequentially, separately or as a bundle. Given data collected from an
online auction site, we investigate bidding behaviors of the bidder with
different bundling strategies. We then study how to use historical bidding data to design the bundling of the items to maximize the revenue of the seller. We compare its performance with existing bundling
strategies.
2 - Nash Equilibria of Sealed-Bid Combinatorial Auctions
Marion Ott, Marissa Beck
We characterize the sets of Nash equilibria (NE) of the combinatorial
Vickrey auction (VA), bidder-optimal core-selecting auctions (BOCS),
and the pay-as-bid auction (PAB). All of the NE of the PAB are NE
of every BOCS, and all of the latter’s NE are also NE of the VA. Analyzing the possible NE outcomes, we find that any assignment and
payments that generate individually rational payoffs (IR) are the result
of some NE of the VA and of every BOCS. A necessary and sufficient
condition for an outcome to result from an NE of the PAB is stricter
than IR but still allows payoffs outside of the core.
3 - A Comparison of the Uniform Price and Vickrey Auctions on General Preference Domains
Brian Baisa
I compare bid behavior in uniform price and Vickrey auctions when
bidders have private values and multiunit demands. I remove quasilinearity and allow for preference domain that includes quasilinearity
and also allows budget constraints, financial constraints, risk aversion
and/or wealth effects. I show that truthtelling is not a dominant strategy in the Vickrey auction. Instead bidders truthfully report demand
for their first unit and overstate demands for all other units. This result
mirrors the incentive for demand reduction in uniform price auctions
shown by Ausubel and Cramton (2002).
IFORS 2014 - Barcelona
4 - Split-Award Procurement Auctions — Can Bayesian
Equilibrium Strategies Predict Human Bidding Behavior in Multi-Object Auctions?
Martin Bichler, Stefan Mayer, Kemal Guler
We analyze how equilibrium predictions can explain human bidding
behavior in multi-object auctions. We focus on two sealed-bid splitaward auctions with ex ante split decisions as they can be regularly
found in procurement practice. These auction formats are straightforward multi-object extensions of the first-price sealed-bid auction. We
first derive the risk-neutral Bayes Nash equilibrium strategies and find
that, although the two auction mechanisms yield the same expected
costs to the buyer, other aspects of the two models, including the equilibrium strategies, differ significantly.
FA-43
each of the classes for nonlinear non-monotone options, we employ
copula functions. The property of full option ranking is relaxed in
cases of symmetric attributes, and its solved by introducing exchangeable copulas. The solution is demonstrated on real and artificial cases.
FA-43
Friday, 8:30-10:00 - Room 217
Water Distribution Network Design and
Management
Stream: OR in Water Management
Invited session
FA-42
Friday, 8:30-10:00 - Room 215
Qualitative Multiple Criteria Decision
Making I
Stream: Qualitative Multiple Criteria Decision Making
Invited session
Chair: Vladislav Rajkovič
Chair: Marko Bohanec
1 - Qualitative Multi-Attribute Decision Method DEX:
Theory and Practice
Marko Bohanec, Nejc Trdin
DEX is a qualitative multi-attribute decision method, aimed at evaluation and analysis of decision alternatives. Conceptually, DEX is a combination of multi-criteria decision analysis and expert systems. DEX’s
models are hierarchical and composed of qualitative (symbolic) variables, whose interrelations are modeled with decision rules. DEX and
the supporting software DEXi were used in many practical applications. The purpose of this work is threefold: (1) formal description of
DEX, (2) overview of its practical applications, and (3) research and
development challenges for the future.
2 - Application of Qualitative Multi-Attribute Decision
Model for Patient’s Health Status Evaluation
Uros Rajkovic, Olga Sustersic, Vladislav Rajkovic
Evaluation of patient’s health status is usually based on different signs
and symptoms which have to be aggregated in final estimate of patient’s status. This can be viewed as a multi attribute decision making
(MADM) problem. In this contribution we present the implementation of Henderson’s theoretical model of basic living activities for patient health status evaluation. Qualitative MADM methodology DEX
is used, which facilitates user friendly acquisition and explanation of
expert knowledge. Practical evaluation of our solution confirmed the
added value in transparency of patient’s status.
3 - Comparative Evaluation of Various Energy Options
using Qualitative Multi-Attribute Models
Branko Kontic, Marko Bohanec, Nejc Trdin, Davor Kontic,
Sonja Zagorc-Kontic, Marusa Matko
The topic of the paper is comparative evaluation of various energy options. It is treated from the strategic evaluation point of view focusing
on the constituents of sustainability appraisal. The latter examines differences between the approach, which builds on specific indicators like
climate change, ecology, air quality, health and well being, etc., and the
approach, which rather applies more general interpretation based on
rationality, feasibility, and uncertainties of energy options. The evaluation was supported by qualitative multi-attribute modeling method
DEX.
4 - Solving the Ranking Problem in DEX Methodology
Using Copulas
Biljana Mileva-Boshkoska, Marko Bohanec
Chair: Derek Verleye
1 - A Stochastic Programming Approach to Water Resources Management Evaluating Costs and Risks
Paola Zuddas, Alexei Gaivoronski, Giovanni Sechi
In this paper we consider the problem of water resources management
when data uncertainty occurs. We develop a cost/risk optimization
model that can assist the manager of the system in its decision balancing the level of target delivery to the users and the level of risk that
this delivery will not be met. We obtain a target barycentric value with
respect to selected decision variables and a reduction of the risk of negative consequences derived from unmet resources demand. We show
results of some numerical experiments in real physical systems.
2 - Optimal Placement of Isolation Valves on Water Distribution Networks
Andrea Peano
Water Distribution Networks for urban water supply need to be sectorised by means of isolation valves so that, in case of damage, any
pipe can be disconnected from the source, dewatered and repaired, by
closing the isolation valves of its sector. A limited number of isolation
valves must be optimally located on the network so that the maximum
unsatisfied demand is minimized. This is a generalization of the wellknow Graph Partitioning problem, since "unintended isolation" must
be considered. We present and discuss pros and cons of different solution approaches.
3 - Solving Multi-Period Water Production and Distribution Problems in Large-Scale Networks
Derek Verleye, El-Houssaine Aghezzaf
We present a complete model for the optimal planning of water production and distribution in a large-scale water supply network. Since this
network is mesh-structured, energy conservation laws must be satisfied. Nonlinear pressure loss restrictions are hereby introduced, which
require an adapted solution approach. Furthermore the model contains
binary variables. We device an algorithm that decomposes our problem into multiple "tractable" subproblems and efficiently handles the
difficult constraints. Results on a real-world network are discussed and
compared with other solution approaches.
4 - Heuristics and Decomposition Techniques for Large
Multi-Period Network Planning Problems
Simon Dunstall, Nahid Jafari, Tarek Elgindy, Andreas Ernst,
Melanie Ayre, Asef Nazari
We report on the application of heuristics and decomposition techniques to solve multi-period network planning problems arising in
electricity systems, water networks and freight transport. Mixedinteger programming formulations of these problems result in very
large instances. These instances can be solved by the direct application of commercial solvers, but can require several days of computing
time. The heuristics and decomposition techniques reduce and limit
the time required, which is especially important for industrial users of
network planning software systems.
We provide a solution for ranking of qualitative multi-attribute options
modeled with DEX methodology. In DEX, the attributes form a hierarchical structure which solves the problem of sorting the options into
preferentially ordered classes. To obtain full option ranking within
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IFORS 2014 - Barcelona
Friday, 10:30-12:00
FB-03
FB-01
Location (contributed)
Getting the Decisions Right, Fast (IBM)
Stream: Location
Invited session
Friday, 10:30-12:00 - Room 118
Stream: Sponsored Sessions
Sponsored session
Chair: Susara van den Heever
Chair: Sofiane Oussedik
1 - Getting the Decisions Right, Fast
Susara van den Heever, Sofiane Oussedik
Recent CPLEX and Decision Optimization Center developments will
be presented as well as insights on recent work on handling uncertainty,
automatically and interactively. The presentation will also include use
cases that highlight the ease-of-use of the development environments
and seamless integration to build interactive optimization based applications that accomplish key business objectives and deliver the right
solutions to the user.
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Friday, 10:30-12:00 - Room 111
Vehicle Routing Problems 2
Stream: Combinatorial Optimization
Invited session
Chair: Irene Loiseau
Friday, 10:30-12:00 - Room 001
Chair: Ricardo Aceves-García
1 - Problem Size Reduction in a Large Multi-Period
Location-Allocation Problem
Guina Sotomayor Alzamora, Leonardo Lustosa, Fernanda
Raupp, Carlos Eduardo da Camara Pereira
Despite advances in general methods and specific techniques of mathematical programming, its application to location problems still presents
challenges. Among these is the frequently large volume of data involved. In this work we discuss problems encountered in developing
a preliminary design and economic evaluation of an asphalt distribution system for the Brazilian market. The study comprised a year of
seasonal demand dispersed in some 2800 municipalities. Among the
solutions adopted some are believed to be original, and despite their ad
hoc character, seem to be more generally applicable.
2 - Multi-Period Facility Location Problem with an Uncertain Number of Servers
Amit Vatsa
This work takes motivation from rural healthcare in developing countries. We look at staffing Primary Health Centers (PHCs) with doctors to achieve maximum population coverage over a planning horizon. Number of doctors joining in each period of the planning horizon
is uncertain. It needs to be decided in which sequence the PHCs should
be assigned with a doctor. We use minimization of maximum regret to
model the problem and give a local search and three tabu search implementations. Experiments show that tabu search outperforms CPLEX
12.4 when the problem increases to practical size.
1 - The Vehicle Routing Problem with Minimizing Environmental Pollution
Lorena Pradenas, Mauricio Bravo, Víctor Parada
3 - Solution to the Capacitated Location Problem Using
Separable Cross Decomposition
Ricardo Aceves-García
The objective of this work is to propose an approach to freight transport
planning routes (vehicle routing), with pickup and delivery of products
to customers in certain time windows with several goals, among which
are pollution reduction and conducting negotiations with various transportation firms. To solve the problem first we set out to develop a
multiobjective mathematical model which will be solved by an exact
method to test the model with small size instances. After, we used a
multiobjective metaheuristic method to solve instances of medium and
large size.
Applying the strategy of cross decomposition to the location problem,
it is operated simultaneously its primal and dual structure, which results in a successive solution of two subproblems and the reduction of
the number of master problems. When it incorporates the Lagrangian
separable relaxation in this cross-scheme, ensuring that the sub problems keep all the original restriction without losing some of them, the
need to resolve some of the master problems is removed and it is obtained a simple strategy solution and efficient, resolving two transport
subproblems.
2 - A Multiple Ant Colony System for the Prize Collecting
Location Routing Problem
Irene Loiseau, Daniel Negrotto
Given a set of possible customers and their demands, and potential locations for distribution centers, the Prize Collecting Location Routing
problem consists of choosing the depots to be opened, and drawing the
routes to visit some of the customers. Not all customers have to be
visited and each one has a prize associated when is visited. To deal
with this problem we developed a Multiple Ant Colony algorithm that
searches solutions by means of two different colonies, one focusing on
the location problem and the other dealing with the routing problem.
Preliminary results are very promising.
3 - Outsourcing regional commercial cash operations in
the Chinese Banking Industry
Zhu Nan, Qiu Hong
The problem of outsourcing the commercial cash operations of the Chinese commercial banks to third-party companies in Chinese regions is
studied. We present a mixed integer linear programming model of this
problem for identifying the minimum total cost of cash transport, storage and sorting of the regional commercial cash service network between the Chinese Central Bank and commercial banks. It is concluded
that it would often be beneficial to the Chinese commercial banks, from
the point of view of cost reduction to outsource their cash operational
activities.
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Friday, 10:30-12:00 - Room 119
Traffic Management
Stream: Traffic Flow Theory and Traffic Control
Invited session
Chair: Michael O Oladejo
1 - Analysis of Road Traffic Accidents in Antalya
Province (Turkey) using Geographical Information
Systems
Ela Ertunc, Tayfun Cay, Omer Mutluoglu
In this study, a general statistical analysis has been made in a GIS environment of road traffic accidents occurred in 2009 and 2010 years in
Antalya Province Center. Also, traffic accidents have been analyzed by
correlating environmental factors with parameters situated in a traffic
accident data set. As a result, at the intersections in Antalya Province
Center, there were identified 41 accident hot spots for the year 2009,
and was identified 57 accident hot spots for the year 2010. A total of
23 intersections were defined as accident hot spots in both years.
IFORS 2014 - Barcelona
2 - Convergence Analysis on Advanced Traffic Assignment Algorithms
Seungjae Lee, Jooyoung Kim, Shinhae Lee
We have compared the convergence of some advanced algorithms embedded in commercial software in order to solve the equilibrium road
traffic assignment. We have tested traffic assignment algorithms in
Emme, Cube and Transcad. Convergence performances are compared
from simple networks to large scale networks. In simple contrived networks, we can test if the algorithms are able to converge into a known
solution. In large scale networks, we can test if the algorithms calculate
reasonable solutions by comparing base scenario and do-alternative
scenario.
3 - Optimal Transportation Network using Challenges as
Catalytic Factors
Michael O Oladejo, Jighjigh Abraham Tamber
Derivation of optimal transportation network using challenges of obstacles, attacks and terrorism as factors by dynamic programming embedded with obstacles and advantages.
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4 - Optimizing Lock Operations: A Combinatorial Benders’ Approach
Jannes Verstichel, Patrick De Causmaecker, Greet Vanden
Berghe
We consider the operation of ship locks with one or more parallel
chambers, which can transfer several ships in a single lockage operation. The corresponding lock scheduling problem consists of three
strongly interconnected sub problems: lockage scheduling, chamber
assignment, and ship positioning. An efficient Combinatorial Benders’ decomposition is developed. Experiments on a large test set
show that this decomposition method strongly outperforms an existing monolithic approach, especially for instances with a complex ship
positioning sub problem.
FB-06
Friday, 10:30-12:00 - Room 211
Matheuristics II
Stream: Matheuristics
Invited session
FB-05
Chair: Michel Gamache
Quayside Operations
1 - A Hybrid Method for the Probabilistic Maximal Covering Location-Allocation Problem
Marcos Antonio Pereira, Leandro Coelho, Luiz A. N. Lorena,
Ligia C. de Souza
Friday, 10:30-12:00 - Room 002
Stream: Port Operations
Invited session
Chair: Evrim Ursavas
1 - Berth Allocation Problem under Stochastic Nature
Evrim Ursavas, Xiang Zhu
Berth management drives the port management process and the major
objective for this process is to determine the optimal location and optimal berthing time for the vessels. In this study, we propose a framework based on stochastic dynamic programming approach to model the
berth allocation problem and compute optimal polices under stochastic arrival and handling times. A heuristic based relaxation is proposed
to confront dimensional computational complexity. We illustrate our
methodology via a case study.
2 - Solving the 3D Stowage Planning with Quay Crane
Scheduling by Representation by Rules and Genetic
Algorithm
Anibal Azevedo, Andrea Oliveira, Cristiano Morini, Luiz
Salles Neto, Antônio Chaves, Antônio Moretti
This paper formulates and proposes a framework for solving the 3D
Stowage Planning for Container ship (3D SPC) integrated with the
Scheduling of Quay Cranes (SQC) problem. The 3D SPC and also
SQC problems are combinatorial ones which justifies not only the applications of meta-heuristics, but also a different way to represent the
solution, called representation by rules. The robustness of the developed representation is attested in a problem with 30 ports, 1500 TEUs
ship, 2 Quay Cranes which binary representation demand 40,545,000
binary variables to represent just one solution for the 3D SPC.
3 - On the Complexity of Container Stowage Planning
Problems
Dario Pacino, Kevin Tierney, Rune Jensen
The optimization of container ship and depot operations embeds the
k-shift problem, in which containers must be stowed with at most k rehandles. We first solve an open problem showing that changing from
uncapacitated to capacitated stacks reduces the problem complexity
from NP-complete to polynomial. We then examine the complexity
of an abstraction of the current state-of-the-art container ship stowage
planning, the hatch overstow problem. We show that this problem is
NP-complete, which means that even abstract formulation of container
ship stowage planning is intractable.
This paper presents a hybrid algorithm that combines a metaheuristic and an exact method to solve the Probabilistic Maximal Covering
Location-Allocation Problem. A linear programming formulation for
the problem presents variables that can be partitioned into location and
allocation decisions. This model is solved to optimality for small and
medium-size instances. For larger instances, a flexible ALNS heuristic
was developed to obtain location solutions, whereas the allocation subproblems are solved to optimality. An improvement procedure based
on an integer programming method is also applied.
2 - A Hybrid Algorithm for the Robust Graph Coloring
Problem
Javier Ramirez, Roman Anselmo Mora-Gutiérrez, Eric
Alfredo Rincón-García, Antonin Ponsich, Aana Lilia
Laureano-Cruces
A hybrid branch and cut algorithm, which generates initial solutions and solves the problems after branching by musical composition
method, is proposed in this paper to solve the robust graph coloring
problem [1], which is a generalization of graph coloring problem. An
experimental result shows that this algorithm is better than other algorithms presented on the literature. References: [1] Javier Yáñez, Javier
Ramırez, The robust coloring problem, European Journal of Operational Research, Volume 148, Issue 3, 1 August 2003, 546-558.
3 - A Matheuristic for the Bi-Objective Arc Routing Problem
Igor Coelho, Daniel Porumbel, El-ghazali Talbi, Luidi
Simonetti, Luiz Satoru Ochi
The bi-objective arc routing problem consists of a set of weighted arcs
that must be serviced by vehicles of limited capacity, minimizing the
longest tour and also the sum of all traversed arcs. This problem has
many practical applications such as garbage collection and it is a NPHard problem. We tackle it by means of an indirect representation
based on permutations and propose matheuristics that integrates an exact decoder with classical multi-objective frameworks. Results show
that the proposed approach is well-suited for this problem and it is extensible to other optimization problems.
4 - Tabu Search Algorithm for the Optimal Planning of a
Marketing Campaign on Search Engines
Michel Gamache, Alain Hertz, Mehdi Jaoua
In this paper, we present a tabu search algorithm for the optimal planning a marketing campaign on search engines. This type of problem
consists in maximizing a certain criterion (e.g., the number of clicks
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IFORS 2014 - Barcelona
leading to the company website), while ensuring a certain level of quality (minimum number of impressions, minimum number of conversions) without exceeding a daily budget. The neighborhood, as well as
methods of diversification and intensification that led to the construction of this resolution approach will be presented.
FB-07
Friday, 10:30-12:00 - Room 003
Theory of Optimal Control
Stream: Optimal Control
Contributed session
Chair: Klara Mizhidon
1 - On One Application of Convex Optimization to Stability Problems
Şerife Yılmaz, Taner Büyükköroğlu, Vakif Dzhafarov
One of the most important problems of control theory is the control
of switched systems. This problem is related to the common quadratic
Lyapunov function problem and one way to solve it is LMI (Linear Matrix Inequalities) approach. On the other hand this approach requires
a huge number of parameters and is not effective when the number
of subsystems and matrix dimensions increase. In this report we give
alternative methods for testing stability of switched systems. These
methods are based on the convexity property of the maximum eigenvalue function of symmetric matrices.
2 - About an Approach to Indentify Linear Dynamic Systems
Elena Madaeva
This presentation proposes an approach to identify linear stationary dynamical systems to construct the control model. This approach is based
on measurement results of phase coordinates of the system at certain
time intervals. The identification of matrix systems according to the
proposed approach is reduced to constructing and to solving of the
matrix linear algebraic equation. Constructing the equation is found
by interpolating initial tabulated solutions of the Cauchy problem. We
provide examples and numerical calculations.
3 - Pontryagins Maximum Principle for Optimal Control
Problems with Infinite Horizon
Nico Tauchnitz
In this talk we consider a class of infinite horizon optimal control problems with a nonlinear dynamical system. For typical applications it is
demonstrated that the state variables belong to a Weighted Sobolev
space. Making appropriate assumptions on the growth of the data of
the problem we can prove Pontryagins Maximum Principle as necessary condition for a strong local minimum. The obtained maximum
principle includes transversality conditions as well.
4 - Conditions for Satisfying Phase Constraints in a
Control Problem
Klara Mizhidon, Arsalan Mizhidon
In this work, we propose an analytical and numerical method for constructing a desired law of motion of a dynamical system. By desired
control we mean admissible control that keeps the system in the phase
constraints under constantly acting disturbances. External disturbances
are described by polyharmonic functions. Consider an auxiliary optimal control problem with functional depending on weight coefficient.
The choice of coefficient provides construction of desired law of motion. The theoretical justification of the proposed approach is presented.
FB-08
Friday, 10:30-12:00 - Room 120
Dynamic Programming and Multicriteria
DSS
Stream: Dynamic Programming
Invited session
Chair: Zdenek Hanzalek
242
1 - Decision Support System (DSS) Based on Dynamic
Programming with Fuzzy Returns for Optimal Management of Natural Resources
Lidija Zadnik Stirn
Paper presents a DSS for evaluation of feasible management scenarios
(integrative, segregative, mixed) of renewable natural resources over
long time horizon, regarding essential future economic, ecological and
social demands, and conflicting stakeholders’ and distinctive groups’
interests. Time perspective is captured by the use of discrete dynamic
programming, while the management goals are denoted by fuzzy indicators. Membership function and fuzzy operators combine the scenarios/goals and indicators. The DSS is illustrated on a sustainable
management of Natura 2000 forestland in Slovenia.
2 - Graphing Tri-Criterion Nondominated Surfaces
Maximilian Wimmer, Ralph E. Steuer
This talk emphasizes on the geometry and properties of the nondominated surfaces in tri-criterion portfolio selection. It is demonstrated
how the single hyperboloids that are usually computed in parameter
space can be converted into decision space, i.e., into the form x’Q +
x’P + R = 0. Furthermore, a principle axis transformation is performed
to transform the hyperboloids into normal form that is required for detailed graphs. In the talk, many graphs are used to illustrate.
3 - Maximising Diversity in Combinatorial Scenario
Spaces
Christian Carling, E Anders Eriksson
Scenario Diversity Analysis is a form of Morphological Analysis (MA)
where variables can be nominal, as in standard MA, or ordinal. When
ordinality is relevant for the problem domain it is of interest to assess policies against sets of maximally diverse scenarios. We present a
formal model for this type of problem based on order theory, which enables an effective algorithm for finding optimal scenario sets. Mixing
genetic and greedy optimisation techniques, the algorithm performs
well compared to current methods and is particularly effective for complicated, non-convex scenario spaces.
4 - Two-Level Heuristic Algorithm for the Hierarchical
Scheduling Problem
Zdenek Hanzalek, Roman Capek, Premysl Sucha
We deal with the scheduling problem where both the projects and
the available resources are hierarchically structured in more levels
of abstraction like subprojects, resource centers and resource areas.
For such a problem we propose a hierarchically structured scheduling
model and the heuristic algorithm, which is composed of more cooperating levels, reflecting the hierarchical structure of the problem. For
the evaluation of the algorithm, we use the standard benchmark instances from the PSPLib library, which are further adjusted to follow
the hierarchical structure of the studied problem.
FB-09
Friday, 10:30-12:00 - Room 121
Electricity Networks
Stream: Technical and Financial Aspects of Energy
Problems
Contributed session
Chair: Jorge Valenzuela
1 - Combinatorial Optimization Enhances the Energy
Output of Electric Power Networks
Christiano Lyra Filho, Celso Cavellucci, Fábio Usberti, José
Federico Vizcaino
Energy is continuously dissipated in electric power networks. Reduction of these losses can be regarded as a hidden source of energy; in
Brazil, the reduction of each percentage point is equivalent to the output of a 1000 MW hydro plant. The talk discusses combinatorial optimization problems that provide alternatives to reduce losses in electric
distribution systems and gives an overview of two reference problems
in this area: finding minimum loss paths for energy flows and reducing losses by the control of reactive power flows. It considers solution
techniques and fathoms new ideas.
IFORS 2014 - Barcelona
2 - Lying Generators
Dávid Csercsik
We consider an optimal power flow (OPF) scenario in which the generation values regarding the OPF are calculated by a central authority
and a centralised mechanism is applied for the determination of generator payoffs. We analyze the situation when generators may provide
false information about their production parameters and thus manipulate the OPF computation in order to potentially increase their resulting
profit. We consider several central payoff mechanisms and compare
their vulnerability. Furthermore we analyze the effect of cooperation
and mutual information of generators.
3 - Seasonal Transmission Switching with N-1 Reliability
Requirements
Jorge Valenzuela, Masood Jabarnejad, Jianhui Wang
A new control paradigm that switches transmission lines into/out of
service has been proposed to improve the economics of electric power
systems. In this presentation, a large-scale mixed integer programming model is described where the transmission switching occurs at
the beginning of a time period and remains unchanged during that period. The objective of the optimization model is to minimize the total
energy generation cost over the season subject to loads a and N-1 reliability requirements. A decomposition approach is developed to solve
the optimization problem efficiently.
4 - A Nonlinear Electrical Capacity Planning Model with
Application to the Case of Indonesia
Wanshan Zhu
We extend the linear model of Integrated Resource Strategic Planning
(IRSP) of long term capacity planning to a nonlinear model so that we
can study, in addition to capacity, the utilization hours as decision variables. Furthermore, we apply the regularization method to this planning problem so that we can find among multiple solutions the one
which is most friendly to renewable energy. We apply the model to Indonesia and find surprisingly that the demand side management does
not necessarily reduce the green house emissions.
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Friday, 10:30-12:00 - Room 122
Team and Assignment Optimization
Stream: Timetabling and Rostering
Contributed session
Chair: Wilmer Atoche
1 - Genetic Algorithms Applied to Management of Customer Portfolio and Management of Daily Schedules
for a Bank Sales Workforce
Ricardo Soares Boaventura, Christina Marques Testa, Keiji
Yamanaka
The problem of defining the Daily Schedule for employees to sell products is strategically important for companies to minimize cost, increase
efficiency and profit. This problem is similar multi-traveling salesman/vehicles problems, with the difference of selecting clients according to higher profitability and strategies. The daily goal is to discover
the best route to be built for visiting clients always starting and returning in the same point. The proposed system was developed using the
techniques of genetic algorithms and can be accessed via the Web and
is linked to Google Maps.
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3 - Optimal Allocation of Football Team
Wilmer Atoche
The purpose of this paper is to demonstrate the use of optimization
tools applied to obtain an ideal football team. The assessment of each
football player is its performance parameters at each position of the
football field and using integer linear programming, one can optimize
the initial alignment, changes of team players that can be performed
during the game and other applications.
4 - About Some Characteristics that are common in Optimization Projects Involving Human Resources
Juan Manuel Garcia Lopez
Various classes of Operations Research problems deal with Human Resources. Examples are Timetabling, Task Scheduling, Rostering, Shift
assignment or Routing. Unlike other scarce material resources, Human
Resources are of a special nature, forcing them to be managed carefully
when implementing a project. If one of those projects is modeled ignoring their special characteristics, the likelihood of stakeholder’s dismissal of the solution increases. This presentation shares some project
management lessons learned while implementing various optimization
projects dealing with Human Resources.
FB-11
Friday, 10:30-12:00 - Room 113
Euclidean Distance Geometry and
Applications
Stream: Combinatorial Optimization
Invited session
Chair: Nelson Maculan
Chair: Antonio Mucherino
1 - Some Notes of Euclidean Distance Geometry and
Graph Theory Involving Telecom, Computer Networks and Molecular Biology Applications
Rosiane deFreitas, Bruno Cardoso Dias, Nelson Maculan,
Carlile Lavor
In this work, the relationship between Euclidean distance geometry
and graph theory will be explored, where some operational research
problems will be considered, involving theoretical models and computational techniques proposed for channel allocation problems in wireless networks, detection of malicious code in computer systems, and
determining of the 3D structure of protein molecules. Implicit enumeration algorithms will be presented, addressing issues of feasibility
and optimality of solutions, with emphasis on the method of branchprune-and-bound.
2 - New Developments on the Application of the Hyperbolic Smoothing Technique to Solve the Distance Geometry Problem
Helder Venceslau, Adilson Elias Xavier
In the very beginning, the Hyperbolic Smoothing (HS) Technique was
employed to solve distance geometry problems (DGPs) mainly as a
heuristic tool, but some of its basic properties had already been established, remarkably its convexification power in a limit situation. Recent research has shed some light on the convergence process, which
helps to explain its high success rate compared to the resolution of the
classical minimum sum-of-squares formulation of the problem. Latest
theoretical and computational developments regarding the application
of HS to solve DGPs will be presented.
2 - An Application for a Laboratory Assignment with Rotations
Takeshi Koide
3 - Numerical Solution of The Euclidean Problem in nSpace
Virginia Costa, Brígida Sartini, Marcia Fampa, Nelson
Maculan
An application based on spreadsheet software is developed for an assignment in a course in author’s department. The course aims to provide experiences of research activities to junior students and the students are assigned to three different laboratories. The assignment task
is conducted by a faculty member, who has to consider student’s preference of laboratories and as well as the capacities of laboratories with
rotations. The assignment is modeled as a mixed-integer programming
problem and the developed application seeks an optimal solution for
the problem.
The Euclidean Steiner tree problem (ESTP) in Rn consists of finding a
tree of minimal Euclidean length that spans a given set of points in Rn,
using or not additional points. Only a few papers consider the exact solution for the ESTP in Rn (n>2) and there are just two works that considered a mathematical programming formulation for the ESTP. One
of them presented a convex mixed-integer formulation that could be
implemented in a Branch and Bound (B&B) algorithm. This work
presents techniques to improve the performance of the B&B algorithm
in order to implement this formulation.
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IFORS 2014 - Barcelona
4 - Molecular Distance Geometry and Atomic Orders
Antonio Mucherino
The Molecular Distance Geometry Problem (MDGP) is the one of finding the conformation of a molecule while exploiting the available distances between some pairs of its atoms. The MDGP is NP-hard and is
usually reformulated as a global optimization problem in a continuous
space. We are working on a subclass of instances for which this space
can be discretized, and on a branch-and-prune (BP) algorithm for their
solution. In order to perform the discretization, MDGP instances have
to satisfy some assumptions, that strongly depend on the order in which
the atoms of the molecule are considered.
FB-13
Friday, 10:30-12:00 - Room 123
Scheduling Applications 2
Stream: Scheduling
Invited session
Chair: Sanja Petrovic
Chair: Greet Vanden Berghe
1 - Scheduling Patients for Surgery
Chris Potts, Marion Penn, Paul Harper
FB-12
Friday, 10:30-12:00 - Room 004
Scheduling Models in Operational
Decision Making
Stream: Scheduling under Resource Constraints
Invited session
Chair: Joanna Jozefowska
Chair: Francisco Ballestin
1 - ORAS: Route Optimization System for the Hospital at
Home Service
Sacramento Quintanilla, Francisco Ballestin, M.Pilar Lino, M.
Angeles Pérez, Vicente Valls
ORAS is a mobile route-planning application developed for use in the
home hospitalization (HH) service. Doctors and nurses who provide
HH services must travel by taxis to different homes where their patients are hospitalized. The software is designed to show daily the
most efficient route to be taken by each doctor and nurse and to update
in real time the information about the routes. A graphic visualization
is used to show the routes taken by each taxi or person. The core is a
set of algorithms that achieves a significant reduction in both cost and
staff waiting times.
2 - Decomposition of a Storage and Retrieval Problem in
a Warehouse
M. Angeles Pérez, Francisco Ballestin, M.Pilar Lino,
Sacramento Quintanilla, Vicente Valls
We work with a warehouse where some forklifts have to store and retrieve pallets, with the objective of performing the given orders in the
minimum time possible. The warehouse works with random storage:
any pallet can occupy different positions. In our problem three block
of decisions have to be made: 1) in which position to store or retrieve
a pallet, 2) which forklift is going to work with each pallet, and 3)
when exactly each order is going to be performed. We decompose
our problem into three different subproblems to solve it. Each of the
subproblems is assigned to one block of decisions.
3 - Metrics and Approximated Solution of Machine
Scheduling Problems
Alexander Lazarev
In this paper, we propose a new approximation scheme for scheduling problems. The scheme is based on search for the polynomially
solvable instance which has a minimal distance in the metric from the
original instance. One can also improve the scheme by constructing
new metrics and finding new polynomially solvable cases of scheduling problems.
4 - Scheduling an Injection Plant with Order Dependent
Setups
Joanna Jozefowska, Marek Goslawski, Marcin Kulus, Jenny
Nossack
A scheduling problem observed in an injection molding plant is presented. The problem involves time consuming changeover operations.
The objective is to maximize the plant productivity. Scheduling constraints follow from limited availability of staff responsible for the
changeovers. A two stage approach is proposed. At the first stage
jobs are assigned to machines and the order of jobs on each machine
is fixed. At the second stage the operators are assigned to machines.
The schedules are compared with schedules generated by a dedicated
greedy heuristics and by an experienced dispatcher.
Patients are referred to hospital for surgery and a scheduling policy
determines the day of their operation. Emergencies must be treated
immediately, while other patients have due dates that depend on their
condition. Scheduling rules depend on whether the booking for a patient is immediate or can be delayed, the priority rule among patients to
be booked, and the order in which potential booking dates are searched.
Using data from a case study, we evaluate our scheduling rules using:
due dates being met; average patient waiting time; operating theatre
overruns; and fairness to patients.
2 - Hot Strip Mill Scheduling under Consideration of Energy Consumption
Karen Puttkammer, Matthias Gerhard Wichmann, Thomas
Spengler
In steel industry hot rolling is an energy intensive process as steel slabs
need to be heated before being rolled on the hot strip mill. The energy
consumption is determined by the production schedule. Due to rising
energy prices decision support for the hot strip mill scheduling problem
(HSMSP) under consideration of energy consumption becomes necessary. This contribution is based on a new MILP formulation. Therein
the energy requirement for heating is modeled according to causation.
We propose a problem specific heuristic solution approach and present
first numerical results.
3 - Reception, Mixture and Delivery of Crude Oil in a Terminal
Bernardo Zimberg, Eduardo Camponogara, Enrique Ferreira
This paper refers to the reception, mixture and delivery of crude oil.
Each tank at the terminal receives different qualities from different cargos that arrive in predefined periods. Transfer is allowed between tanks
and the main pipeline to the refinery. There is a schedule of crude oil
quality mixtures and volumes required by the refinery. The problem
consists in finding an optimized schedule that meets the constraints.
An MILP model is proposed, analyzed, and solved for a specific case.
The tool can be applied to determine the optimal schedule of crude oil
operations over a time horizon.
4 - Optimal Scheduling for Storage and Retrieval of Assembly Blocks in Temporary Storage Yard for Shipbuilding Process
Byung-Hyun Ha, Jung-Ryoul Son
This paper studies scheduling of storing and retrieving assembly
blocks in a temporary storage yard for shipbuilding process. The objective is to minimize the number of relocations of blocks subject to
the storage and retrieval time windows being satisfied. We show the
problem is NP-hard and present a mixed-integer programming model
based on multi-commodity network flows. The revised models are proposed by investigating the properties in the problem. To overcome the
computational inefficiency, an A* algorithm is devised and the performance is validated through the numerical experiments.
FB-14
Friday, 10:30-12:00 - Room 124
Shop Scheduling
Stream: Scheduling
Invited session
Chair: Waldemar Kaczmarczyk
244
IFORS 2014 - Barcelona
1 - Some Finite Planning Horizon Inspection Models
with Non-Negligible Inspection Times
Honest Chipoyera
Finite planning horizon Inspection models with non-negligible inspection times are developed for a system whose time to failure has a known
probability distribution. Two scenarios are explored: 1) inspections
take place while the system is running, 2) whenever the system has
to be checked, it is switched off completely. For these two scenarios,
two sub-scenarios each are studied: a) all inspections are of the same
fixed duration and b) inspection times are random variables following
a known probability distribution. Maximization of profit is used as the
sole optimization criterion.
2 - Makespan Poorly Approximates Machine Utilization
in the Flow Shop System
Waldemar Kaczmarczyk
Maximization of machine utilization is the most popular objective in
production scheduling. It is, however, usually replaced by minimization of the schedule length which is unambiguously defined and easy
to compute. First, we show that for the flow shop problem makespan
poorly approximates machine utilization, because it ignores overlapping of consecutive schedules. Next, we propose new method to estimate machine utilization which considers production over multiple
periods (shifts). Finally, we show that maximal utilization may be
achieved with relatively simple algorithms.
3 - Decoupling time and cost in project performance
management
Homayoun Khamooshi
The EVM and its derivatives (e.g., Earned Schedule) use cost as a
proxy to measure schedule performance to control duration of the
project. In this research the authors have decoupled new schedule performance measures to evaluate efficacy and efficiency of the schedule
and planned duration at any level of the project. These new indices
are easy to understand, have a wider application, and can be used by
contractors, clients and the scheduling offices to assess and measure
schedule performance. The technique is called EDM (Earned Duration Management).
4 - Minimising the Sum of Total Tardiness and Earliness
in a Flow Shop Scheduling using Hybrid Genetic Algorithm
Ashwani Kumar Dhingra, Sunita Dhingra
Present work considers the flow shop scheduling problems for minimizing the sum of total tardiness and earliness under sequence dependent setup time (SDST). Hybrid Genetic Algorithm (HGA) has been
proposed in which the generation of seed sequence has been obtained
from the earliest due date (EDD) rule denoted as HGA (EDD), EDD
followed by NEH procedure denoted as HGA (NEH_EDD) and simple GA. From the comparative analysis, it has been found that HGA
(NEH_EDD) provides the superior results for minimizing the sum of
total tardiness and earliness criteria for SDST flow shop scheduling
problems.
FB-15
Friday, 10:30-12:00 - Room 125
Experimental Research in Management
Accounting and Management Control 3
Stream: Experimental Perspectives and Challenges in
Management Accounting and Management Control
Invited session
Chair: Stephan Leitner
1 - Diagnostic Study about the Utilization of Shared Service Centers for Municipalities of Southern Brazil
Gustavo Krüger, Rogrigp Correa
This paper aims to diagnose the use of Shared Services Centers (SSC)
by the Brazilian municipalities. To achieve this goal, a survey was performed covering the 102 most populous counties in southern Brazil,
FB-16
using the questionnaire as a tool for data collection. The main findings show that were not identified SSC constituted under the sample
surveyed and that virtually 100% of the managers participating in the
research has no knowledge about SSC, even though the SSC is, nowadays, a practice widely adopted internationally, according to a study of
Krüger, Corrêa and Vanti (2013).
2 - Slovak Business Cycles in the Post-Communist Era
Martin Lukáčik, Karol Szomolányi, Adriana Lukáčiková
Computing Slovak average PPP converted GDP per capita; considering a Slovak population size we state, that Slovak economy is small,
emerging and open. However, computing cyclical properties of the
chosen variables we state that Slovak business cycles suit for an open,
rich economy more. Using VAR specification we consider that production shocks are main source of the Slovak business cycles. The small
open real business cycle model is suitable to explain Slovak business
cycles. Calibrating parameters of the model, we state that the model
better fits data when we use the CES production function.
3 - Experimental Evaluation of a Set of Multi-Criteria Decision Making Methods
Sajid Siraj, Alessio Ishizaka
Three multi-criteria decision making (MCDM) methods have been experimentally evaluated for their usefulness in solving a specific problem. Participants were asked to rank five available coffee shops using
the MCDM tools. Their rankings were also recorded before and after the experiment. A voucher was offered for the shop suggested by
the initial or MCDM ranking. If the subject showed dissatisfaction
with the choice, s/he was offered an exchange for a small fee. The
results were statistically compared in order to determine how the decision evolves with the use of these MCDM tools.
FB-16
Friday, 10:30-12:00 - Room 127
Industrial Applications of Machine
Learning
Stream: Intelligent Optimization in Machine Learning
and Data Analysis
Invited session
Chair: Anton Khritankov
1 - Customer Churn Analysis in Telecommunication Industry
Mehmet Yahya Durak, Ilayda Ulku, Fadime
Üney-Yüksektepe
Churn management is an important issue for telecom companies. In
Turkey since 2009, it has been possible to change the GSM operator
without changing the cell phone number. Thus, competition increases
and customer loyalty become more important. In this research, a questionnaire is applied to obtain the real data of GSM users’ information
and behavior of the churn possibility. Hence, this research analyzes
the obtained data by using existing data mining algorithms in order to
determine the important factors for the churn prediction and to find the
possible customer behaviors about loyalty.
2 - Data Mining Application for Production Systems:
R2R Controller Design in Multi-Item Production Systems
Cheong Sool Park, Youngji Yoo, Jun Seok Kim, Sung-Shick
Kim, Jun-Geol Baek
In the paper, we propose a R2R control model for multi-item production systems. In the multi-item environment, the types of products or
types of layers are rapidly changed run-by-run or by time and also the
status of facilities are changed run-by-run. So we propose a new R2R
control model which is able to explain both effects of the types of products and the status of equipment by time. The proposed model consists
of the term of general effects, types of products or layers effects and
time effects. The recursive estimation method distributes cause and
effects to each term.
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IFORS 2014 - Barcelona
3 - Strategic Indicators for Science and Technology
Competency Analysis
Sejung Ahn, Oh-Jin Kwon, Dohyun Kim, June Young Lee,
Kyung-Ran Noh
1 - A Multiobjective Resource Allocation Problem in
Project Scheduling
Chao Chen, Guangquan Cheng, Baoxin Xiu, Jincai Huang,
Weiming Zhang, Cheng Zhu
It is very important to identify the current position and trends of each
national science and technology for the R&D planning. In particular, the accurate analysis and diagnosis based on objective information
is essential. For this, the information analysis should be performed
through multilateral aspects using a variety of indicators. In this research, strategic indicators were investigated for science and technology competency analysis using journal publications. By applying these
indicators to bio- and nano-technologies, the national research profiles
were identified.
Resource allocation involves allocating finite resources to the activities
of a given baseline schedule which obtains by the RCPSP-schedule.
The objective of our research is to develop a multiobjective optimization approach for the resource allocation problem. A multiobjective
optimization heuristic which incorporates problem specific knowledge
is then designed to obtain the Pareto optimal solutions. Finally, extensive computational results obtained on a set of benchmark problems
are reported.
FB-17
Friday, 10:30-12:00 - Room 005
Combinatorial Structures
Stream: Graph Searching
Contributed session
Chair: Nancy Clarke
1 - On Efficient Unique Maximum Matching Algorithms
Eugen Mandrescu, Vadim Levit
If the matching number and the vertex cover number of a graph G
are equal, then G is called a Konig-Egervary graph. Bartha (2010)
conjectured that a unique perfect matching in a graph G, if it exists,
can be found in linear time in terms of the size of G. In this research
we validate this conjecture for both Konig-Egervary graphs and unicylic graphs. More specifically, we use a variation of Karp-Sipser leafremoval algorithm (1981), which ends with an empty graph if and only
if the original graph is a Konig-Egervary graph with a unique perfect
matching.
2 - Mathematical Programming Models and Relaxations
for the Minimum Hub Cover Problem
Belma Yelbay, S. Ilker Birbil, Kerem Bulbul
We introduce a new combinatorial optimization problem, named minimum hub cover (MHC) problem. MHC problem is solved to increase
the efficiency of query processing over graph databases. This problem
is known to be NP-hard. We first give an integer programming formulation and then introduce several relaxations based on linear programming and semi-definite programming. After discussing the relations
among these formulations, we present a comprehensive computational
experiment to investigate the empirical performances of the proposed
mathematical models.
3 - An Improved Iterated Greedy Algorithm for the Minimum Weighted Dominating Set
Salim Bouamama
In this contribution we consider the implementation of an improved
iterated greedy algorithm for the minimum weighted dominating set
problem (MWDS). MWDS is a classical, NP-complete optimization
problem in graph theory with many applications such as clustering
in wireless networks, formation of a routing backbone and multidocument summarization in information retrieval. Given a graph with
weighted vertices, the goal of MWDS is to find a subset of vertices
with minimum total weight such that each vertex of the graph is either
in the subset or adjacent to at least one vertex in the subset.
FB-18
Friday, 10:30-12:00 - Room 112
Applications of Multiobjective
Optimization II
Stream: Multiobjective Optimization - Theory, Methods
and Applications
Invited session
Chair: Guilhem Raffray
246
2 - Shape Optimization of Rotating Disks
Dmitry Khominich, Fedor Gubarev, Alexis Pospelov
The methodology for structural design of rotating disks was developed.
The disk was considered as axisymmetric rotating part of aircraft engines subjected to thermal, inertial, blade and fit forces. Methods of
static stress analysis and low-cycle fatigue life prediction were used
to predict disk performance. The goal was to determine the shape of
the disk cross section with minimum weight and maximum fatigue cycles. The family of Pareto-frontiers was obtained for different rotating
speeds by mean of descent-diffusion optimization approach.
3 - Multi-Objective Optimization for the Design of Fish
and Meat Hot-Smoking Processes
Guilhem Raffray, Patrick Sebastian, Antoine Collignan
The purpose of this work is the food process design optimization for
the production of African traditional hot-smoked products. Based on
a methodology of interpretation and aggregation of multiple industrial
constraints, a multi-objective decision tool is developed for improving
the technological performances of productivity, energy efficiency and
product quality. A genetic algorithm evaluates various design alternatives and converges to the most desirable solution. The optimized
solution is then subjected to a sensitivity analysis to consider the lack
of reliability of some field data.
4 - Multiple Criteria Simulation Optimization: Further
Refinements
Esmeralda Niño Pérez, Mauricio Cabrera-Ríos
Pareto Efficiency conditions are used in an iterative framework based
on experimental design, and pairwise comparison. In particular, this
work improves upon the use of Data Envelopment Analysis to determine the efficient frontier, as well as, the use of a single-pass algorithm
previously proposed by our research group. The results show a rapid
convergence to a more precise characterization of the Pareto-efficient
solutions. The revised algorithm is illustrated by a series of cases in
manufacturing systems simulation.
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Friday, 10:30-12:00 - Room 128
New Methods for Multiobjective
Optimization
Stream: Multiobjective Optimization - Theory, Methods
and Applications
Invited session
Chair: Alan Pearman
1 - Complete Efficient Frontier of Bicriteria Nonlinear
Separable Discrete Optimization Problems with Multiple Constraints
Yuji Nakagawa, Sakuo Kimura, Ross J. W. James, Chanaka
Edirisinghe
We propose a technique for finding all efficient solutions of the bicriteria nonlinear separable discrete optimization (BINSDO) problem using
a unique enumeration approach, termed the Target Method, which is
based on a surrogate constraint method (Management Science, March
1914). As the Target Method does not use DP dominance, it can be
applied to instances with multiple constraints. The Target Method is
also superior to existing algorithms for 0-1 separable discrete problem
with a single constraint in both speed and accuracy, whilst improving
the number of efficient solutions.
IFORS 2014 - Barcelona
2 - A new Algorithm for Optimizing a Linear Fractional
Function over an Integer Efficient Set of a Multiple
Objective Linear Problem
Younsi Née Abbaci Leila, Mustapha Moulai
In many situations, a decision maker faces a large number of different
efficient solutions and the selection of her preferred solutions becomes
a very hard task. A way of assessing some preferred solution is by optimizing a function over the efficient set. In this work, a new algorithm
is developed that optimizes an arbitrary linear fractional function over
an integer efficient set of a Multiple Objective Integer Linear Programming problem (MOILP). The proposed method is based on a simple
selection technique that improves the principal objective value at each
iteration.
3 - An Enumerative Cutting Plane Approach to Integer
Linear Vector Optimization Problems
Walter Habenicht
The approach presented in this paper is a hybrid approach, using cutting planes and enumeration. In the interactive part of the procedure
the decision maker controls the searching process by defining regions
in outcome space. Cutting planes are used to install a stopping rule that
guarantees under customary conditions the optimality of the solution.
4 - Identifying a Maximally Representative Sample: A
Linear Binary Goal Programming Formulation
Alan Pearman
An analyst must select a sample of size s from a population, size n.
Each member of the population has a number of characteristics - for
example big/small; old/young/middle-aged; male/female; etc.. The
chosen sample must contain at least a certain number in each of these
categories. If s is small relative to n, it may be impossible to select a
sample meeting all constraints and the constraints will need to be prioritised. The paper presents a linear binary goal programming model
to search for an acceptable sample with an application to the evaluation
of EU Framework 7 research projects.
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3 - A Dynamic Stochastic Unit Commitment Formulation
to Accommodate Wind Uncertainty
Canan Uckun, Audun Botterud, John Birge
There is a rapid increase in renewable energy generation in many parts
of the world. New methods and approaches in electricity market operations are needed to efficiently manage the continuing increase in
variability and uncertainty caused by expanding renewable resources.
This paper proposes an improved stochastic programming approach
for accommodating wind power uncertainty in electricity markets. The
proposed formulation improves the standard two-stage stochastic unit
commitment problem by incorporating a more dynamic representation
of the scheduling decisions.
4 - Stochastic Market Clearing in Electricity Markets
with High Penetration of Wind Energy: Air emissions
Reductions and Economic Savings
Ali Daraeepour, Dalia Patino-Echeverri
This study measures the impacts of employing stochastic market clearing in a market-based power system. The benefits are in terms of
reduced costs of the integration of variable energy resources (VERs)
relative to deterministic market clearing models including, reduction
in costs and air emissions from ancillary services required to manage
the variability of these resources, and reduction in costs and air emissions from reduced wind-power curtailment. In order to increase the
efficiency of the stochastic model, scenario generation and reduction
techniques have been also employed.
FB-21
Friday, 10:30-12:00 - Room 006
Cutting and Packing 6
Stream: Cutting and Packing
Invited session
FB-20
Friday, 10:30-12:00 - Room 129
Stochastic Unit Commitment with
Renewables
Stream: Stochastic Optimization in Energy
Invited session
Chair: Warren Powell
1 - A Dynamic Programming Approach to the Ramp
Constrained Intra-Hour Stochastic Single-Unit Commitment Problem
Ditte Heide-Jørgensen, Trine Krogh Boomsma, Pierre Pinson
We consider the problem of single-unit commitment (1UC) in a power
system with renewable energy. To account for the intermittency of
renewable generation and the resulting additional system flexibility requirements, we assume a fine time resolution of the scheduling horizon
and consider ramping. We extend existing deterministic dynamic programming formulations of the 1UC problem to include stochastic wind
power generation. In doing so, we consider how and when to account
for updates of information, and put special efforts into modeling uncertainty in wind power forecasts as a Markov chain.
Chair: Guntram Scheithauer
1 - Minimal Proper Non-IRUP Instances of the OneDimensional Cutting Stock Problem
Guntram Scheithauer, Vadim Kartak, Artem Ripatti
We consider the well-known one-dimensional cutting stock problem
(1CSP). It is shown that all possible instances of the 1CSP can be divided into a finite number of equivalence classes when the number
of items is fixed. A method for enumerating all these classes is investigated. This method is improved for searching proper non-IRUP
instances with minimal number of items. We found that the minimal
number of items is 10 when a proper non-IRUP instance exists. We
also found 365 equivalence classes that consist of such instances.
2 - New Inequalities for 1D Relaxations of the 2D Strip
Packing Problem
Isabel Friedow, Guntram Scheithauer
We investigate a heuristic for the 2-dimensional rectangular strip packing problem (2DSPP) that constructs a feasible packing by placing 1dimensional cutting patterns obtained by solving the horizontal 1D bar
relaxation (1DHBR). To represent a solution of 2DSPP, a 1DHBR solution has to satisfy, among others, the vertical contiguous condition.
To strengthen the 1DHBR with respect to that vertical contiguity new
inequalities were formulated and numerically analyzed.
2 - SMART-ISO: An Informationally Correct Model of the
PJM Energy Markets and Power Grid
Warren Powell
3 - Branch-and-Price Methods for the 1D Contiguous
Bin Packing Problem
Marat Mesyagutov, Guntram Scheithauer, Gleb Belov
SMART-ISO is a detailed simulator of the PJM energy markets and
power grid. It accurately captures the day-ahead unit commitment,
intermediate term scheduling (every 30 minutes) and real-time economic dispatch (every 5 minutes). Generator scheduling reflects limits
on notification times, which provides a precise model of uncertainty in
each decision. We report on studies of high penetrations of renewables,
and we describe the design of robust policies which eliminate outages
while maximizing energy utilization from renewables, exploiting the
properties of AC power flow networks.
We consider the 1D contiguous bin packing problem (CBPP-1). Being
a relaxation of the 2D strip packing problem, CBPP-1 is also relevant
for different areas, e.g., for scheduling. To tackle CBPP-1, we use
a Gilmore-Gomory model, which is a Dantzig-Wolfe decomposition
of the position-indexed formulation. In order to obtain a contiguous
structure for the optimal solution, its basis matrix must have a consecutive 1’s property. For construction of such matrices, we develop
new branch-and-price algorithms which are distinguished by various
strategies for the enumeration of partial solutions.
247
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IFORS 2014 - Barcelona
4 - A Two-Objective Two-Dimensional Cutting Stock and
Assortment Problem
Banu İçmen, Refail Kasimbeyli
In this work we study two-dimensional cutting stock (2DCSP) and assortment problem where stock of different sizes is available and a set
of rectangular items has to be obtained through guillotine cuts. We
propose a two-objective mixed-integer programming model for the
2DCSP. The objective functions are formulated in the form of minimizing the global area of the used stock materials that is the total
trim loss, and the number of used stock types. Different scalarization
methods are used to solve the developed two-objective mixed-integer
programming model and obtained solutions are compared.
FB-22
Friday, 10:30-12:00 - Room 007
Advances in Service Process Analysis
Stream: Game Theory and Service Management
Invited session
Chair: Jan Van Mieghem
1 - Optimal Design of Co-Productive Services: Interaction and Work Allocation
Guillaume Roels
In this paper, we develop an analytical model of joint production between a service provider and a customer and characterize how a service
firm should design its co-productive system. We show that, as a task
becomes more standard, it is desirable to decrease the degree of interaction between the provider and the customer by making their efforts
more substitutable and to allocate most of the work to whoever is the
most efficient. Our analysis gives rise to a service-process framework
with three archetypes of co-productive services: collaborative services,
service factories, and self-services.
2 - Collaboration and Resource Sharing in Networks
Jan Van Mieghem
We study collaboration and resource sharing in processing networks.
We start by describing the challenges that collaboration and resource
sharing brings to network capacity (maximal throughput). We present
conditions on the network’s collaboration architecture that guarantee
that simple bottleneck analysis truly captures the capacity of the process. We then proceed to study control of synchronization under nonpreemption. We find that synchronization of collaborating resource
under non-preemptions introduces fundamental and non-trivial tradeoffs between throughput and controllability.
3 - Staffing Service Systems When Capacity Has a Mind
of its Own
Martin Lariviere
We examine a service provider that has contracted to process a flow of
transactions but which allows its workers to design their own schedules. Hence, the firm must make sure it has enough staff over the
horizon but cannot directly assign agents to time intervals. We show
that if the firm offers constant compensation terms over periods with
varying demands, low demand periods will be overstaffed. Adjusting
the per-transaction compensation or by limiting the number of agents
that can sign up in each period corrects this.
1 - A Variable Neighbourhood Metaheuristic for the
Clustered Vehicle Routing Problem
Christof Defryn, Kenneth Sörensen
A vehicle routing problem in which clients are partitioned into clusters is called a clustered vehicle routing problem (CluVRP). Clients
belonging to the same cluster should be visited by the same vehicle
sequentially in the same path. We divide the problem in two underlying combinatorial problems: the bin packing problem - at the level
of the clusters - and the travelling salesman problem - at individual
client level. Different local search operators at each level, embedded
in a variable neighbourhood metaheuristic framework, are combined
to obtain high quality solutions.
2 - A Parallel Iterated Local Search Heuristic for Heterogeneous Fleet Vehicle Routing Problems
Juliana Silva, Puca Huachi Penna, Eyder Rios, Ricardo Farias,
Luiz Satoru Ochi
This paper introduces a parallel Iterated Local Search (ILS) heuristic
for solving the Heterogeneous Fleet Vehicle Routing Problems. The
proposed parallel heuristic merges concepts of different metaheuristics
on a parallel environment, to take advantage of multiple-core processors and GPUs. The combination of these elements, along with a cooperation mechanism carried out by parallel tasks, enabled to develop an
efficient algorithm. In order to present the effectiveness of the parallel
heuristic, the achieved results are compared with those obtained by a
sequential version of the heuristic.
3 - Iterated Local Search Algorithm for the Open Vehicle
Routing Problem with Time Windows
Jose Brandao
The problem studied here is the open vehicle routing problem with
time windows (OVRPTW). This problem is identical to the vehicle
routing problem with time windows, except that the vehicles do not
return to the distribution depot after delivering the goods to the customers. The OVRPTW has been solved with an iterated local search
algorithm, taking as first objective to minimize the number of routes
of the solution and as second objective minimizing the total distance
travelled. The performance of the algorithm is tested using a large set
of benchmark problems.
4 - A Parallel Iterated Local Search Algorithm on GPUs
for Quadratic Assignment Problems
Erdener Ozcetin, Gurkan Ozturk
It is getting widespread to develop meta-heuristics on GPUs, with the
motivation of decreasing solution time of combinatorial optimization
problems. Up to 50x speed-ups are gained in recent studies. In this
study, a parallel iterated local search algorithm has been proposed to
solve the QAP on GPUs. This parallel algorithm and the sequential one
on central processing units are tested and compared for test problems
in literature. Indeed, it is observed that the parallel algorithm works
averagely 6.31x for Skorin problems and 11.93x for Taillard problems
faster than sequentially one.
FB-24
Friday, 10:30-12:00 - Room 212
Tools and Applications in Actuarial
Sciences
Stream: Actuarial Sciences and Stochastic Calculus
Invited session
Chair: Anna Castañer-Garriga
1 - On Log Convex and Log Concave Discrete Random
Variables Associated with Counting Processes
Carmen Sangüesa, Francisco Germán Badia
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Friday, 10:30-12:00 - Room 008
VNS and ILS
Stream: Metaheuristics
Contributed session
Chair: Jose Brandao
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Counting processes are important in insurance as they can describe
the arrivals of claims in an insurance company. In the present talk we
consider a counting processes stopped at a random time T, independent of the process. Provided that T is log concave (log convex), we
give sufficient conditions on the arrival times so that the number of
events occurring before T preserves this property. We study both log
concavity and log convexity preservation, under the assumption that
the process has independent interarrival times. We also apply the log
concavity results in inventory models.
IFORS 2014 - Barcelona
2 - Sustainability of Public Pension
Tadashi Uratani
The financial sustainability of public pension requires that the reserve
should be positive to pay the benefit in the demographic and economical environment change subject to the certain level of the income replacement ratio. Assuming the market asset and the income for pension follows an Ito processes and we maximize the net present value
of pension for the cohort, to guarantee the pension fund sustainability, we apply the martingale method of the optimal consumption and
investment theory. We use the age-structured model to the pension
population change.
3 - Order Statistics and Insurance Risk Models
Claude Lefèvre
This paper points out and exploits a close connection between the joint
distribution of order statistics and the finite-time ruin probability in a
class of insurance risk models. An extension to insurance risk models
with two classes of insurance business is then investigated. The key
mathematical tool is a special family of Appell polynomials with one
or two variables.
4 - Optimal Stop-Loss Reinsurance: A Dependence
Analysis
Anna Castañer-Garriga, M. Mercè Claramunt
The stop-loss reinsurance stands out among reinsurance contracts in
the insurance market. It presents an interesting property: it is optimal
if the criterion of minimizing the variance of the cost of the insurer is
used. We analyse this contract in one period from the point of view
of the insurer and the reinsurer. Firstly, the influence of the parameters of the reinsurance on the correlation coefficient between the cost
of the insurer and the reinsurer is studied. Secondly, the optimal stoploss contract is obtained if the criterion used is the maximization of the
joint survival probability.
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Friday, 10:30-12:00 - Room 009
Applications of Metaheuristics
Stream: Applications of Heuristics
Contributed session
Chair: Hiroyuki Ebara
1 - A new Heuristic Approach to the Set-Partition Problem
Goranka Nogo, Ivo Ivanisevic
We propose a new heuristic algorithm for solving the set-partition
problem. Our algorithm is based on a combination of the best features
of a greedy approach and Karmakar-Karp differencing algorithm. The
computational results show that our approach has good performance.
In some cases, we achieve significantly better results than both greedy
approach and Karmakar-Karp algorithm.
2 - A Dual Search Method for Routing Problems
Mona Hamid, Jamal Ouenniche
Routing problems have been at the origin of the design of many optimal and heuristic solution frameworks such as branch-and-bound algorithms, branch-and-cut algorithms, local search methods and metaheuristics. In this research, we design a new dual local search for routing problems and test its performance on the TSPLIB instances. Computational results suggest that the proposed dual search framework is a
promising design.
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4 - Scheduling Container Trains at Port Botany
Daniel Harabor, Daniel Guimarans, Pascal Van Hentenryck
In a recent work we showed that there exists significant unrealised rail
capacity at Sydney’s Port Botany. Unlocking this capacity depends on
better management of rail resources, including improved staging and
scheduling practices. We study the impact of several such changes:
(i) we replace fixed servicing windows with anytime servicing; (ii) we
apply constraints to train length and rake utilisation; (iii) we schedule
and stage trains holistically, between the port and intermodal terminals
in the Sydney area. We aim to consolidate trains and move the same
container volume with fewer trips.
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Friday, 10:30-12:00 - Room 010
Multiobjective Bi-Level Optimization
(contributed)
Stream: Nonsmooth Optimization and Variational Analysis
Invited session
Chair: Susanne Franke
1 - Convexification in Multiobjective Semi-Infinite Programming
Francisco Guerra-Vázquez, Jan-J Ruckmann
We deal with multiobjective semi-infinite nonconvex optimization
problems which are defined by finitely many objective functions and
infinitely many inequality constraints in a finite-dimensional space.
Under the reduction approach it is shown that, locally around a proper
efficient solution, this problem can be transformed equivalently in such
a way that the Lagrangian of the associated weighted sum optimization
problem corresponding to the transformed problem is locally convex
around the proper efficient solution.
2 - Nonsmooth Multiobjective Bilevel Optimization Problem under Generalized Invexity
Hachem Slimani, Karima Bouibed, Mohammed Said Radjef
We consider a nonsmooth nonlinear optimistic bilevel optimization
problem where the upper-level and the lower-level are vector optimization problems. By using Karush-Kuhn-Tucker type conditions
associated to the lower-level problem, we reformulate the bilevel optimization problem into an equivalent nonlinear multiobjective singlelevel optimization problem with inequality constraints, under appropriate constraint qualification and generalized invexity assumptions. We
study the obtained problem and we establish necessary and sufficient
optimality conditions under generalized invexity.
3 - Parallel Consultant-Guided Search for the Traveling
Salesperson Problem
Koki Nakayama, Hiroyuki Ebara
3 - A Proximal Point Method with Generalized Distances
for a Class of Bilevel Equilibrium Problems
João Xavier da Cruz Neto, Glaydston Bento, Jurandir
Oliveira, Pedro Soares Junior
Metaheuristic algorithms have been studied as a method for solving combinatorial optimization problems. Recently, the ConsultantGuided Search (CGS) for solving the Traveling Salesperson Problem
(TSP) has been proposed. In this paper, we propose a parallel method
which assigns consultants and clients of the CGS to processes of computers and calculates an approximation solution for the TSP. We execute a computer experiment with the benchmark instances (TSPLIB)
by 10 quad-core computers. Our algorithm provides a solution with
less than 6% error rate for problem instances of 3038 cities.
We consider a bilevel problem involving two pseudomonotone equilibrium bifunctions and show that this problem can be solved by an
interior proximal point method with generalized distances. We propose a framework for the convergence analysis of the sequences generated by the algorithm. This class is very interesting because it covers
mathematical programs and optimization problems over equilibrium
constraints.
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IFORS 2014 - Barcelona
4 - Bilevel Road Pricing: A Solution Algorithm
Susanne Franke
We consider a road pricing problem which is modeled as a bilevel programming problem: The leader represents the owner of the network
who wants to influence the traffic flow by determining tolls, and the
follower represents the user of the system. In order to solve this problem, we use the optimal value reformulation of the bilevel programming problem and propose an algorithm. We investigate the structure
of the problem and formulate optimality conditions. We show that it
is possible to find optimal solutions of the problem with the help of an
outer approximation of its feasible set.
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Friday, 10:30-12:00 - Room 213
Infrastructure Development and
Environment 2
Stream: Infrastructure Development and Environment
Invited session
Chair: Fernando Crespo
Chair: Elise del Rosario
Chair: Erik Kropat
1 - Planning Luanda’s Electricity Distribution Network
Expansion using a MILP approach
A. Miguel Gomes, António José Moreira, M. Teresa Costa
This work regards the electrical distribution network of Luanda, analysis and planning of what is considered to be urgent about its expansion,
selection of locations where it is feasible to locate new substations,
appropriate modeling of the real problem and a proposal for an optimal solution to expand the existing network. After analyzing different
mathematical models applied to the distribution expansion problem, an
MILP approach has been considered adequate. The model was solved
by CPLEX. As a means of validation, the solution has been implemented in the Simulator PowerWorld 8.0 OPF.
2 - Optimizing a Supply Chain Network Design under
Network Disruptions
Juan Esteban Muriel Villegas, Juan G. Villegas, Carmen
Patino Rodriguez
This work studies a strategic supply chain (SC) management problem: How to design a Colombian SC network in the presence of transportation network disruptions caused by the national rain season. We
present an optimization model that integrates a multiproduct, multiechelon SC with economies of scale, and a road network prone to failures with site dependent probabilities. Using a stochastic optimization
approach we are able to find a more resilient Colombian SC design
that adapts better to different disruptive scenarios while minimizing
the total costs of the SC.
3 - Selection of Governments Arrangements for Freight
Transport in Mexico City: A Multilevel System
Zaida Estefanía Alarcón-Bernal
With the goal of optimizing the implementation of public politics for
freight transportation into the urban area in Mexico City, this paper
submits a multilevel program model in which the main problem aims
to minimize maintenance costs of the principal roads, taking into account the companies involved in freight transportation within the city,
who seek to minimize their operative costs; on a third level, it is considered the reaction of the population, who aims to minimize the impacts
such as travel time and pollution. The model suggested can be resolved
using a multiparametric approach.
4 - The Challenges in the Waterfront Regeneration by
the Participatory Planning
Tomás Hanáček
The Eastern Europe city planning is becoming more flexible, the cities
are able to absorb the changes in the different time intervals. The
multidisciplinary planning process is based on the communication of
all components of the participatory planning (city government, residents, communities, academia, experts). The unexploited brownfield
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and bluefield areas inside the cities appropriate the public attention.
They have the potential to restart social and economic city development. The regeneration process increases the rate of collective knowledge and creates the specific solutions.
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Friday, 10:30-12:00 - Room 130
Advances in MINLP
Stream: Mixed-Integer Nonlinear Programming
Invited session
Chair: Eva Lee
Chair: Ingmar Vierhaus
1 - Nonlinear Mixed Integer Programming Approach for
Cervical Cancer Treatment
Eva Lee
Cervical cancer is slow-growing and in early stages may not have any
symptoms. Successful treatment remains challenging and the mortality rate in the U.S. is high at about 35%. We describe novel biological
treatment planning designs that incorporate functional PET information for targeted escalated dose delivery. Our study reveals improvement both in local tumor control and organs-at-risk toxicity, two competing and desirable goals that were previously thought to be unachievable simultaneously.
2 - The Convex Hull of Graphs of Polynomial Functions
Wei Huang, Raymond Hemmecke
The convex hull of the graph of a polynomial function over a polytope
is the intersection of all closed half-spaces containing the graph. We
give a description of these half-spaces using semi-algebraic sets. This
gives a finite algorithm to compute the convex hull. For polynomials
in low dimension and degree (related to real applications), a polyhedral relaxation can be computed quickly by an algorithm which can be
extended to a spatial branch-and-bound algorithm for MINLPs.
3 - Embedding Structural Information in SimulationBased MINLP Optimization
Vidar Gunnerud
In this presentation, we present a method designed to find optimal settings, both discrete and continues, for a petroleum production network.
Emphasis is put on the system being divisible into components, as this
underlying assumption motivates the algorithm in its entirety in that
rather simple relations between the system components are modeled
as explicit structural constraints. The significantly more complex relations within each component are based on simulations, or approximations thereof. This results in a simulation based MINLP formulation
with structural algebraic constraints.
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Friday, 10:30-12:00 - Room 011
Societal Complexity and Healthcare
Stream: Methodology of Societal Complexity
Invited session
Chair: Eizo Kinoshita
Chair: Cathal Brugha
1 - Business Game
Zhana Tolordava
Business game "Business and Risk" is implemented in the two game
sections: - The first one is built on the team solving the business case
for establishing a risk management program for the real sector industrial enterprise; - The second one simulates the process of preparing
a business plan for a real electromechanical enterprise by a group of
people interested in acquiring investment from a professional investor
(or a lender bank). Players of this game identify all types of risks that
may arise in the course of the project implementation.
IFORS 2014 - Barcelona
2 - Efficiency of Orthopedic Wards in Acute Hopitals
Zilla Sinuany-Stern, Simona Cohen Kadosh, Lea Friedman
We study the effect of the socio-economic status of patients on the
efficiency of orthopedic wards in all acute hospitals in Israel (20 hospitals), from the view point of the regulator — the ministry of Health.
At the first stage, Data Envelopment Analysis is used with two inputs,
and 3 outputs. As a second stage, regression analysis is utilized to test
the effect of the socio-economic status of patients on the efficiency.
Our hypothesis is that there is a negative effect of the socio-economic
status of patients on the efficiency of orthopedic wards.
3 - Handbook Handling Societal Complexity
Dorien DeTombe
The Handbook ’Handling Societal Complexity: A Study of the Theory of the Methodology of Societal Complexity and the COMPRAM
Methodology with Examples of Applications on Global Safety’, by
Dorien DeTombe, is published. The book describes the theoretical development of the theory and the Compram Methodology, a methodology for policy making for scientists, practitioners, politicians, master
and PhD students in the field of Methodology, Social Sciences, Operational Research, Management and Political Sciences. Examples on
Healthcare, Economics, Climate Change, Terrorism and Floods.
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Friday, 10:30-12:00 - Room 013
P2P, Social Networks and E-commerce
Stream: Telecommunications and Networks
Contributed session
Chair: Yuliya Gaidamaka
1 - Applying Multi-criteria Group Decision Approaches
to Explore Online Group Buying Purchase Intention
Yang-Chieh Chin
Online group buying refers to a certain number users who join via Internet to buy a certain product at a discounted price. It is a multicriteria group decision problem. Thus, this study uses a dominancebased rough set approach (DRSA) to determine the collective decision
rules of the initiators and users, representing a generalized description
of the decision makers’ preference information. The second phase of
the study uses the collective decision rules to classify all decision objects. Practical and research implications are also offered.
2 - Pancake Graph based Solution for Improving Dynamicity in P2P Networking
Amad Mourad, Djamil Aïssani, Mordji Zouweyna
P2P networking has been largely developed in recent time. However,
high dynamicity is already a serious problem in most developed applications. Particular graphs have been proposed as underlying architecture such as De Bruijn and Pancake graphs. In this paper, we propose
an optimized scheme for lookup acceleration in peer to peer network
based on Pancake graph. The proposed model is pragmatic and easy to
implement. Performance evaluations show that the results are globally
satisfactory, especially in term of cost lookup with high churn rate.
3 - Construction and Analysis of a Mathematical Model
for Data Buffering in Peer-to-Peer Based Streaming
Networks
Yuliya Gaidamaka, Andrey Samuylov, Konstantin
Samouylov, Sergey Shorgin
The detailed mechanism of data exchange between peers in streaming
P2P-network is investigated, the network performance measures and
quality of service (QoS) parameters are determined. A mathematical
model for buffering streaming data in P2P-network is built as a Markov
chain. The model takes into account buffer sizes, peers churn, playback lags, up- and download rates, collisions, and downloading strategy. The main network performance parameters are latency, startup
delay, playback continuity, and universal streaming. The results of calculation of main QoS parameters are given.
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Friday, 10:30-12:00 - Room 014
Forecasting Methods
Stream: Forecasting Methods
Contributed session
Chair: Chris Tofallis
1 - A Complexity Improvement Strategy for the Mycielski
Binary Forecasting Algorithm for Fast and Efficient
Prediction
Omer Nezih Gerek, Mehmet Fidan
Mycielski algorithm is a strong binary forecasting method that depends on infinite-past observations. It traces the whole series for the
longest suffix word that appears at the tail of the sequence. The repeated past search makes the algorithm complexity non-polynomial.
By slightly increasing memory demands, we propose an improvement
of the search using a dictionary-based approach. Eventually, the process speeds up to a polynomial order. Due to the similarity of the
improvement to the famous LZ-78 method over the non-polynomial
LZ-77, we call the new method the Mycielski-78 method.
2 - On a Time Series Forcasting Method based on Walsh
Transform
Erik Bajalinov, Szabolcs Duleba
Many real-world time series exhibit strong seasonal behavior and may
be successfully forecasted using Holt-Winters exponential smoothing
methods. Our recent research connected with the Walsh functions
shows that sometimes when analyzing time series the so called Walsh
transform can lead to very accurate predictions. In our talk we discuss
this unique approach, demonstrate some real-world numerical examples with highly accurate results and compare obtained results.
3 - Why MAPE Should not be used to Compare Forecasting Methods
Chris Tofallis
Surveys show the mean absolute percentage error is the most widely
used measure of forecast accuracy in businesses. Yet it systematically favours methods which under-forecast. We explain this effect.
We investigate an alternative relative error metric, based on the forecast/actual ratio, which overcomes this problem. We illustrate its use in
estimating the prediction model and show that this has a multiplicative
error. It predicts the geometric mean and so is less affected by outliers,
and possesses a suitable form of unbiasedness for relative accuracy.
This measure seems preferable to MAPE.
4 - A Forecasting Method for Non-Stationary Spare
Parts Demand
Laura Turrini, Joern Meissner
Contextual events can strongly influence demand for spare parts: a
very hot summer, for example, may increase the demand of delicate
parts, while cancellation of a maintenance contract will reduce it drastically. Depending on so many contextual factors, demand fluctuates in
size, and misses out the stationarity assumed in classic models. We develop a forecasting method that deals with non-stationarity of demand:
it uses Hidden Markov Chains to model the demand generation process
and estimates its parameters through history. We apply our method to
distinct datasets to prove its practical use.
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Friday, 10:30-12:00 - Room 016
Knowledge Work and Workers
Stream: Knowledge in Organizations
Invited session
Chair: A. D. Amar
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IFORS 2014 - Barcelona
1 - A Knowledge and Capability Based View on
Performance-Based Contracting in Defence Acquisition
Thomas Ekstrom, Kostas Selviaridis
The Swedish Defence Procurement Agency (DPA) is in the process
of changing from procurement of equipment to acquisition of performance, and from procurement through competition to acquisition
through, e.g., partnering. In addition, the Swedish Armed Forces and
the DPA are transferring resources, roles and responsibilities, between
them, in order to enhance overall effectiveness and efficiency. Based
on a knowledge and capability based view, this paper reports on research that has been initiated in order to investigate how knowledge
and capability is developed and maintained in this context.
2 - Innovation vs. Efficiency in the Supply Chain
Ajay Das
One source of competitive advantage is innovation. Another is process efficiencies. But process efficiency focuses on variance reduction
and even flows. Innovation needs variance and experimentation. Is the
pursuit of process efficiency then incompatible with the pursuit of innovation? And, specifically, considering the increasing size of external
value-partitioning, does this incompatibility extend to supply chains as
well? We theorize and examine the issue.
FB-35
Friday, 10:30-12:00 - Room 131
Stochastic Modeling and Simulation with
Applications
Stream: Stochastic Modeling and Simulation in Engineering, Management and Science
Contributed session
Chair: Gennadiy Burlak
1 - Utilizing a Trend-Renewal Framework for Estimating
Repair Effects in Failing Systems
Ernie Love, Qingyu Yang
A failing system experiences multiple failure modes each of which
causes system shutdown with subsequent repair and restart. A trendrenewal framework is utilized to capture the repair effects for each
mode of failures/repair. Data was collected on a cement kiln incurring 150 failures and 5 shutdowns for overhaul. Causes of failure were
identified as operational, mechanical or electrical. A trend-renewal
framework is seen to usefully capture the (expected) improved failure rate by virtue of the repairs. Comparisons with Kijima virtual age
frameworks are made.
2 - A Stochastic Optimization for Chemical Separation
Problems
Fattaneh Cauley
This research presents a non-convex mathematical programming
model of chemical separation problems. The model is based on algebraic relationships of the Standing Wave Design (SWD) equations,
where by solving these equations the desired product purity and yield
for many systems is guaranteed. The model can easily be modified
for simultaneous optimization of a large number of variables. Pairing
the model with two stochastic optimization algorithms, Simulated Annealing, and Genetic Algorithm, produces efficient tools for solving
multi-objective optimization problems of SMB systems.
3 - Object-Oriented Approach at Optimization of Interacting Quasi-Similar Objects in Optical Simulations
Gennadiy Burlak
Study the properties of a complex system with interaction of many
subsystems is interpreted as interaction of collection of quasi-similar
objects. We apply this approach to study behavior of the photon spectrum in microspheres with many quasiperiodic layers. We considered a
layer as a separate object having internal complex structure with fields,
methods reflecting the specific behaviour. Our simulations have detected that the quasiperiodicity parameter of such objects can exceed
the golden mean value. Then in such structure the extremely narrow
resonances with complete transmittance arise.
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Friday, 10:30-12:00 - Room 132
Healthcare Management
Stream: Healthcare Management
Invited session
Chair: Subhash Datta
Chair: Gerhard-Wilhelm Weber
1 - Optimal Resource Allocation for Effective Health
Care Delivery in Niger Delta Region of Nigeria - an
Invariant Property Based Algorithm Approach
Idorenyin Etukudo
Operators of health care delivery system in Niger Delta region of Nigeria are confronted with challenges of optimal resource allocation to
meet the objectives of the funding agencies. As a way out, a model
is hereby developed and a numerical illustration presented through an
invariant property based algorithm gives optimal resource allocation to
meet these objectives.
2 - Selecting Basic Insurance Organizations’ covered
Medications in Iran
Arash Aliakbari, Seyedeh Hoda Shajari, hamid pourasghari,
mohammadreza mehregan, Fatemeh Boloori, Farnaz
Hooshmand Khaligh, Jamaleddin Kedmati
Basic insurance organizations in Iran are faced with lots of challenges,
specifically in allocating resources efficiently. One of these challenges
is in healthcare system where they should help people to pay for medications and healthcare services. This paper presents a mathematical
approach to determine the basic insurance medications as efficient as
possible in order to achieve equity. Using UTADIS method and a Goal
Programming Model, we develop a Decision Support System to decide
which medications should be covered as well as insurer’s contribution
for selected ones.
3 - HIV Diagnostic Service Delivery in South Africa: Scenario Analysis using a Multi-Objective Version of the
Uncapacitated Fixed-Charge Location Model
Louzanne Oosthuizen, Johannes Gerhardus Benade, James
Bekker
The commercial availability of a new, point-of-care device for HIV
diagnostic testing has prompted a need to re-evaluate the delivery of
diagnostic services in the South African public healthcare sector. The
basic structure of the uncapacitated fixed-charge location model is expanded in this work to a multi-objective model and adapted to take location costs, operating costs, transport distances, service delivery levels and health impact into consideration in order to evaluate alternative
scenarios for incorporating this testing device into the South African
laboratory and hospital network.
4 - Models for Preventing and Treating Malaria in
Resource-Constrained Regions
Susan Martonosi
Malaria is endemic throughout Africa and other regions of the world.
While interventions exist to prevent malaria or reduce its consequences, resources for distributing these interventions in developing areas are limited. I will present an optimization framework for
choosing cost-effective allocations of interventions across several geographic regions and multiple time periods subject to budget constraints.
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Friday, 10:30-12:00 - Room 017
Managing Transshipments
Stream: Recovery Inventory Management Policies
Invited session
Chair: Jianjun Xu
252
IFORS 2014 - Barcelona
1 - Decision Models for Purchasing and Reselling of Unused Spaces in Less-than-truckload Trips
Manop Reodecha, Naragain Phumchusri, Wissanu Sammaung
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2 - Systemic and Systematic Risk in Stock Returns
Roberto Panzica, Monica Billio, Massimiliano Caporin,
Loriana Pelizzon
This extended multi-period newsboy decision model is to maximize
the expected profit of a low-cost third-party logistics service provider
(LSP) who purchases unused spaces in truck trips from other LSPs to
service its customers. It helps to find an optimal target space to purchase for each route in a specific period and helps to decide to accept or
reject each customer’s service request. Trip offers and requests come
gradually in periods prior to the actual trips with known probability
distributions in each period. A truck trip allows multiple delivery and
pick-up points and transshipments.
The understanding of propagation mechanisms behind recent financial crises leads the increased interest in systemic risk and networkbased methods have been used to infer from data connections among
institutions (or companies). In this work, we elaborate the link between systemic and systematic risk and introduce a modeling framework where the two risks co-exist. The model is a variation of the
traditional CAPM where networks are used to infer links across assets
and the systemic risk component acts in an additive way on both the
systematic and idiosyncratic risk components.
2 - Production and Transshipment Management of Two
Manufacturing Facilities: Dynamics, Efficient Optimal Policy and Characteristics
Jianjun Xu, Youyi Feng
3 - Carrying the (Paper) Burden: A Portfolio View of Systemic Risk and Optimal Bank Size
Jaap Bos, Martien Lamers, Victoria Purice
We study the optimal inventory and transshipment policy of a finite
horizon, periodic review inventory system of two manufacturing facilities that replenishes the same product to fulfill stochastic demands. In
each period the system plans to produce at both facilities and the production will be completed at the end of the period. After demands are
realized, the leftover inventory of any facility can be transferred into
the other facility. We show that the dynamics of optimal production
and transshipment decisions in both facilities are specified by monotone switching curves.
We examine the relationship between bank size and financial stability
by viewing the supervisor of a banking system as an ’investor’ holding
a portfolio of banks. Based on this view, we investigate the role of large
banks in determining the systemic risk in this portfolio. Using data on
US banks and bank holding companies, our results indicate that the
largest banks in the current portfolio are consistently overrepresented
compared to the minimum variance portfolio, and that the riskiness
of the portfolio can be reduced without sacrificing returns by limiting
concentration.
3 - Multi-Refinery Product Transportation Optimization
Eren Cicek, Metin Turkay
Petroleum refining is a low-margin and very competitive industry.
Thus for the multiple refinery operating companies, inter-refinery
transportation of semi-products are vital for maximum utilization. The
paper discusses the reciprocal transportation network between two refineries in Turkey, small one near the drilling site and complex one
for meeting required product specifications. Transportation modes are
railroad tankers, road haulage and blending the products into crude oil
pipeline. The challenge is to minimize the overall transportation cost
under fluctuating costs and demands.
4 - Approximate Dynamic Programming for Lateral
Transshipment Problems in Multi-Location Inventory
Systems
Olga Rusyaeva, Joern Meissner
To fix the mismatch between actual customer demand and the available stock in multiple locations under the inability to replenish from
a central warehouse, companies often turn to lateral transshipments.
We propose a proactive transshipment policy that answers the question from which source to which destination how many units should be
transshipped in advance to maximize the revenue of the network. For
high-dimensional instances, we develop a heuristic that constructs a
concave piecewise-linear approximation and updates it using stochastic sample gradients.
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Friday, 10:30-12:00 - Room 214
Assessing Systemic Risk
Stream: Operational Research and Quantitative Models in Banking
Invited session
Chair: Raffaella Calabrese
1 - Modelling the Probability of Government Measures
and Failures During the 2008-2012 through the GEV
Model
Marta Degl’Innocenti, Raffaella Calabrese
After the autumn of 2008, the Euro-system and USA adopted a series
of extensive measures to ensure financial and economic stability. Focusing on the US and EU banking industry, we employ the generalized
extreme value regression (GEV) model proposed by Calabrese and Osmetti (2013) to estimate the probability of receiving ad hoc government
interventions, namely recapitalization, debt guarantees and asset relief
over the period 2008-2012. These estimates are then compared with
the probability of bank failures.
4 - Modelling Cross-Border Bank Contagion using
Marshall-Olkin Copula
Raffaella Calabrese, Silvia Osmetti
In this paper, we propose a new copula based methodology for modelling cross-border bank contagion. In this work we use copulae to
model the dependence structure of times to defaults for banks located in two different countries. We suggest to apply the MarshallOlkin(MO) copula for modelling bank contagion. The second innovative aspect of this work is to consider a Type I censored sampling.
The sample information of non-defaulted banks can be so used to estimate the bank contagion. Finally, we apply the proposed approach to
analyse the contagion between the Italian and British banking systems.
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Friday, 10:30-12:00 - Room 018
Discrete Optimization III
Stream: Discrete and Global Optimization
Contributed session
Chair: Tonguc Ünlüyurt
1 - Multi-Start Local Search Heuristic for the Cell Formation Problem
Mikhail Batsyn, Ilya Bychkov, Panos Pardalos, Pavel Sukhov
In this talk we present a local search heuristic for the cell formation
problem. This problem consists in clustering of machines and parts
into production cells such that the inter-cell movement of parts is minimized and the intra-cell movement is maximized. The local search
procedure is repeated many times for randomly generated cell configurations. We improve a random solution moving one machine or part
from one cell to another until the objective increases. Our experiments
are performed for popular instances from the literature. Better solutions unknown before are found for several of them.
2 - Sequential Testing with Fixed Costs in Batches
Tonguc Ünlüyurt, Baris Selcuk, Ozgur Ozluk
Sequential Testing problem requires the identification of the correct
state of a system when learning the states of the individual components of the system is costly. The goal is to minimize expected cost
when probability of the state of each component is known. In this
work, we consider an extension of the problem where multiple tests
can be executed simulataneously. In this case the advantage would be
to incur the fixed cost only once. In this work, we consider a series
system where a given set of subsets of tests can be performed together.
We report some initial computational results.
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IFORS 2014 - Barcelona
3 - Adaptivity in the Stochastic Blackjack Knapsack
Problem
Aleksander Vainer, Asaf Levin
We bound the improvement of a policy due to adaptivity in a variant
of the stochastic knapsack where the values are deterministic and the
sizes have independent random distributions. In our problem items are
chosen sequentially. The act of choosing an item instantiates its size.
If the final subset is feasible, its value equals the sum of values of its
items. Otherwise its value is zero. The goal is to find a policy maximizing its expected value. We study the adaptivity gap for this problem
and other variants (or special cases).
4 - Canonical Duality Method for the Design of FIR Filters with Signed-Powers-of-Two Coefficients
Ning Ruan
We consider the optimal design of finite impulse response filters (FIR)
with sums of signed-powers-of-two coefficients, which is based on the
weighed integral square error criterion. This problem is formulated
as a constrained integer programming problem. We construct the corresponding canonical dual problem through canonical duality theory.
Then the analytic solution is obtained by criticality condition. It is
noted that the dual problem over a positive definite space is a concave
maximization problem over a convex set, and hence can be solved efficiently by existing optimization techniques.
FB-40
Friday, 10:30-12:00 - Room 019
Quantitative Models for Performance and
Dependability II
Stream: Quantitative Models for Performance and Dependability
Invited session
Chair: Sabri Erdem
1 - Linking Voice of Industry (Recruiters) with BSchools’ Service Operations using Q Sort Technique
through Quality Function Deployment
Jitendra Sharma, Tinu Agrawal
Customer needs are the most important input for designing of any
product or service in today’s scenario. In this context, B-Schools have
to be one-step ahead of the industries’ expectations and meeting these
expectations requires the expectations be understood. In this paper,
authors have attempted to link Voice of Industry-Recruiters to business education process using Q-Sort technique in QFD for complete
industry satisfaction. The paper discusses the collection of industries’
voice and their development into structured, evaluated and quantified
requirements through Q-sort technique.
2 - Local-Scale Maximum Daily Ozone Prediction by using Artificial Intelligence Techniques
Bing Gong, Joaquin Ordieres-Mere
Ozone (O3) is one of the worst harmful pollutants nowadays which affects public health, damage the crop growing then lead to serious economic loss. In this study, some state-of-art artificial intelligence (AI)
techniques such as Neural Network, Support Vector Machine, Random
Forest and Ensemble methods will be used for predicting ozone level
locally at different stations in the Valley Metropolitan Area of Mexico
area which is considered as one of the biggest cities worldwide. Besides, integrate local-scale prediction models at different stations into
a regional-scale model will be considered.
3 - A Bagging-Based Undersampling Strategy for Classification: A Customer Churn Prediction Application
Kristof Coussement, Geert Verstraeten
Several researchers have investigated how to overcome rare events in
classification settings through undersampling. This research study uses
real-life churn datasets to deliver insights into the merits and drawbacks of undersampling. This setting is an ideal test bed given that
customer churn is often considered a rare event in multiple industries,
while the classification context could largely benefit from undersampling given the large datasets. The authors propose a new baggingbased undersampling strategy that delivers promising performance results against existing methods.
254
4 - Assessing Entrepreneurial Potential of Individuals
using Principal Component Analysis
Sabri Erdem, Nilay Bıçakcıoğlu, Mehmet Çağlıyangil
Entrepreneurship has taken considerable attention since it plays a vital
role in contributing to the economy of a country. This paper studies entrepreneurship by collecting all the characteristics reviewed from
the literature and develops an entrepreneurial scale to measure whether
people have an entrepreneurial spirit. Our methodology is followed by
expert opinions, questionnaire design and principal component analysis (PCA). The results show that PCA can be applied to measure entrepreneurship ability and guide following studies by providing a comparison tool for entrepreneurship ability.
FB-41
Friday, 10:30-12:00 - Room 216
Network Congestion Models
Stream: Traffic Equilibrium
Invited session
Chair: Patrice Marcotte
Chair: Niccolo’ Bulgarini
1 - Novel Formulations for Stackelberg Security Games
Carlos Casorrán-Amilburu, Martine Labbé, Bernard Fortz,
Fernando Ordonez
We present new tight formulations for the Single-type-of-Follower
Stackelberg Game and for the Single-type-of-Attacker Stackelberg Security Game, improving the current formulations present in the literature. We show that both formulations provide a complete linear description of the convex hull of the sets of feasible solutions of the corresponding problems and show that one formulation is the projection
of the other on the appropriate space. The formulations presented for
the Bayesian case improve the continuous relaxations of existing formulations. Computational experiments are carried out.
2 - Derivative-Free Algorithms for the Estimation of Dynamic Demand Structure using Traffic Counts
Bojan Kostic, Daniele Tiddi, Guido Gentile
As travel demand is an essential input to the Dynamic Traffic Assignment (DTA) model, it is crucial to have correct Origin-Destination (OD) matrices. In this paper we compare different derivative-free algorithms for the demand estimation, focusing on the structure of the matrices instead on the single entries. This is a non-linear bi-level problem as it involves congestion dynamics and user equilibrium. Three
algorithms (SPSA, Nelder-Mead, CMA-ES) will be applied in different traffic regimes to investigate their ability of converging to a known
solution, after perturbing the initial demand.
3 - A Convergent and Efficient Decomposition Method
for the Symmetric Traffic Assignment Problem
Marco Sciandrone, David Di Lorenzo
We consider the symmetric network equilibrium problem, formulated
as a convex minimization problem whose variables represent the path
flows. In order to take into account the difficulties related to the large
dimension of real network problems we adopt a decomposition-based
approach, suitably combined with a column generation strategy. We
present an inexact block-coordinate descent method with proven global
convergence. Computational experiments performed on medium-large
dimensional problems show that the proposed algorithm is competitive
with state of the art methods.
IFORS 2014 - Barcelona
4 - Decomposition Methods for One-Level Formulations
of the Origin-Destination Estimation Problem
Niccolo’ Bulgarini, David Di Lorenzo, Fabio Schoen, Marco
Sciandrone
The most general formulation of the Origin-Destination (OD) estimation problem is a bilevel programming model based on observations
from a link subset and on historical OD information. We consider onelevel convex optimization problems, as relaxed OD estimation formulations, and propose convergent decomposition algorithms for largescale problems. The proposed algorithms take into account that onelevel formulations can be viewed as static traffic assignment problems
with elastic demand, where negative cycles may be present in the network. Computational results are presented and discussed.
FB-43
Multiple-attribute selection decisions require gathering information using observations that can provide data about only one of the attributes
at a time. When resources are scarce, the decision-maker must choose
which attributes to observe (sample) in a way that maximizes the likelihood that the correct alternative will be selected. This talk will describe
sample allocation policies for multiple-attribute selection decisions
with attribute values estimated through pass-fail testing (Bernoulli trials) and those estimated by techniques that are subject to normally distributed measurement error.
FB-43
Friday, 10:30-12:00 - Room 217
FB-42
Friday, 10:30-12:00 - Room 215
Qualitative Multiple-Criteria Decision
Making II
Stream: Qualitative Multiple Criteria Decision Making
Invited session
Chair: Marko Bohanec
Chair: Vladislav Rajkovič
1 - Numerical Relational Multi-Attribute Models in Qualitative Multi-Attribute Method DEX
Nejc Trdin, Marko Bohanec
DEX is a qualitative decision support method aimed at evaluation and
analysis of decision alternatives. Many real decision problems are
based on relational properties between at least two types of entities,
and require a combination of numeric and symbolic attributes. For
example, evaluation of bank’s reputational risk has relations between
banks, bank’s counterparts and clients, and financial products. In this
work we address the task of extending DEX to facilitate evaluation of
relationally connected decision alternatives, described with a combination of numeric and symbolic attributes.
2 - Multi-Attribute Model for Assessment of SMEs Adoption of High Performance Computing Cloud Services
Mirjana Kljajic Borstnar, Tomi Ilijas, Andreja Pucihar
High Performance Computing offered as a cloud service is regarded as
one of the key competitiveness boosters for SMEs, particularly manufacturing. However, business models are not yet explored, and technology adoptance is in its early stages. In order to explore and support
new business ideas there is need for assessment of the SMEs readiness
and market viability. Based on theory and practice we are proposing
a qualitative multi-attribute model for SMEs’ cloud HPC adoption assessment. The model will be verified on a set of experiments conducted
within several EU projects in I4MS initiative.
Risk Management and Performance
Analysis
Stream: Operational Research and Quantitative Models in Banking
Contributed session
Chair: Stavros A. Zenios
Chair: Carlo Lucheroni
Chair: Jake Ansell
1 - Lending Decisions with Limits on Capital Available
Lyn Thomas, Mee Chi So
In order to stimulate or subdue the economy, banking regulators have
sought to impose caps or floors on individual bank’s lending to certain
types of borrowers. This work shows that the resultant decision problem for a bank of which potential borrower to accept is a variant of the
marriage/secretary problem where one can accept several applicants.
This work solves the decision problem using dynamic programming.
By solving numerical examples we show the potential loss of profit and
the inconsistency in the lending decision that are caused by introducing
floors and caps on lending.
2 - Feasible Algorithms for Lattice and Directed Subspaces
Piotr Wojciechowski, Vladik Kreinovich, Jennifer Del Valle
In some practical situations it is important to check whether a given
linear subspace of a vector-lattice is a lattice. In financial applications, it was proven by Abramovich et al. (J. of Economic Dynamics &
Control 2000) that the existence of appropriate minimum-cost insured
portfolios is equivalent to the fact that the linear space generated by the
corresponding financial instruments is lattice-ordered. In the talk we
present feasible, polynomial-time, algorithms for solving the problem.
Some generalizations and future applications will be discussed.
3 - Business Intelligence System Complexity, and Approaches to Understand the User Segments in Business Intelligence Systems and Adapt Data Cubes to
User Needs
Violeta Mirchevska, Igor Korelič, Matjaz Gams, Franc
Škedelj, Mirjana Kljajic Borstnar, Vladislav Rajkovic
Business intelligence (BI) systems offer wide variety of functionalities
for data retrieval, analysis and visualization, improving the quality of
business decision-making. Still, the usage analyses reveal rather low
BI adoption. In this contribution, we discuss the complexity of BI
systems and approaches to make them user- and context-specific. We
analyse results of a case study for determining different types of BI
users from system-user interaction traces using clustering, and adaptation of data cubes to user needs by using multiple criteria decision
analysis.
4 - Information Gathering for Multiple-Attribute Selection Decisions
Dennis Leber, Jeffrey Herrmann
255
FC-50
IFORS 2014 - Barcelona
Friday, 12:15-13:45
Friday, 14:00-15:30
FC-50
FD-50
Plenary Session K. Smith-Miles
Closing Ceremony
Stream: Plenary Sessions
Keynote session
Stream: Plenary Sessions
Invited session
Friday, 12:15-13:45 - Plenaries room
Chair: Stefan Nickel
1 - Understanding Strengths and Weaknesses of Optimization Algorithms with new Visualization Tools
and Methodologies
Kate Smith-Miles
Objective assessment of optimization algorithm performance is notoriously difficult, with conclusions often inadvertently biased towards the
chosen test instances. Rather than reporting average performance of
algorithms across a set of chosen instances, we discuss a new methodology to enable the strengths and weaknesses of different optimization
algorithms to be compared across a broader instance space. Results
will be presented on TSP, timetabling and graph coloring to demonstrate: (i) how pockets of the instance space can be found where algorithm performance varies significantly from the average performance
of an algorithm; (ii) how the properties of the instances can be used
to predict algorithm performance on previously unseen instances with
high accuracy; (iii) how the relative strengths and weaknesses of each
algorithm can be visualized and measured objectively; and (iv) how
new test instances can be generated to fill the instance space and provide desired insights into algorithmic power.
256
Friday, 14:00-15:30 - Plenaries room
S TREAMS
Actuarial Sciences and
Stochastic Calculus
Applications of Dynamical
Models
Business Analytics
Optimization and Big Data
Ricardo Josa-Fombellida
Universidad de Valladolid
ricar@eio.uva.es
Alberto Pinto
University of Porto
aapinto1@gmail.com
Track(s): 30
Ali Emrouznejad
Aston University
a.emrouznejad@aston.ac.uk
Juan Pablo Rincon-Zapatero
Universidad Carlos III de Madrid
jrincon@eco.uc3m.es
Track(s): 24
AHP (Analytic Hierarchy
Process) /ANP (Analytical
Network Process)
Chi-Cheng Huang
Aletheia University
j1225a@ms7.hinet.net
Track(s): 37
Applications of Heuristics
Geir Hasle
Sintef Ict
geir.hasle@sintef.no
Track(s): 25
Auctions
Karla Hoffman
George Mason University
khoffman@gmu.edu
Track(s): 41
Algorithmic Game Theory
Ron Lavi
Technion
ronlavi@ie.technion.ac.il
Track(s): 22
Algorithms and Computational
Optimization
Basak Akteke-Ozturk
Middle East Technical University
bozturk@metu.edu.tr
Aviation
Douglas Fearing
The University of Texas at Austin
doug.fearing@mccombs.utexas.edu
Vikrant Vaze
Thayer School of Engineering,
Dartmouth
vikrant.s.vaze@dartmouth.edu
Track(s): 3
Haldun Sural
Middle east technical university
hsural@metu.edu.tr
Track(s): 43
Behavioural Operational
Research
Allocation Problems in Game
Theory
Raimo P. Hämäläinen
Aalto University ,School fo Science
raimo.hamalainen@aalto.fi
Track(s): 23
Sirma Zeynep Alparslan Gok
Faculty of Arts and Sciences,
Suleyman Demirel University
zeynepalparslan@yahoo.com
L. Alberto Franco
Loughborough University
L.A.Franco@lboro.ac.uk
Big Data Analytics
Mariana Rodica Branzei
"Alexandru Ioan Cuza” University
branzeir@info.uaic.ro
Track(s): 30
Seoung Bum Kim
Korea University
sbkim1@korea.ac.kr
Track(s): 42
Analytics Application and
Practice
Biomass-Based Supply Chains
Don Kleinmuntz
Kleinmuntz Associates
don@kleinmuntzassociates.com
Track(s): 23
Magnus Fröhling
Karlsruhe Institute of Technology
(KIT)
magnus.froehling@kit.edu
Taraneh Sowlati
University of British Columbia
taraneh.sowlati@ubc.ca
Track(s): 38
Diego Klabjan
Northwestern University
d-klabjan@northwestern.edu
Track(s): 45
Challenge ROADEF/EURO
Eric Bourreau
LIRMM
eric.bourreau@lirmm.fr
Track(s): 28
City Logistics and Freight
Demand Modeling
Jose Holguin-Veras
Rensselaer Polytechnic Institute
jhv@rpi.edu
Track(s): 6
Combinatorial Optimization
Silvano Martello
University of Bologna
silvano.martello@unibo.it
Paolo Toth
University of Bologna
paolo.toth@unibo.it
Track(s): 2 11
Computational Statistics
Pakize Taylan
Dicle University
pakizetaylan@yahoo.com
Gerhard-Wilhelm Weber
Middle East Technical University
gweber@metu.edu.tr
Track(s): 43
Continuous and Discontinuous
Dynamical Systems
Ozan Özkan
Selçuk University
oozkan@selcuk.edu.tr
Mevlüde Yakıt Ongun
Süleyman Demirel University
mevludeyakit@sdu.edu.tr
Track(s): 12
257
STREAMS
Convex Optimization Methods
and Applications
Amir Beck
Technion - Israel Institute of
Technology
becka@ie.technion.ac.il
Marc Teboulle
Tel Aviv University
teboulle@math.tau.ac.il
Track(s): 38
Copositive and Polynomial
Optimization
Immanuel Bomze
University of Vienna
immanuel.bomze@univie.ac.at
Daniel Plaumann
University of Konstanz
Daniel.Plaumann@uni-konstanz.de
Track(s): 16
Cutting and Packing
A. Miguel Gomes
INESC TEC, Faculdade de
Engenharia, Universidade do Porto
agomes@fe.up.pt
IFORS 2014 - Barcelona
DEA Applications
Decision Support Systems
Ana Camanho
Universidade do Porto
acamanho@fe.up.pt
Fatima Dargam
SimTech Simulation Technology
F.Dargam@SimTechnology.com
Meryem Duygun Fethi
University of Leicester
m.fethi@le.ac.uk
Track(s): 14
Boris Delibasic
University of Belgrade
boris.delibasic@fon.bg.ac.rs
Decision Analysis, Decision
Support Systems
Mikhail Kuznetsov
Moscow Institute of Physics and
Technology
mikhail.kuznecov@phystech.edu
Vadim Strijov
Russian Academy of Sciences,
Computing Center
strijov@ccas.ru
Track(s): 27
Decision Making Modeling and
Risk Assessment in the
Financial Sector
José Fernando Oliveira
University of Porto
jfo@fe.up.pt
Track(s): 21
Cristinca Fulga
Gheorghe Mihoc-Caius Iacob
Institute of Mathematical Statistics
and Applied Mathematics of
Romanian Academy
fulga@csie.ase.ro
Track(s): 34
Data Mining
Decision Processes
Dolores Romero Morales
University of Oxford
dolores.romeromorales@sbs.ox.ac.uk
Track(s): 25
Manel Baucells
Universitat Pompeu Fabra
manel.baucells@upf.edu
Data Mining in Finance and
Commodities
Marcus Hildmann
ETH Zurich
hildmann@eeh.ee.ethz.ch
Dejan Stokic
DataMain
sdeyan@gmail.com
Track(s): 34
Data Mining, Knowledge
Discovery and Artificial
Intelligence
Karla Hoffman
George Mason University
khoffman@gmu.edu
Track(s): 32
258
Jeffrey Keisler
University of Massachusetts Boston
jeff.keisler@umb.edu
Juuso Liesiö
Aalto University
juuso.liesio@aalto.fi
Alec Morton
University of Strathclyde
alec.morton@strath.ac.uk
Track(s): 31
Jorge E. Hernández
University of Liverpool
J.E.Hernandez@Liverpool.ac.uk
Isabelle Linden
University of Namur
isabelle.linden@unamur.be
Shaofeng Liu
University of Plymouth
shaofeng.liu@plymouth.ac.uk
Jason Papathanasiou
University of Macedonia
jason.papathanasiou@gmail.com
Pascale Zaraté
Toulouse University
zarate@irit.fr
Track(s): 42
Defence and Security
Applications
Ana Isabel Barros
TNO
ana.barros@tno.nl
Track(s): 33
Demand and Supply Planning in
Consumer Goods and Retailing
Rob Broekmeulen
TU Eindhoven
r.a.c.m.broekmeulen@tue.nl
Alexander Hübner
Catholic University
Eichstaett-Ingolstadt
alexander.huebner@ku-eichstaett.de
Heinrich Kuhn
Catholic University of
Eichstaett-Ingolstadt
heinrich.kuhn@ku-eichstaett.de
Winfried Steiner
Clausthal University of Technology,
Institute of Management and
Economics
winfried.steiner@tu-clausthal.de
Track(s): 19
IFORS 2014 - Barcelona
Discrete and Global
Optimization
Jan van Vuuren
Stellenbosch University
vuuren@sun.ac.za
Gerhard-Wilhelm Weber
Middle East Technical University
gweber@metu.edu.tr
Track(s): 39
Dynamic and Repeated Games
Rida Laraki
CNRS, Université Dauphine and
Ecole Polytechnique
rida.laraki@gmail.com
Track(s): 24 28
Dynamic Programming
Lidija Zadnik Stirn
University of Ljubljana
lidija.zadnik@bf.uni-lj.si
Track(s): 8
Dynamical Models in
Sustainable Development
Pierre Kunsch
Vrije Universiteit Brussel
pkunsch@vub.ac.be
Track(s): 7
Dynamical Systems and
Mathematical Modelling in OR
Katsunori Ano
Shibaura Institute of Technology
k-ano@shibaura-it.ac.jp
Selma Belen
CAG University
selmaalgumus@gmail.com
Gerhard-Wilhelm Weber
Middle East Technical University
gweber@metu.edu.tr
Track(s): 9
Educational Planning and
Development
Subhash Datta
Centre for Inclusive Growth and
Sustainable Development
subhash.datta@gmail.com
Gerhard-Wilhelm Weber
Middle East Technical University
gweber@metu.edu.tr
Track(s): 40
Energy Economics,
Environmental Management and
Multicriteria Decision Making
Wolf Fichtner
KIT
wolf.fichtner@wiwi.uni-karlsruhe.de
Peter Letmathe
RWTH Aachen University
Peter.Letmathe@rwth-aachen.de
Vadim Strijov
Russian Academy of Sciences,
Computing Center
strijov@ccas.ru
Track(s): 8
STREAMS
Financial Mathematics and OR
Katsunori Ano
Shibaura Institute of Technology
k-ano@shibaura-it.ac.jp
Sevtap Kestel
Applied Mathematics Institute
skestel@metu.edu.tr
Mustafa Pinar
Bilkent University
mustafap@bilkent.edu.tr
Gerhard-Wilhelm Weber
Middle East Technical University
gweber@metu.edu.tr
Track(s): 30
Environmental Sustainability in
Supply Chain
Financial Optimization
Werner Jammernegg
WU Vienna University of Economics
and Business
werner.jammernegg@wu.ac.at
Nan Chen
The Chinese University of Hong
Kong
nchen@se.cuhk.edu.hk
Tina Wakolbinger
WU (Vienna University of Economics
and Business)
tina.wakolbinger@wu.ac.at
Track(s): 33
Duan Li
The Chinese University of Hong
Kong
dli@se.cuhk.edu.hk
Equilibrium Problems in Energy
Steven Gabriel
University of Maryland
sgabriel@umd.edu
Track(s): 7
Experimental Perspectives and
Challenges in Management
Accounting and Management
Control
Stephan Leitner
Alpen-Adria-Universität Klagenfurt
stephan.leitner@aau.at
Alexandra Rausch
Dept. for Controlling and Strategic
Management
Alexandra.Rausch@aau.at
Track(s): 15
Fabio Tardella
Sapienza University of Rome
fabio.tardella@uniroma1.it
Track(s): 29
Forecasting Methods
Chris Tofallis
University of Hertfordshire
c.tofallis@herts.ac.uk
Track(s): 32
Fuzzy Decision Support
Systems, Soft Computing,
Neural Network
Heinrich Rommelfanger
J. W. Goethe University
rommel@wiwi.uni-frankfurt.de
Track(s): 26
Fuzzy Optimization - Systems,
Networks and Applications
Erik Kropat
Universität der Bundeswehr München
erik.kropat@unibw.de
Silja Meyer-Nieberg
Universität der Bundeswehr München
silja.meyer-nieberg@unibw.de
Track(s): 7
259
STREAMS
IFORS 2014 - Barcelona
Game Theory
Health Care Applications
Miquel Oliu Barton
Université de Neuchâtel
oliubart@gmail.com
Track(s): 44
Sally Brailsford
University of Southampton
s.c.brailsford@soton.ac.uk
Track(s): 39
Game Theory and Operations
Management
Health Care Data Analytics
Greys Sosic
University of Southern California
sosic@marshall.usc.edu
Moshe Haviv
Hebrew University of Jerusalem
haviv@mscc.huji.ac.il
Track(s): 22
Geometric Clustering
Steffen Borgwardt
Technische Universität München
borgwardt@ma.tum.de
Andreas Brieden
Universität der Bundeswehr München
andreas.brieden@unibw.de
Peter Gritzmann
TU München
gritzman@ma.tum.de
Track(s): 45
Global Optimization
Herman Mawengkang
The University of Sumatera Utara
mawengkang@usu.ac.id
Gerhard-Wilhelm Weber
Middle East Technical University
gweber@metu.edu.tr
Nancy Clarke
Acadia University
nancy.clarke@acadiau.ca
Track(s): 17
Graphs and Networks
Dominique de Werra
EPFL
dominique.dewerra@epfl.ch
Track(s): 12
Green and Humanitarian
Logistics
Tolga Bektas
School of Management
T.Bektas@soton.ac.uk
Track(s): 42
260
Kwok Leung Tsui
City University of Hong Kong
kltsui@cityu.edu.hk
Track(s): 22
Healthcare Management
Subhash Datta
Centre for Inclusive Growth and
Sustainable Development
subhash.datta@gmail.com
Gerhard-Wilhelm Weber
Middle East Technical University
gweber@metu.edu.tr
Track(s): 36
Humanitarian Operations
Research
Erik Kropat
Universität der Bundeswehr München
erik.kropat@unibw.de
Silja Meyer-Nieberg
Universität der Bundeswehr München
silja.meyer-nieberg@unibw.de
Gerhard-Wilhelm Weber
Middle East Technical University
gweber@metu.edu.tr
Track(s): 32
Hybrid Heuristics
Saïd Hanafi
University of Valenciennes
said.hanafi@univ-valenciennes.fr
Said Salhi
University of Kent
s.salhi@kent.ac.uk
Track(s): 45
Hyperheuristics
Andrew J. Parkes
University of Nottingham
ajp@cs.nott.ac.uk
Track(s): 33
IFORS Prize for OR in
Development 2014
Elise del Rosario
OSSFFI
elise@jgdelrosario.com
Sue Merchant
Blue Link Consulting
suemerchant@hotmail.com
Andrés Weintraub
University of Chile
aweintra@dii.uchile.cl
Track(s): 20
Infrastructure Development and
Environment
Subhash Datta
Centre for Inclusive Growth and
Sustainable Development
subhash.datta@gmail.com
Gerhard-Wilhelm Weber
Middle East Technical University
gweber@metu.edu.tr
Track(s): 27
Initiatives for OR Education
Olga Nazarenko
National Technical University of
Ukraine "Kyiv Polytechnic Institute"
olga.nazarenko@ukr.net
Gerhard-Wilhelm Weber
Middle East Technical University
gweber@metu.edu.tr
Track(s): 44
Intelligent Optimization in
Machine Learning and Data
Analysis
Nikita Ivkin
Moscow Institute of Physics and
Technology (State University)
ivkinnikita@gmail.com
Anton Khritankov
MIPT
anton.khritankov@acm.org
Anastasia Motrenko
Moscow Institute of Physics and
Technology
pastt.petrovna@gmail.com
Ivan Reyer
Dorodnicyn Computing Centre of
RAS
reyer@forecsys.ru
Track(s): 16
IFORS 2014 - Barcelona
Interior Point Methods and
Conic Optimization
Jordi Castro
Universitat Politecnica de Catalunya
jordi.castro@upc.edu
Tamás Terlaky
Lehigh University
terlaky@lehigh.edu
Track(s): 17
International Aspects of OR:
Cooperation — Coordination —
Communication
Jakob Krarup
University of Copenhagen
krarup@diku.dk
Graham Rand
Lancaster University
g.rand@lancaster.ac.uk
Ulrike Reisach
Neu-Ulm University of Applied
Sciences
ulrike.reisach@hs-neu-ulm.de
Gerhard-Wilhelm Weber
Middle East Technical University
gweber@metu.edu.tr
Track(s): 28 45
Knowledge in Organizations
A. D. Amar
Seton Hall University
amaramar@shu.edu
Track(s): 34
Location
Sibel A. Alumur
TOBB University of Economics and
Technology
salumur@etu.edu.tr
Ioannis Giannikos
University of Patras
I.Giannikos@upatras.gr
STREAMS
Lot-Sizing and Related Topics
Metaheuristics
Bernardo Almada-Lobo
Faculty of Engineering of Porto
University
almada.lobo@fe.up.pt
Kenneth Sörensen
University of Antwerp
kenneth.sorensen@uantwerpen.be
Track(s): 23
Christian Almeder
European University Viadrina
Almeder@europa-uni.de
Methodology of Societal
Complexity
Alistair Clark
University of the West of England
Alistair.Clark@uwe.ac.uk
Track(s): 41
Managing Risk in Supply
Chains
Kumar Sanjay
Penn State University- Erie
sxk89@psu.edu
Track(s): 44
Maritime Transportation
Henrik Andersson
Norwegian University of Science and
Technology
Henrik.Andersson@iot.ntnu.no
Kjetil Fagerholt
Norwegian University of Science and
Technology
kjetil.fagerholt@iot.ntnu.no
Track(s): 5
Mathematical Economics
Alexander Zaslavski
Technion
ajzasl@techunix.technion.ac.il
Track(s): 25
Matheuristics
Richard Hartl
University of Vienna
richard.hartl@univie.ac.at
Track(s): 6
Dorien DeTombe
Chair Euro Working Group
detombe@nosmo.nl
Track(s): 29
Mixed-Integer Nonlinear
Programming
Armin Fügenschuh
Helmut Schmidt University
fuegenschuh@hsu-hh.de
Track(s): 28
Multiobjective Linear, Integer,
and Combinatorial Optimisation
Matthias Ehrgott
Lancaster University
m.ehrgott@lancaster.ac.uk
Track(s): 44
Multiobjective Optimization
Emilio Carrizosa
Universidad de Sevilla
ecarrizosa@us.es
Track(s): 37
Multiobjective Optimization Theory, Methods and
Applications
Jussi Hakanen
University of Jyvaskyla
jussi.hakanen@jyu.fi
Markus Hartikainen
University of Jyväskylä
markus.e.hartikainen@jyu.fi
Kaisa Miettinen
University of Jyväskyla
kaisa.miettinen@jyu.fi
Track(s): 18 19
Mercedes Landete
University Miguel Hernández of
Elche
landete@umh.es
Track(s): 3
Meta-Analytics: A Marriage of
Metaheuristics and Analytics
Logistics in Health Care
Gary Kochenberger
University of Colorado Boulder
gary.kochenberger@ucdenver.edu
Jose Luis Gonzalez-Velarde
Monterrey Tech
gonzalez.velarde@itesm.mx
Manuel Laguna
University of Colorado at Boulder
laguna@colorado.edu
Track(s): 40
Gerhard-Wilhelm Weber
Middle East Technical University
gweber@metu.edu.tr
Track(s): 29
Vedat Verter
McGill University
Vedat.Verter@mcgill.ca
Track(s): 6
Fred Glover
University of Colorado
fredwglover@yahoo.com
Multiple Criteria Decision
Making and Optimization
261
STREAMS
IFORS 2014 - Barcelona
Nonlinear Programming
Optimal Control
Goran Lesaja
Georgia Southern University
goran@georgiasouthern.edu
Ekaterina Kostina
University of Marburg
kostina@mathematik.uni-marburg.de
Florian Potra
University of Maryland
potra@umbc.edu
Track(s): 14
Gernot Tragler
Vienna University of Technology
tragler@eos.tuwien.ac.at
Track(s): 7
Nonsmooth Optimization and
Variational Analysis
Optimisation in Health Care
Antonio Frangioni
Universita’ di Pisa
frangio@di.unipi.it
Track(s): 26
Janny Leung
Systems Engineering and Engineering
Management Dept
jleung@se.cuhk.edu.hk
Track(s): 43
Operational Research and
Quantitative Models in Banking
Optimization Modeling in
OR/MS
Constantin Zopounidis
Technical University of Crete
kostas@dpem.tuc.gr
Track(s): 38 43
Robert Fourer
AMPL Optimization Inc.
4er@ampl.com
Operational Research in
Financial and Management
Accounting
Matthias Amen
University of Bielefeld
Matthias.Amen@web.de
Track(s): 43
Operations Finance Interface
Anne Lange
Technische Universität Darmstadt
a.lange@bwl.tu-darmstadt.de
Track(s): 24
Operations/Marketing Interface
Kathryn E. Stecke
University of Texas at Dallas
KStecke@utdallas.edu
Jun Zhang
Fudan University
jzhang4@gmail.com
Xuying Zhao
University of Notre Dame
xzhao1@nd.edu
Track(s): 27
Bjarni Kristjansson
Maximal Software, Ltd.
bjarni@maximalsoftware.com
Track(s): 21
Natashia Boland
The University of Newcastle
natashia.boland@newcastle.edu.au
Concepcion Maroto
Universitat Politecnica de Valencia
cmaroto@eio.upv.es
Marc McDill
Penn State University
mmcdill@psu.edu
Leif Sandal
Norwegian School of Economics
leif.sandal@nhh.no
Track(s): 36
OR in Petrochemicals and
Mining
Vikas Goel
ExxonMobil
goelvikas@gmail.com
Dimitri Papageorgiou
ExxonMobil
djpapag@gatech.edu
Track(s): 29
Optimization Models and
Algorithms in Energy Industry
OR in Quality Management
Cristina Corchero
Catalonia Institute for Energy
Research
ccorchero@irec.cat
Ipek Deveci Kocakoç
Dokuz Eylul University Faculty of
Economics and Administrative
Sciences
ipek.deveci@deu.edu.tr
F.-Javier Heredia
Universitat Politècnica de Catalunya BarcelonaTech
f.javier.heredia@upc.edu
Track(s): 10
Gulser Koksal
Middle East Technical University
koksal@metu.edu.tr
Track(s): 27
OR and Ethics
OR in Water Management
Cristobal Miralles
Universidad Politecnica de Valencia
cmiralles@omp.upv.es
Track(s): 24
Maddalena Nonato
Universita’ di Ferrara
nntmdl@unife.it
Track(s): 43
OR Consultancy and Case
Studies
Petroleum Logistics
Sue Merchant
Blue Link Consulting
suemerchant@hotmail.com
John Ranyard
Retired
jranyard@cix.co.uk
Track(s): 21
262
OR in Agriculture, Forestry and
Fisheries
Irina Gribkovskaia
Molde University College Specialized University in Logistics
irina.gribkovskaia@himolde.no
Evrim Ursavas
University of Groningen
e.ursavas@rug.nl
Iris F.A. Vis
University of Groningen
i.f.a.vis@rug.nl
Track(s): 5
IFORS 2014 - Barcelona
Preference Learning
Krzysztof Dembczynski
Poznan University of Technology
kdembczynski@cs.put.poznan.pl
Salvatore Greco
University of Catania
salgreco@unict.it
Roman Slowinski
Poznan University of Technology
roman.slowinski@cs.put.poznan.pl
Willem Waegeman
NGDATA
willem.waegeman@ugent.be
Track(s): 24
Production and the Link with
Supply Chain
Lionel Amodeo
University of Technology of Troyes
lionel.amodeo@utt.fr
Farouk Yalaoui
University of Technology of Troyes
farouk.yalaoui@utt.fr
Track(s): 40
Production Management &
Supply Chain Management
Kathryn E. Stecke
University of Texas at Dallas
KStecke@utdallas.edu
Track(s): 32
Project Management and
Scheduling
Rainer Kolisch
Technische Universitaet Muenchen
rainer.kolisch@wi.tum.de
Vicente Valls
University of Valencia
Vicente.Valls@uv.es
Track(s): 12
Qualitative Multiple Criteria
Decision Making
Marko Bohanec
Jozef Stefan Institute
marko.bohanec@ijs.si
Vladislav Rajkovič
University of Maribor
vladislav.rajkovic@gmail.com
Track(s): 42
Quality and Performance
Measurement in Humanitarian
Relief Chains
Sadia Samar Ali
Fortune Institute of International
Business , New Delhi - 110057, India
sadiasamarali@gmail.com
Track(s): 44
Quantitative Models for
Performance and Dependability
Mikhail Kuznetsov
Moscow Institute of Physics and
Technology
mikhail.kuznecov@phystech.edu
Vadim Strijov
Russian Academy of Sciences,
Computing Center
strijov@ccas.ru
Track(s): 40
Railway and Metro
Transportation
Leo Kroon
Erasmus University Rotterdam
lkroon@rsm.nl
Juan A. Mesa
University of Seville
jmesa@us.es
Anita Schöbel
Georg-August Universiy Goettingen
schoebel@math.uni-goettingen.de
Track(s): 1
Realistic Production Scheduling
Ruben Ruiz
Universitat Politècnica de València
rruiz@eio.upv.es
Track(s): 14
Recovery Inventory
Management Policies
Nagihan Comez Dolgan
Bilkent University
comez@bilkent.edu.tr
Track(s): 37
STREAMS
Revenue Management I
Luce Brotcorne
INRIA
Luce.Brotcorne@inria.fr
Sumit Kunnumkal
Indian School of Business
Sumit_Kunnumkal@isb.edu
Huseyin Topaloglu
Cornell University
huseyin@orie.cornell.edu
Track(s): 15
Scheduling
Erwin Pesch
University of Siegen
erwin.pesch@uni-siegen.de
Track(s): 13 14
Scheduling under Resource
Constraints
Joanna Jozefowska
Poznañ University of Technology
jjozefowska@cs.put.poznan.pl
Track(s): 12
Simulation in Management
Accounting and Management
Control
Stephan Leitner
Alpen-Adria-Universität Klagenfurt
stephan.leitner@aau.at
Friederike Wall
Alpen-Adria-Universitaet Klagenfurt
friederike.wall@uni-klu.ac.at
Track(s): 44
Simulation Methods in Finance
Aysegul Iscanoglu Cekic
Selcuk University
iscanoglu@yahoo.com
Gerhard-Wilhelm Weber
Middle East Technical University
gweber@metu.edu.tr
Track(s): 27
Simulation-Optimization in
Logistics & Production
Albert Ferrer
Technological University of Catalonia
(UPC)
alberto.ferrer@upc.edu
Angel A. Juan
Fundació per a la Universitat Oberta
de Catalunya
ajuanp@gmail.com
Track(s): 41
263
STREAMS
Social and Economic Networks
Ozan Candogan
Duke University
ozan.candogan@duke.edu
Track(s): 6
IFORS 2014 - Barcelona
Stochastic Optimization in
Energy
Technical and Financial
Aspects of Energy Problems
Warren Powell
Princeton University
powell@princeton.edu
Track(s): 20
Raimund Kovacevic
University Vienna
raimund.kovacevic@univie.ac.at
Soft OR / Systems and
Multimethodology
Stochastic Programming
Giles Hindle
Hull University Business School
giles.hindle@hull.ac.uk
Francois Louveaux
University of Namur
francois.louveaux@unamur.be
John Mingers
Kent University
j.mingers@kent.ac.uk
Suvrajeet Sen
University of Southern California
s.sen@usc.edu
Track(s): 45
Leroy White
University of Bristol
leroy.white@bris.ac.uk
Track(s): 38
Stochastic Modeling and
Simulation in Engineering,
Management and Science
Katsunori Ano
Shibaura Institute of Technology
k-ano@shibaura-it.ac.jp
Natashia Boland
The University of Newcastle
natashia.boland@newcastle.edu.au
Erik Kropat
Universität der Bundeswehr München
erik.kropat@unibw.de
Zeev (Vladimir) Volkovich
Ort Braude Academic College
zeev@actcom.co.il
Gerhard-Wilhelm Weber
Middle East Technical University
gweber@metu.edu.tr
Track(s): 35
Stochastic Models for Service
Operations
Francesca Maggioni
University of Bergamo
francesca.maggioni@unibg.it
Track(s): 41
264
Strategy and Analytics
Martin Kunc
University of Warwick
martin.kunc@wbs.ac.uk
Maria Teresa Vespucci
University of Bergamo
maria-teresa.vespucci@unibg.it
Track(s): 9
Telecommunications and
Networks
Bernard Fortz
Université Libre de Bruxelles
bfortz@euro-online.org
Ivana Ljubic
University of Vienna
ivana.ljubic@univie.ac.at
Track(s): 31
Frances O’Brien
University of Warwick
Frances.O-Brien@wbs.ac.uk
Track(s): 24
Theoretical Developments in
DEA
Supply Chain Management
Dimitris Despotis
University of Piraeus
despotis@unipi.gr
Moritz Fleischmann
University of Mannheim
Moritz.Fleischmann@bwl.unimannheim.de
Herbert Meyr
University of Hohenheim
H.Meyr@uni-hohenheim.de
Track(s): 4
Sustainable Development
Tatjana Vilutiene
Vilnius Gediminas Technical
University
tatjana.vilutiene@vgtu.lt
Track(s): 45
Teaching OR/MS
Maria Antónia Carravilla
Universidade do Porto | Faculdade de
Engenharia
mac@fe.up.pt
Track(s): 8 30
Ozren Despic
Aston University
o.despic@aston.ac.uk
Dario Landa-Silva
University of Nottigham
dario.landasilva@nottingham.ac.uk
Track(s): 10
Traffic Equilibrium
Michael Patriksson
Chalmers University of Technology
mipat@chalmers.se
Track(s): 41
Traffic Flow Theory and Traffic
Control
Nikolas Geroliminis
EPFL
nikolas.geroliminis@epfl.ch
Track(s): 4
Vehicle Routing
Daniele Vigo
University of Bologna
daniele.vigo@unibo.it
Track(s): 2
Session Chair Index
Álvarez-Miranda, Eduardo . . . . . . . . . . . . . . . . . . . HB-31
ealvarez@utalca.cl
DMGI, Universidad de Talca, Curicó, Italy
Abi-Zeid, Irene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-31
Irene.Abi-Zeid@osd.ulaval.ca
University of Laval, Quebec City, QC, Canada
Abraham, Matan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-45
matanabraham@gmail.com
Actuarial Science, University of Cape Town, Cape Town,
Western Cape, South Africa
Acevedo, Andrés . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-37
acevedo83@gmail.com
Mechanical and Industrial Engineering, Concordia University, Montreal, Quebec, Canada
Aceves-García, Ricardo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-03
aceves@unam.mx
Sistemas, Universidad Nacional Autónoma de México, México, Distrito Federal, Mexico
Adida, Elodie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-32
elodie.goodman@ucr.edu
School of Business Administration, University of California
at Riverside, United States
Agell, Nuria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-45
nuria.agell@esade.edu
Information Systems Management, ESADE-URL, Spain
lena.altherr@fst.tu-darmstadt.de
Chair of Fluid Systems, Technische Universität Darmstadt,
Darmstadt, Germany
Alvarez-Valdes, Ramon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-21
ramon.alvarez@uv.es
Statistics and Operations Research, University of Valencia,
Burjassot, Spain
Amado, Carla . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-14
camado@ualg.pt
Faculdade de Economia, Universidade do Algarve, Faro, Portugal
Amar, A. D. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-34, FB-34
amaramar@shu.edu
Management Department, Seton Hall University, South Orange, NJ, United States
Amen, Matthias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-43
Matthias.Amen@web.de
Chair for Quantitative Accounting & Financial Reporting,
University of Bielefeld, Bielefeld, Germany
Amodeo, Lionel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-40
lionel.amodeo@utt.fr
Charles Delaunay Institute, University of Technology of
Troyes, Troyes, France
Ampountolas, Konstantinos . . . . . . . . . . . . . . . . . . . . . . . . . TE-04
konstantinos.ampountolas@glasgow.ac.uk
School of Engineering, University of Glasgow, United Kingdom
Akteke-Ozturk, Basak . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-43
bozturk@metu.edu.tr
Department of Industrial Engineering, Middle East Technical
University, Ankara, Turkey
Andersson, Henrik . . . . . . . . . . . . . . . . . . . . . . . . . . HA-05, ME-35
Henrik.Andersson@iot.ntnu.no
Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology,
Trondheim, Norway
Albareda Sambola, Maria . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-03
maria.albareda@upc.edu
Statistics and Operations Research, Technical University of
Catalonia, Terrassa, Spain
Angelo, Simone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-22
simonealdrey@yahoo.com.br
Operational Research, Federal University of Rio de Janeiro UFRJ, Angra dos Reis, Rio de Janeiro, Brazil
Ali, Sadia Samar . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-44, HE-44
sadiasamarali@gmail.com
Operations Management, Fortune Institute of International
Business , New Delhi - 110057, India, New Delhi, India
Anjos, Miguel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-17
anjos@stanfordalumni.org
Mathematics and Industrial Engineering & GERAD, Polytechnique Montreal, Montreal, Quebec, Canada
Aliefendioğlu, Kaan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-21
kaan.aliefendioglu@gmail.com
Industrial Engineering, Istanbul Kültür University, Istanbul,
Turkey
Ano, Katsunori . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-35
k-ano@shibaura-it.ac.jp
Mathematical Sciences, Shibaura Institute of Technology,
Saitama-shi, Saitama-ken, Japan
Almeida, João . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-30
jpa@ipb.pt
Mathematics, LIAAD - INESC TEC and Instituto Politécnico
de Bragança, Bragança, Portugal
Ansell, Jake . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-43
J.Ansell@ed.ac.uk
Business Studies, The University of Edinburgh, Edinburgh,
United Kingdom
Alshahrani, Mohammed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-26
mshahrani@kfupm.edu.sa
Mathematics and Statistics, King Fahd University of
Petroleum and Minerals (KFUPM), DHAHRAN, Other,
Saudi Arabia
Arikan, Emel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-33
earikan@wu.ac.at
Information Systems and Operations, Vienna University of
Economics and Business, Austria
Altekin, F. Tevhide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-04
altekin@sabanciuniv.edu
Sabanci School of Management, Sabanci University, Istanbul, Turkey
Altherr, Lena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-21
Arlt, Josef . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-34
arlt@vse.cz
Department of Statistics and Probability, University of Economics, Prague, Prague, Czech Republic
Arns Steiner, Maria Teresinha . . . . . . . . . . . . . . . . . . . . . . MB-32
maria.steiner@pucpr.br
265
SESSION CHAIR INDEX
IFORS 2014 - Barcelona
Industrial Engineering Dept., PUCPR, Curitiba, Pr, Brazil
Artigues, Christian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-28
artigues@laas.fr
LAAS, CNRS, Toulouse Cedex 4, France
Batmaz, Inci . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-17
ibatmaz@metu.edu.tr
Department of Statistics, Middle East Technical University,
Ankara, Turkey
Asta, Shahriar. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-33, HE-33
Sba@cs.nott.ac.uk
Computer Science, The University of Nottingham, Nottingham, Nottingham, United Kingdom
Battaïa, Olga . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-13
battaia@emse.fr
IE & Computer Science, Ecole des Mines de Saint Etienne,
Saint Etienne, France
Atoche, Wilmer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-10
watoche@pucp.edu.pe
Ingeniería Industrial, Pontificia Universidad Católica del
Perú, Lima, Peru
Battiti, Roberto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-40
battiti@disi.unitn.it
DISI - Dipartimento di Informatica e Telecomunicazioni,
Universita’ di Trento, Trento, Italy
Ayer, Turgay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-39
ayer@isye.gatech.edu
Industrial and Systems Engineering, Georgia Tech, Atlanta,
GA, United States
Baucells, Manel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-31
manel.baucells@upf.edu
Economics and Business, Universitat Pompeu Fabra,
Barcelona, Spain
Azizi, Nader . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-45
n.azizi@kent.ac.uk
Kent Business School, University of Kent, Chatham, Kent,
United Kingdom
Baudach, Jens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-35
baudach@itl.tu-dortmund.de
Institute of Transport Logistics, TU Dortmund University,
Dortmund, NRW, Germany
Azizoglu, Meral . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-12
ma@metu.edu.tr
Department of Industrial Engineering, Middle East Technical
University, Ankara, Turkey
Baydoğan, Mustafa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-42
mustafa.baydogan@boun.edu.tr
Department of Industrial Engineering, Boğaziçi University,
İstanbul, Turkey
Baesens, Bart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-25
bart.baesens@econ.kuleuven.ac.be
Decision
Sciences
and
Information
Mangement,
K.U.Leuven, Leuven, Leuven, Belgium
Belenguer, José Manuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-02
jose.belenger@uv.es
Estadística i Investigació Operativa, Universitat de València,
Burjasot, Valencia, Spain
Baisa, Brian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-41
bbaisa@amherst.edu
Dept of Economics, Amherst College, Amherst, MA, United
States
Bell, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-08
pbell@ivey.ca
Western Univesity, Ivey Business School, London, Ontario,
Canada
Baldemor, Milagros . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-40
milagrosbaldemor@yahoo.com
Mathematics, DMMMSU, San Fernando, Philippines
Beraldi, Patrizia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-45
patrizia.beraldi@unical.it
Department of Mechanical, Energy and Management Engineering, University of Calabria, Rende (CS), ITALY, Italy
Ballestero, Enrique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-38
eballe@esp.upv.es
Escuela Politecnica Superior de Alcoy, Technical University
of Valencia, Alcoy (Alicante), Spain
Ballestin, Francisco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-12
Francisco.Ballestin@uv.es
Matematicas para la Economia, Universidad de Valencia, Valencia, Spain
Barceló, Jaume . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-04
jaume.barcelo@upc.edu
Statistics and Operations Research, Universitat Politècnica
de Catalunya, Barcelona, Spain
Baringo, Luis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-09
Luis.Baringo@gmail.com
EEH - Power Systems Laboratory, ETH Zurich, Zürich,
Switzerland
Barros, Ana Isabel . . . . . HA-33, TA-33, TB-33, TD-33, TE-33
ana.barros@tno.nl
Military Operations, TNO, The Hague, Netherlands
Bastert, Oliver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-28
oliverbastert@fico.com
FICO, Munich, Germany
266
Berman, Oded . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-03
berman@rotman.utoronto.ca
Rotman School of Management, University of Toronto,
Toronto, ON, Canada
Bertazzi, Luca . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-41
bertazzi@eco.unibs.it
Dept. of Quantitative Methods, University of Brescia, Brescia, Italy
Bettinelli, Andrea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-02
andrea.bettinelli@unibo.it
DEI, Università di Bologna, Bologna, Italy
Bichler, Martin. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-41, TE-43
martin.bichler@in.tum.de
Informatics, TU München, Garching, Germany
Bierwirth, Christian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-02
christian.bierwirth@wiwi.uni-halle.de
Martin-Luther-University Halle-Wittenberg, Halle, Germany
Bimpikis, Kostas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-06
kostasb@stanford.edu
Stanford GSB, Stanford, CA, United States
IFORS 2014 - Barcelona
Bloemhof, Jacqueline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-08
jacqueline.bloemhof@wur.nl
Operations Research and Logistics, Wageningen University,
Wageningen, Netherlands
Bohanec, Marko . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-42, FB-42
marko.bohanec@ijs.si
Department of Knowledge Technologies, Jozef Stefan Institute, Ljubljana, Slovenia
Boland, Natashia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-29
natashia.boland@newcastle.edu.au
School of Mathematical and Physical Sciences, The University of Newcastle, Callaghan, NSW, Australia
Bomze, Immanuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-16
immanuel.bomze@univie.ac.at
Dept. of Statistics and OR, University of Vienna, Vienna,
Austria
Bordin, Chiara . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-09
chiara.bordin2@unibo.it
Department of Electrical, Electronic and Information Engineering (DEI), University of Bologna, Bologna, Italy, Italy
Borgwardt, Steffen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-45
borgwardt@ma.tum.de
Fakultät für Mathematik, Technische Universität München,
Garching, Bayern, Germany
Bouarab, Hocine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-02
hocine.bouarab@gerad.ca
MAGI, Polytechnique, Montreal, Qc, Canada
Boudia, Mourad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-03
mourad.boudia@amadeus.com
Operations Research and Innovation, Amadeus, Sophia Antipolis, France
Bourreau, Eric . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-28
eric.bourreau@lirmm.fr
LIRMM, Montpellier, France
Bozic, Caslav . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-38
caslav.bozic@kit.edu
Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Brailsford, Sally . . . . . MA-39, MB-39, MD-39, ME-39, TA-39,
TB-39
s.c.brailsford@soton.ac.uk
University of Southampton, Southampton, United Kingdom
Brandao, Jose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-23
sbrandao@eeg.uminho.pt
Management, University of Minho; CEMAPRE — ISEG,
University of Lisbon, Braga, Portugal
Brandenburg, Marcus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-08
marcus.brandenburg@tu-berlin.de
Department of Production Management, Technische Universität Berlin, Berlin, Germany
Brandt, Felix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-02
brandt@fzi.de
Information Process Engineering, FZI Research Center for
Information Technology, Karlsruhe, Germany
Brauneis, Alexander . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-44
alexander.brauneis@aau.at
Finance & Accounting, University of Klagenfurt, Klagenfurt,
Austria
SESSION CHAIR INDEX
Bravo, Mila . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-38
mibrasel@epsa.upv.es
Universitat Politècnica de València, Alcoy, Spain
Brieden, Andreas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-45
andreas.brieden@unibw.de
Universität der Bundeswehr München, Neubiberg, Germany
Briskorn, Dirk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-13
briskorn@uni-wuppertal.de
University of Wuppertal, Germany
Brugha, Cathal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-29
Cathal.Brugha@ucd.ie
Management Information Systems, University College
Dublin, Dublin 4, Ireland
Bruni, Maria Elena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-41
mariaelena.bruni@unical.it
Department of Mechanical, Energy and Management Engineering, unical, cosenza, italy, Italy
Bulgarini, Niccolo’ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-41
niccolo.bulgarini@unifi.it
Dipartimento di Ingegneria dell’Informazione, Universita’
degli Studi di Firenze, Florence, Tuscany, Italy
Burkhardt, Thomas . . . . . . . . . . . . . . . . . . . . . . . . . MA-30, TB-30
tburkha@uni-koblenz.de
Campus Koblenz, IfM, Universitaet Koblenz-Landau,
Koblenz, Germany
Burlak, Gennadiy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-35
gburlak@uaem.mx
Centro de Investigaciones en Ingeniería y Ciencias Aplicadas,
Universidad Autónoma del Estado de Morelos, Cuernavaca,
Mexico
Buttrey, Samuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-22
buttrey@nps.edu
Operations Research, Naval Postgraduate School, Monterey,
CA, United States
Caballini, Claudia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-05
claudia.caballini@unige.it
DIBRIS - Department of Informatics, Bioengineering,
Robotics and System Engineering. CIELI - Italian Centre
of Excellence in Integrated Logistics, University of Genova,
Genova, Italy, Italy
Cacchiani, Valentina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-11
valentina.cacchiani@unibo.it
DEI, University of Bologna, Bologna, Italy
Cadarso, Luis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-01, MD-03
luis.cadarso@urjc.es
Rey Juan Carlos University, Fuenlabrada, Madrid, Spain
Caimi, Gabrio Curzio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-01
gabrio.caimi@bls.ch
Netzentwicklung, BLS Netz AG, Bern, Bern, Switzerland
Calabrese, Raffaella . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-38
rcalab@essex.ac.uk
University of Essex, Colchester, United Kingdom
Candogan, Ozan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-06
ozan.candogan@duke.edu
Fuqua School of Business, Duke University, Durham, NC,
United States
Cano, Javier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-31
267
SESSION CHAIR INDEX
IFORS 2014 - Barcelona
javier.cano@urjc.es
Rey Juan Carlos University, Spain
Cardonha, Carlos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-13
chcardo@br.ibm.com
Systems of Engagement and Insight, IBM Research - Brazil,
São Paulo, São Paulo, Brazil
United Kingdom
Ciarallo, Frank . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-08
frank.ciarallo@wright.edu
College of Engineering & Computer Science, Wright State
University, Dayton, Ohio, United States
Carmona, Manuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-28
mcarmona@palisade.com
Palisade UK Ltd., West Drayton, United Kingdom
Clarke, Nancy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-17, FB-17
nancy.clarke@acadiau.ca
Mathematics and Statistics, Acadia University, Wolfville,
Nova Scotia, Canada
Caro, Gegoire . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-34
caro@swissquant.ch
swissQuant Group AG, Zürich, Switzerland
Cohn, Amy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-03
amycohn@umich.edu
University of Michigan, United States
Carreras, Ashley . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-38
acarreras@dmu.ac.uk
Leicester Business School, De Montfort University, Leicester, United Kingdom
Colombi, Marco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-02
marco.colombi@ing.unibs.it
Department of Information Engineering, University of Brescia, Brescia, Italy
Carrizosa, Emilio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-25
ecarrizosa@us.es
Estadistica e Investigacion Operativa, Universidad de Sevilla,
Sevilla, Spain
Conn, Andrew . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-28
arconn@us.ibm.com
IBM TJ Watson Research Center, New York, United States
Castañer-Garriga, Anna . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-24
acastaner@ub.edu
Universitat de Barcelona, Barcelona, Spain
Corchero, Cristina . . . . . . . . . . . . . . . . . . . . . . . . . . MA-10, ME-10
ccorchero@irec.cat
Electrical Engineering Research Area, Catalonia Institute for
Energy Research, Sant Adria del Besos, Spain
Ceparano, Maria Carmela . . . . . . . . . . . . . . . . . . . . . . . . . . ME-25
milena.ceparano@gmail.com
Department of Economics and Statistics, University of
Naples Federico II, Napoli, NA, Italy
Costa, Ana Paula . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-42
apcabral@ufpe.br
Federal University of Pernambuco, Recife, PE, Brazil
Chaabane, Amin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-40
amin.chaabane@etsmtl.ca
Departement of Automated Manufacturing Engineering,
École de Technologie Supérieure, Montreal, Quebec, Canada
Chakraborty, Arnab . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-23
arnab.d.chakraborty@accenture.com
Accenture Analytics, Bangalore, India
Chao, Yu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-14
yc@chu.edu.tw
Business Administration, Chung Hua University, Hsinchu,
Taiwan
Chen, Argon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-19
achen@ntu.edu.tw
Industrial Engineering, National Taiwan University, Taiwan
Chen, Nan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-29
nchen@se.cuhk.edu.hk
Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin,
Hong Kong
Chiabaut, Nicolas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-04
nicolas.chiabaut@entpe.fr
Université de Lyon, ENTPE / IFSTTAR, Vaulx en Velin,
France
Choudhary, Alok . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-06
a.choudhary@sheffield.ac.uk
Management School, University of Sheffield, Sheffield,
United Kingdom
Christodoulou, Giorgos . . . . . . . . . . . . . . . . . . . . . . HD-22, HE-22
gchristo@liv.ac.uk
Computer Science, University of Liverpool, Liverpool,
268
Crawford, Broderick . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-25
broderick.crawford@ucv.cl
Pontificia Universidad Catolica de Valparaiso, Chile
Crespo, Fernando . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-27
facrespo@gmail.com
Universidad Central de Chile, Santiago, Región Metropolitana, Chile
Crook, Jonathan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-43
j.crook@ed.ac.uk
University of Edinburgh Business School, University of Edinburgh, Edinburgh, Lothian, United Kingdom
Cruz-Zambrano, Miguel . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-10
mcruz@irec.cat
Energy Economics Group, Institut de Recerca en Energia de
Catalunya, Sant Adria del Besos, Spain
Dangaard Brouer, Berit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-05
blof@man.dtu.dk
DTU Management Engineering, Technical University of
Denmark - DTU, Kongens Lyngby, Denmark
Dargam, Fatima. . . . . . . . . . . . . . . . . . . . . . HA-42, HD-42, TE-42
F.Dargam@SimTechnology.com
SimTech Simulation Technology, Graz, Austria
Dash, Gordon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-30
ghdash@uri.edu
Finance and Decision Sciences, University of Rhode Island,
Kingston, RI, United States
Datta, Subhash . . . . . . . . . . . . . . . . . . . . . . . FA-27, FB-36, TB-40
subhash.datta@gmail.com
Centre for Inclusive Growth and Sustainable Development,
GURGAON, Haryana, India
IFORS 2014 - Barcelona
De Causmaecker, Patrick . . . . . . . . . . . . . . . . . . . . HD-33, HE-33
Patrick.DeCausmaecker@kuleuven-kortrijk.be
Computer Science/CODeS, Katholieke Universiteit Leuven,
Kortrijk, Flanders, Belgium
de Koster, René . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-04
rkoster@rsm.nl
Rotterdam School of Management, Erasmus University Rotterdam, Rotterdam, Netherlands
de Oliveira, Manuela Maria . . . . . . . . . . . . . . . . . . . . . . . . MA-35
moliveira@ipma.pt
IPMA, Portugal
de Oliveira, Welington . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-26
welingtonluis@gmail.com
IMPA, Rio de Janeiro, Rio de Janeiro, Brazil
Deckmyn, Gaby . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-36
gaby.deckmyn@uantwerpen.be
University of Antwerpen UA, Wilrijk, Belgium
Defterli, Ozlem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-07, HD-35
defterli@cankaya.edu.tr
Department of Mathematics and Computer Science, Cankaya
University, Ankara, Turkey & Saginaw Valley State University, College of Science, Engineering and Technology, MI,
USA (currently as PostDoc), Saginaw, Michigan, United
States
Dehmer, Matthias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-03
matthias.dehmer@univie.ac.at
Bundeswehr Universität München, Germany
Deineko, Vladimir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-30
v.deineko@warwick.ac.uk
Warwick Business School, Warwick University, Coventry,
United Kingdom
del Rosario, Elise . . . . . . . . . . . . . . FB-27, TA-44, TB-44, TD-44
elise@jgdelrosario.com
OSSFFI, Quezon City, Metro Manila, Philippines
Delorme, Xavier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-13, HE-13
delorme@emse.fr
Fayol-emse, Cnrs, Umr 6158, Limos, Ecole des Mines de
Saint Etienne, Saint Etienne, France
Demange, Marc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-12
demange@essec.edu
ESSEC Business School and LAMSADE UMR 7243, Paris,
France
Demir, Emrah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-42, MD-42
e.demir@tue.nl
School of Industrial Engineering, Eindhoven University of
Technology, Eindhoven, Netherlands
Desai, Jitamitra . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-39
jdesai@ntu.edu.sg
School of Mechanical and Aerospace Engineering, Nanyang
Technological University, Singapore
Despotis, Dimitris . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-10
despotis@unipi.gr
Department of Informatics, University of Piraeus, Piraeus,
Greece
DeTombe, Dorien . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-29
detombe@nosmo.nl
Methodology of Societal Complexity, Chair Euro Working
Group, Amsterdam, Netherlands
SESSION CHAIR INDEX
Devine, Mel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-10
mel.devine@ul.ie
Department of Mathematics & Statistics, University of Limerick, Ireland
Dias, Luis C. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-31
lmcdias@fe.uc.pt
Faculdade de Economia / INESC Coimbra, Univ. Coimbra,
Coimbra, Portugal
Doerner, Karl . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-12
karl.doerner@jku.at
Institute for Production and Logistics Management, Johannes
Kepler University Linz, Linz, Austria
Dolgui, Alexandre . . . . . HA-13, HB-13, HD-13, HE-13, TB-13,
TE-13
dolgui@emse.fr
IE & Computer Science, Ecole des Mines de Saint Etienne,
Saint Etienne, France
Dos Santos, Maria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-33
maria.dossantos@kerp.at
R & D, Weee, KERP Competence Center Electronics & Environment, Vienna, Austria
Doumpos, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-16
mdoumpos@dpem.tuc.gr
School of Production Engineering and Management, Technical University of Crete, Chania, Greece
Duarte, Abraham . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-37
abraham.duarte@urjc.es
Computer Sciences, Universidad Rey Juan Carlos, Madrid,
Spain
Ebara, Hiroyuki . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-25
ebara@kansai-u.ac.jp
The Faculty of Engineering Science, Kansai University,
Suita, Osaka, Japan
Ehrgott, Matthias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-44
m.ehrgott@lancaster.ac.uk
Management Science, Lancaster University, Lancaster,
United Kingdom
Ejov, Vladimir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-39
vladimir.ejov@flinders.edu.au
School of Computer Science, Engineering and Mathematics,
Flinders University, Bedford Park, SA, Australia
Ekenberg, Love . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-31
lovek@dsv.su.se
Dept. of Computer and Systems Sciences, Stockholm University, Kista, -, Sweden
Engau, Alexander . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-18, TB-18
aengau@alumni.clemson.edu
Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO, United States
Erdem, Sabri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-40
sabri.erdem@deu.edu.tr
Business Administration, Dokuz Eylul University Faculty of
Business, IZMIR, Turkey
Eriksson, Ola . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-36
Ljusk.Ola.Eriksson@slu.se
Department of Forest Resource Management, Swedish University of Agricultural Sciences, Umea, Sweden
269
SESSION CHAIR INDEX
IFORS 2014 - Barcelona
Escobar-Toledo, Carlos Enrique . . . . . . . . . . . . . . . . . . . . . TB-08
carloset@servidor.unam.mx
Chemical Engineering. Faculty of Chemistry., National University of Mexico (UNAM), Mexico City, DF, Mexico
Euler, Reinhardt . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-12, MD-12
reinhardt.euler@univ-brest.fr
Informatique, Université de Brest, Brest, France
Evans, Antony . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-03
antony.evans@ucl.ac.uk
UCL Energy Institute, University College London, London,
United Kingdom
Faco’, Joao Lauro D.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-39
jldfaco@ufrj.br
Dept. of Computer Science, Universidade Federal do Rio de
Janeiro, Rio de Janeiro, RJ, Brazil
Franke, Susanne . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-26
susanne.franke@math.tu-freiberg.de
TU Bergakademie Freiberg, Germany
Freixas, Josep . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-27
josep.freixas@upc.edu
Applied Mathematics 3, Technical University of Catalonia,
Manresa, Spain
Fries, Carlos Ernani . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-14
carlos.fries@ufsc.br
Department of Production and Systems Engineering, Federal
University of Santa Catarina, Florianopolis, Santa Catarina,
Brazil
Fu, Qi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-37
gracefu@umac.mo
University of Macau, Macau
Fagerholt, Kjetil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-05
kjetil.fagerholt@iot.ntnu.no
Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology,
Trondheim, Norway
Fuduli, Antonio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-26
antonio.fuduli@unical.it
Dipartimento di Matematica e Informatica, Universita’ della
Calabria, Rende, Italy
Fan, Yueyue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-20
yyfan@ucdavis.edu
Civil and Environmental Engineering, University of California, Davis, Davis, CA, United States
Funes, Mariana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-42
mfunes@eco.unc.edu.ar
Facultad de Ciencias Económicas - Universidad Nacional de
Córdoba, Córdoba, Argentina
Faulin, Javier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-41
javier.faulin@unavarra.es
Dept. Statistics and Operations Research, Public University
of Navarre, Pamplona, Navarra, Spain
Gaidamaka, Yuliya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-31
ygaidamaka@sci.pfu.edu.ru
Telecommunication Systems Department, Peoples’ Friendship University of Russia, Moscow, Russian Federation
Fernandez, Elena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MC-50
e.fernandez@upc.edu
Statistics and Operations Research, Technical University of
Catalonia, Barcelona, Spain
Gamache, Michel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-06
michel.gamache@polymtl.ca
Mathematics and Industrial Engineering, École Polytechnique de Montréal, Montréal, Quebec, Canada
Ferrer, Albert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-41
alberto.ferrer@upc.edu
Dpt. of Applied Mathematics I, Technological University of
Catalonia (UPC), Barcelona, Catalunya, Spain
Gamrath, Gerald . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-39, HB-39
gamrath@zib.de
Zuse-Institute Berlin, Berlin, Germany
Fichtner, Wolf . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-08
wolf.fichtner@wiwi.uni-karlsruhe.de
Chair of Energy Economics, KIT, Karlsruhe, Germany
Figueroa-García, Juan Carlos . . . . . . . . . . . . . . . . . . . . . . . HD-07
filthed@gmail.com
Engineering, Universidad Nacional de Colombia, Bogotá,
Cundinamarca, Colombia
Fink, Andreas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-12
andreas.fink@hsu-hamburg.de
Chair of Information Systems, Helmut-Schmidt-University,
Hamburg, Germany
Fourer, Robert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-21, MB-21
4er@ampl.com
AMPL Optimization Inc., Evanston, IL, United States
Fox, Edward . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-19
efox@mail.cox.smu.edu
Marketing, Southern Methodist University, Dallas, Texas,
United States
Franco, L. Alberto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-23
L.A.Franco@lboro.ac.uk
School of Business and Economics, Loughborough University, Loughborough, United Kingdom
270
Gao, David . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-17
d.gao@federation.edu.au
Federation University Australia, Mt Helen, Australia
Garbs, Matthias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-08
matthias.garbs@wiwi.uni-goettingen.de
Chair of Production and Logistics, University of Göttingen,
Göttingen, Germany
García-Jurado, Ignacio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-22
igjurado@udc.es
Department of Mathematics, Coruna University, Coruna,
Spain
García-Villoria, Alberto . . . . . . . . . . . . . . . . . . . . . HD-13, HE-13
alberto.garcia-villoria@upc.edu
Universitat Politècnica de Catalunya, Spain
Garcia-Gonzalo, Jordi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-36
Jordigarcia@isa.utl.pt
Forest Research Centre, Instituto Superior de Agronomia,
Lisbon, Portugal
Gaudioso, Manlio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-26
gaudioso@dimes.unical.it
DIMES, Università della Calabria, Rende, Italy
Gavalec, Martin . . . . . . . . . . . . . . . . . . . . . . ME-26, TA-26, TB-26
IFORS 2014 - Barcelona
martin.gavalec@uhk.cz
Department of Information Technologies FIM, University of
Hradec Kralove, Hradec Kralove, Czech Republic
Gendreau, Michel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-41
michel.gendreau@cirrelt.ca
MAGI and CIRRELT, École Polytechnique, Montreal, Quebec, Canada
Geroliminis, Nikolas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-04
nikolas.geroliminis@epfl.ch
ENAC, EPFL, Lausanne, Switzerland
Gianfreda, Angelica . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-09
agianfreda@london.edu
Management Science and Operations, London Business
School, London, United Kingdom
SESSION CHAIR INDEX
versity of Catania, Catania, Italy
Gribkovskaia, Irina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-05
irina.gribkovskaia@himolde.no
Faculty of Economics, Informatics and Social Sciences,
Molde University College - Specialized University in Logistics, Molde, Norway
Grigoroudis, Evangelos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-29
vangelis@ergasya.tuc.gr
Department of Production Engineering & Management,
Technical University of Crete, Chania, Greece
Gritzmann, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-25, TB-45
gritzman@ma.tum.de
Mathematics, TU München, Munich, Germany
Gimbert, Hugo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-24
hugo.gimbert@labri.fr
CNRS, LaBRI, Bordeaux, France
Guerrin, Francois . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-07
francois.guerrin@cirad.fr
UPR Recyclage & Risque, Inra & Cirad, Montpellier Cedex
5, France
Glover, Fred . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-11, TD-40
fredwglover@yahoo.com
ECEE, University of Colorado, Boulder, Clorado, United
States
Guignard-Spielberg, Monique . . . . . . . . . . . . . . . . . . . . . . . HB-11
guignard_monique@yahoo.fr
OPIM, University of Pennsylvania, Philadelphia, PA, United
States
Goel, Gagan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-22
gagangoel@google.com
Google Research, New York, New York, New York, United
States
Guo, Pengfei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-22
pengfei.guo@polyu.edu.hk
Faculty of Business, Hong Kong Polytechnic University,
Hong Kong
Goel, Vikas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-29
goelvikas@gmail.com
ExxonMobil, Houston, TX, United States
Gurgur, Cigdem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-39
gurgurc@ipfw.edu
Management, Purdue University, Fort Wayne, IN, United
States
Gomes, A. Miguel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-21
agomes@fe.up.pt
INESC TEC, Faculdade de Engenharia, Universidade do
Porto, Porto, Portugal
Gomez San Roman, Tomas . . . . . . . . . . . . . . . . . . . . . . . . . MB-10
tomas.gomez@iit.upcomillas.es
Institute for Research in Technology - IIT, Universidad Pontificia Comillas, ICAI School of Engineering, Madrid, Spain
Gomis, Oriol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-10
ogomis@irec.cat
Universitat Politecnica de Catalunya, Barcelona, Spain
Gonçalves, José Fernando . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-21
jfgoncal@fep.up.pt
LIAAD, INESC TEC, Faculdade de Economia do Porto, Universidade do Porto, Porto, Portugal
Gondzio, Jacek . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-17
j.gondzio@ed.ac.uk
School of Mathematics, University of Edinburgh, Edinburgh,
United Kingdom
Gorgone, Enrico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-26
egorgone@ulb.ac.be
Département d’Informatique, Université Libre de Bruxelles,
Bruxelles, Belgium
Goyal, Vineet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-20
vgoyal@ieor.columbia.edu
Columbia University, New York, NY, United States
Greco, Salvatore . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-24
salgreco@unict.it
Deapartment of Economics and Quantitative Methods, Uni-
Gurski, Frank . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-39
frank.gurski@hhu.de
Institute of Computer Science, University of Düsseldorf,
Düsseldorf, Germany
Gutjahr, Walter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-31
walter.gutjahr@univie.ac.at
Department of Statistics and Decision Support Systems, University of Vienna, Vienna, Vienna, Austria
Haddad, Jack . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-04
jh@technion.ac.il
Technion Israel Institute of Tech, Haifa, Israel
Hakanen, Jussi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-18
jussi.hakanen@jyu.fi
Dept. of Mathematical Information Technology, University
of Jyvaskyla, University of Jyvaskyla, Finland
Hamacher, Silvio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-29
hamacher@puc-rio.br
PUC-Rio, Rio de Janeiro, Brazil
Hanzalek, Zdenek . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-08
hanzalek@fel.cvut.cz
CTU Prague, Prague, Czech Republic
Hao, Jin-Kao . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-40
hao@info.univ-angers.fr
LERIA, Université d’Angers, Angers, France
Harris, Shannon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-06
sharris@katz.pitt.edu
Katz Graduate School of Business, Pittsburgh, PA, United
States
271
SESSION CHAIR INDEX
IFORS 2014 - Barcelona
Hartikainen, Markus . . . . . . . . . . . . . . . . . . . . . . . MB-18, MD-18
markus.e.hartikainen@jyu.fi
Department of Mathematical Information Technology, University of Jyväskylä, University of Jyvaskyla, Finland
Hoberg, Kai . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-19
Kai.Hoberg@the-klu.org
Supply Chain and Operations Strategy, Kühne Logistics University, Hamburg, Germany
Hasgul, Servet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-13
shasgul@ogu.edu.tr
Industrial Engineering, Eskisehir Osmangazi University, Eskisehir, Turkey
Hoechstoetter, Markus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-38
markus.hoechstoetter@kit.edu
Statistics, Kit - Econ, Karlsruhe, Baden-Wuerttemberg, Germany
Hasle, Geir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-25
geir.hasle@sintef.no
Applied Mathematics, Sintef Ict, Oslo, Norway
Holeček, Pavel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-26
pavel.holecek@upol.cz
Department of Mathematical Analysis and Applications of
Mathematics, Palacky University in Olomouc, Olomouc,
Czech Republic
Hämäläinen, Raimo P. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-23
raimo.hamalainen@aalto.fi
Systems Analysis Laboratory, Aalto University ,School fo
Science, AALTO, Finland
He, Xuedong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-29
xh2140@columbia.edu
Industrial Engineering and Operations Research, Columbia
University, New York, United States
Holguin-Veras, Jose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-32
jhv@rpi.edu
Rensselaer Polytechnic Institute, United States
Homberger, Jörg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-12
joerg.homberger@hft-stuttgart.de
Stuttgart, Germany
Hearne, John . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-36
john.hearne@rmit.edu.au
Mathematical and Geospatial Sciences, RMIT University,
Melbourne, Victoria, Australia
Hougaard, Jens Leth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-14
jlh@foi.ku.dk
Institute of Food and Resource Economics, University of
Copenhagen, Copenhagen, Denmark
Hein, Nelson . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-34
hein@furb.br
Mathematics, FURB, Blumenau, Santa Catarina, Brazil
Huang, Yuan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-40
yuan.huang@soton.ac.uk
University of Southampton, Southampton, United Kingdom
Heipcke, Susanne . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-28
susanneheipcke@fico.com
Xpress Optimization, FICO, Marseille, France
Huangfu, Qi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-21
qihuangfu@fico.com
FICO, Birmingham, United Kingdom
Heredia, F.-Javier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-10
f.javier.heredia@upc.edu
Statistics and Operations Research, Universitat Politècnica
de Catalunya - BarcelonaTech, Barcelona, Catalunya, Spain
Humpola, Jesco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-28
humpola@zib.de
Optimization, Zuse Institute Berlin, Berlin, Berlin, Germany
Hernandez, German . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-07
jhonpetrucci2000@yahoo.es
Universidad Nacional de Colombia, Colombia
Herrmann, Frank . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-35
Frank.Herrmann@HS-Regensburg.de
Innovation and Competence Centre for Production Logistics
and Factory Planning, Technical University of Applied Sciences Regensburg, Regensburg, Germany
Hesamzadeh, Mohammad Reza . . . . . . . . . . . . . . . . . . . . . TB-07
mrhesamzadeh@ee.kth.se
Electric Power Systems, KTH Royal Institute of Technology,
Stockholm, Sweden
Huppmann, Daniel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-07
dhuppmann@diw.de
DIW Berlin, Berlin, Germany
Hvattum, Lars Magnus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-05
lars.m.hvattum@iot.ntnu.no
Dept of Industrial Economics and Technology Management,
Norwegian University of Science and Technology, Trondheim, Norway
Iida, Yoichi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-37
iida@rs.suwa.tus.ac.jp
Department of Business Administration and Information,
Tokyo University of Science, Suwa, Chino, Nagano, Japan
Hibiki, Norio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-30
hibiki@ae.keio.ac.jp
Administration Engineering, Keio University, Yokohama,
Japan
Inceoglu, Gonca . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-14
inceoglugonca@gmail.com
Education Faculty - Department of Primary Education - Program in Primary School Mathematic Teaching, Anadolu University, Eskisehir, Turkey
Hildmann, Marcus . . . . . . . . . . . . . . . . . . MA-34, MD-34, ME-34
hildmann@eeh.ee.ethz.ch
Information Technology and Electrical Engineering, ETH
Zurich, Zürich, Switzerland
Ingolfsson, Armann . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-19
Armann.Ingolfsson@UAlberta.Ca
School of Business, University of Alberta, Edmonton, Alberta, Canada
Hindle, Giles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-38
giles.hindle@hull.ac.uk
Mangement Systems, Hull University Business School, Hull,
United Kingdom
Irzhavski, Pavel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-12
irzhavski@bsu.by
Department of Discrete Mathematics and Algorithmics, Faculty of Applied Mathematics and Computer Science, Belaru-
272
IFORS 2014 - Barcelona
sian State University, Minsk, Belarus
Ivkin, Nikita . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-16, HE-16
ivkinnikita@gmail.com
Faculty of Management and Applied Mathematics, Moscow
Institute of Physics and Technology (State University), Dolgoprudny, Moscow Region, Russian Federation
Jacquillat, Alexandre . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-35
alexjacq@mit.edu
Engineering Systems Division, MIT, Cambridge, MA, United
States
Jadbabaie, Ali . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-06
jadbabai@seas.upenn.edu
Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA, United States
Jiménez-Martín, Antonio . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-31
antonio.jimenez@upm.es
Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid (UPM), Boadilla del Monte, Madrid, Spain
Jimenez-Lopez, Mariano . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-26
mariano.jimenez@ehu.es
Economía Aplicada I, University of the Basque Country, San
Sebastian, Spain
Joormann, Imke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-39
joormann@mathematik.tu-darmstadt.de
Research Group Optimization, Dept. of Mathematics, Technical University Darmstadt, Germany
Jozefowska, Joanna . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-12
jjozefowska@cs.put.poznan.pl
Institute of Computing Science, Poznañ University of Technology, Poznañ, Wielkopolska, Poland
Juan, Angel A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-41, TE-41
ajuanp@gmail.com
Computer Science, Fundació per a la Universitat Oberta de
Catalunya, Barcelona, Spain
Juenger, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-11
mjuenger@informatik.uni-koeln.de
Institut fuer Informatik, Universitaet zu Koeln, Koeln, Germany
Kaczmarczyk, Waldemar . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-14
waldek@agh.edu.pl
Department of Operations Research & Information Technology, AGH University of Science & Technology, Krakow,
Poland
Kajiji, Nina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-30
nina@nkd-group.com
Computer Science and Statistics, University of Rhode Island,
and The NKD Group, Inc., Kingston, RI, United States
Kapucugil-Ikiz, Aysun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-27
aysun.kapucugil@deu.edu.tr
Business Administration, Dokuz Eylul University, Izmir,
Turkey
Karaer, Ozgen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-37
okaraer@metu.edu.tr
Industrial Engineering, Middle East Technical University,
Ankara, Turkey
Karalkova, Anastasiya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-05
anastasiya.karalkova@himolde.no
Molde University College- Spescialized University in Logis-
SESSION CHAIR INDEX
tics, Norway
Karapetyan, Daniel . . . . . . . . . . . . . . . . . . . . . . . . . . HB-33, HE-33
daniel.karapetyan@gmail.com
Computer Science, University of Nottingham, Nottingham,
United Kingdom
Karmitsa, Napsu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-26
napsu@karmitsa.fi
Department of Mathematics and Statistics, University of
Turku, Turku, Finland
Kasimbeyli, Refail . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-02
rkasimbeyli@anadolu.edu.tr
Industrial Engineering, Anadolu University, Eskisehir,
Turkey
Katehakis, Michael . . . . . . . . . . . . . . . . . . . . . . . . . HA-19, MB-19
mnk@rutgers.edu
Rutgers, Piscataway, NJ, United States
Kazaz, Burak . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-24
bkazaz@syr.edu
Syracuse University, Syracuse, United States
Kedad-Sidhoum, Safia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-28
safia.kedad-sidhoum@lip6.fr
Lip6 - Upmc, Paris, France
Kemahlioglu-Ziya, Eda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-22
ekemahl@ncsu.edu
North Carolina State University, Raleigh, United States
Kersten, Gregory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-23
gregory@jmsb.concordia.ca
Concordia University, Ottawa, Ontario, Canada
Kersting, Jan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-08
jan.kersting@isi.fraunhofer.de
Energy Policy and Energy Markets, Fraunhofer Institute for
Systems and Innovation Research ISI, Karlsruhe, Germany
Kesavan, Saravanan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-27
skesavan@unc.edu
UNC Kenan-Flagler, Chapel Hill, North Carolina, United
States
Khritankov, Anton . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-16, HB-16
anton.khritankov@acm.org
MIPT, Russian Federation
Kim, Kihoon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-15
kihoon@korea.ac.kr
Korea University Business School, Korea, Republic Of
Kim, Seoung Bum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-42
sbkim1@korea.ac.kr
Industrial Management Engineering, Korea University,
Seoul, Korea, Republic Of
Kimms, Alf . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-22
alf.kimms@uni-due.de
Mercator School of Management, University of DuisburgEssen, Duisburg, Germany
Kimura, Yutaka . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-09, MB-09
yutaka@akita-pu.ac.jp
Systems Science and Technology, Akita Prefectural University, Yuri-honjo, Akita, Japan
Kinoshita, Eizo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-29
kinoshit@urban.meijo-u.ac.jp
273
SESSION CHAIR INDEX
IFORS 2014 - Barcelona
Urban Science Department, Meijo University, Kani, Gifu,
Japan
Kischka, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-33
P.Kischka@wiwi.uni-jena.de
Statistics, University Jena, Jena, Germany
Klabjan, Diego . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-41
d-klabjan@northwestern.edu
Industrial Engineering and Management Sciences, Northwestern University, Evanston, IL, United States
Krarup, Jakob . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-28
krarup@diku.dk
Dept. of Computer Science, University of Copenhagen,
Birkeroed, Denmark
Kress, Moshe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-32
mkress@nps.edu
Operations Research, Naval Postgraduate School, Monterey,
CA, United States
Kleinmuntz, Don . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-23
don@kleinmuntzassociates.com
Kleinmuntz Associates, Chicago, IL, United States
Kroenke, Adriana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-25
didlen@terra.com.br
PPGMNE/Mathematics, UFPR/FURB, Blumenau, Santa
Catarina, Brazil
Klibi, Walid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-41
walid.klibi@kedgebs.com
Operations Management and Information Systems Department, Kedge Bs / Cirrelt, Bordeaux, France
Krokhmal, Pavlo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-20
krokhmal@engineering.uiowa.edu
Mechanical and Industrial Engineering, University of Iowa,
Iowa city, IA, United States
Koberstein, Achim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-04
koberstein@wiwi.uni-frankfurt.de
Business Administration, Goethe-University of Frankfurt,
Frankfurt am Main, Germany
Kroon, Leo . . . . . . . . . . . . . . . . . . . . FA-01, HE-01, ME-01, TA-01
lkroon@rsm.nl
Rotterdam School of Management, Erasmus University Rotterdam, Rotterdam, Netherlands
Koc, Ali . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-20
akoc@us.ibm.com
Business Analytics and Mathematical Sciences, IBM TJ Watson Research Center, Yorktown Heights, NY, United States
Kropat, Erik . . . . . . . . . HD-07, HE-07, FB-27, MA-32, MB-32,
ME-32, TA-32, TB-32, HA-35, HD-35, HE-35, MA-35,
ME-35, TE-35
erik.kropat@unibw.de
Department of Computer Science, Universität der Bundeswehr München, Neubiberg, Germany
Kochenberger, Gary . . . . . . . . . . . . . . . . . . . . . . . . . MB-11, TD-40
gary.kochenberger@ucdenver.edu
University of Colorado Boulder, Boulder, United States
Koksal, Gulser . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-43
koksal@metu.edu.tr
Industrial Engineering, Middle East Technical University,
Ankara, Turkey
Koksalan, Murat. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-18
koksalan@metu.edu.tr
Industrial Engineering, METU, Turkey
Korhonen, Pekka . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-18
pekka.korhonen@aalto.fi
Information and Service Economy, Aalto University School
of Business, Helsinki, Finland
Korotkov, Vladimir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-19
wladko@tut.by
Department of Mathematics and Statistics, University of
Turku, Turku, Finland
Kostoglou, Vassilis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-40
vkostogl@it.teithe.gr
Department of Informatics, Alexander TEI of Thessaloniki,
Thessaloniki, Greece
Kovalyov, Mikhail Y. . . . . . . . . . . . . . . . . . . . . . . . . . HA-13, TE-13
kovalyov_my@yahoo.co.uk
United Institute of Informatics Problems, National Academy
of Sciences of Belarus, Minsk, Belarus
Kozeletskyi, Igor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-22
igor.kozeletskyi@uni-due.de
Mercator School of Management, University of DuisburgEssen, Duisburg, Germany
Kraft, Volker . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-08
volker.kraft@jmp.com
JMP Devision, SAS Institute, Heidelberg, Germany
274
Kuş, Coşkun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-43
coskun@selcuk.edu.tr
Statistics, Selçuk University, Konya, Turkey
Kuefer, Karl-Heinz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-18
karl-heinz.kuefer@itwm.fraunhofer.de
Optimization, Fraunhofer ITWM, Kaiserslautern, Germany
Kuhn, Heinrich . . . . . . . . . . . . . . . . . . . . . HA-19, HB-19, MA-19
heinrich.kuhn@ku-eichstaett.de
Operations Management, Catholic University of EichstaettIngolstadt, Ingolstadt, Bavaria, Germany
Kunnumkal, Sumit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-15
Sumit_Kunnumkal@isb.edu
Indian School of Business, Hyderabad, India
Kunz, Timo P. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-15
t.p.kunz@lancaster.ac.uk
Management Science, Lancaster University Management
School, Lancaster, United Kingdom
Kuyzu, Gultekin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-04
gkuyzu@etu.edu.tr
Industrial Engineering, TOBB University of Economics and
Technology, Ankara, Turkey
Laguna, Manuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-11, TD-40
laguna@colorado.edu
Leeds School of Business, University of Colorado at Boulder,
Boulder, Colorado, United States
Lahaie, Sebastien . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-22
slahaie@microsoft.com
Microsoft Research, United States
Lai, Chien-Jung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-23
laicj@ncut.edu.tw
Department of Distribution Management, National Chin-Yi
IFORS 2014 - Barcelona
University of Technology, Taichung, Taiwan
Lai, Chunhui . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-12
laich2011@msn.cn
School of Mathematics and Statistics, Minnan Normal University, Zhangzhou, Fujian, China
SESSION CHAIR INDEX
Shatin, New Territories, Hong Kong
Liao, Feixiong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-32
f.liao@tue.nl
Urban planning group, TU/e, Eindhoven, Netherlands
Lal, Tarun Mohan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-06
mohanlal.tarun@mayo.edu
Mayo Clinic, Rochester, MN, United States
Liberti, Leo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-11
leoliberti@gmail.com
TJ Watson Research Center, IBM Research, Yorktown
Heights, NY, United States
Lange, Anne . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-24
a.lange@bwl.tu-darmstadt.de
Department of Law and Economics, Technische Universität
Darmstadt, Darmstadt, Germany
Liesiö, Juuso . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-31
juuso.liesio@aalto.fi
Systems Analysis Laboratory, Aalto University, Espoo, Finland
Lantz, Frederic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-38
frederic.lantz@ifpen.fr
IFP-School, Rueil-Malmaison, France
Lim, Yuchul . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-13
tmxhfl13@kaist.ac.kr
Industrial & System Engineering, KAIST, Korea, Republic
Of
Laumanns, Marco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-01
mlm@zurich.ibm.com
IBM Research - Zurich, Rueschlikon, Switzerland
Le Thi, Hoai An . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-17, TB-17
hoai-an.le-thi@univ-lorraine.fr
Computer Science, University of Lorraine, Metz, France
Leclercq, Ludovic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-04
Ludovic.LECLERCQ@entpe.fr
COSYS, Université de Lyon, IFSTTAR / ENTPE, Bron,
France
Lee, Amy H. I. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-37
amylee@chu.edu.tw
Department of Technology Management, Department of Industrial Management, Chung Hua University, Hsinchu, Taiwan
Lee, Eva . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-28
eva.lee@isye.gatech.edu
Industrial and Systems Engineering, Georgia Institute of
Technology, Atlanta, GA, United States
Leitner, Markus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-31
markus.leitner@univie.ac.at
Department of Statistics and Operations Research, University
of Vienna, Vienna, Austria
Leitner, Stephan . . . . . . . . . . . . . . FA-15, FB-15, HE-15, MB-44
stephan.leitner@aau.at
Department of Controlling and Strategic Management,
Alpen-Adria-Universität Klagenfurt, Klagenfurt, Austria
Lesaja, Goran . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-14
goran@georgiasouthern.edu
Mathematical Sciences, Georgia Southern University, Statesboro, Georgia, United States
Lessmann, Stefan . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-40, HE-40
lessmann@econ.uni-hamburg.de
Institute of Information Systems, University of Hamburg,
Hamburg, Germany
Letmathe, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-08, TA-08
Peter.Letmathe@rwth-aachen.de
Faculty of Business and Economics, RWTH Aachen University, Aachen, Germany
Leung, Janny . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-22, HB-43
jleung@se.cuhk.edu.hk
Systems Engineering and Engineering Management Dept,
Linden, Isabelle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-42, HE-42
isabelle.linden@unamur.be
Departement of Business Administration, University of Namur, Namur, Belgium
Liu, Shaofeng . . . . . . . . . . . . . . . . . . . . . . . . HB-42, HE-42, TE-42
shaofeng.liu@plymouth.ac.uk
Graduate School of Management, University of Plymouth,
Plymouth, United Kingdom
Liu, Xin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-38, TE-38
liuxin@lsec.cc.ac.cn
State Key Laboratory of Scientific and Engineering Computing, Academy of Mathematics and Systems Science, Chinese
Academy of Sciences, Beijing, China
Ljubic, Ivana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-31
ivana.ljubic@univie.ac.at
Department of Statistics and Operations Research, University
of Vienna, Vienna, Austria
Loeffler, Andreas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-30
al@wacc.de
Banking and Finance, Freie Universität Berlin, Berlin, Germany
Löhndorf, Nils . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-20
nils.loehndorf@wu.ac.at
Vienna University of Economics and Business, Wien, Austria
Loiseau, Irene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-02, FB-02
irene@dc.uba.ar
Departamento de Computación-, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires,
Argentina
Long, Elisa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-06
elisa.long@anderson.ucla.edu
Anderson School of Management, UCLA, Los Angeles, California, United States
Lorenz, Ulf . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-43
ulf.lorenz@fst.tu-darmstadt.de
Chair of Fluid Systems, Technische Universität Darmstadt,
Darmstadt, Germany
Lotero, Laura . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-27, TB-40
llotero0@unal.edu.co
Ciencias de la computación y de la decisión, Universidad
Nacional de Colombia, Medellin, Antioquia, Colombia
275
SESSION CHAIR INDEX
IFORS 2014 - Barcelona
Louveaux, Francois . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-45
francois.louveaux@unamur.be
Business Administration, University of Namur, Belgium
Lucheroni, Carlo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-43
carlo.lucheroni@unicam.it
School of Science and Technologies, University of Camerino,
Camerino (MC), Italy
Luhandjula, Monga K . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-26
luhanmk@unisa.ac.za
Decision Sciences, University of South Africa, Pretoria,
Gauteng, South Africa
Luke, Russell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-38
r.luke@math.uni-goettingen.de
Institute for Numerical and Applied Math, Universität Göttingen, Göttingen, Niedersachsen, Germany
Lukszo, Zofia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-20
z.lukszo@tudelft.nl
Energy and Industry, Delft University of Technology, Delft,
Zuid Holland, Netherlands
Lundy, Michele . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-37
michele.lundy@port.ac.uk
Business School, University of Portsmouth, United Kingdom
Luo, Sirong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-27
luo.sirong@mail.shufe.edu.cn
School of Statistics and Management, Shanghai University
of Finance and Economics, Shanghai, China
Luque, Mariano . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-18
mluque@uma.es
Applied Economics (Mathematics), University of Malaga,
Malaga, Spain
Lusby, Richard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-01
rmlu@man.dtu.dk
Department of Management Engineering, Technical University of Denmark, Kgs Lyngby, Denmark
Maag, Volker . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-18
maag@itwm.fhg.de
Optimization,
Fraunhofer-Institut für Techno- und
Wirtschaftsmathematik, Kaiserslautern, Germany
Macharis, Cathy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-37
Cathy.Macharis@vub.ac.be
BUTO-MOBI, Vrije Universiteit Brussel, Brussels, Belgium
Maculan, Nelson . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-11, TC-50
maculan@cos.ufrj.br
Ufrj-coppe / Pesc, Universidade Federal do Rio de Janeiro,
Rio de Janeiro, RJ, Brazil
Maldonado, Michelli . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-41
michellimaldo@gmail.com
UNESP - Sao Paulo State University, SJ do Rio Preto, Sp,
Brazil
Malekian, Azarakhsh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-06
azarakhsh.malekian@rotman.utoronto.ca
Rotman School of Business, University of Toronto, Toronto,
ON, Canada
Mallozzi, Lina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-30
mallozzi@unina.it
Matematica e Applicazioni, Università di Napoli Federico II,
Napoli, Italy
276
Malo, Pekka . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-18
pekka.malo@aalto.fi
Information and Service Economy, Aalto University School
of Economics, Helsinki, Finland
Manerba, Daniele . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-02
daniele.manerba@unibs.it
Dept. of Information Engineering, University of Brescia,
Brescia, BS, Italy
Marín, Ángel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-01
angel.marin@upm.es
Matemática Aplicada y Estadística, Universidad Politécnica
de Madrid, Madrid, Madrid, Spain
Marín, Alfredo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-03
amarin@um.es
Departamento de Estadística e Investigación Operativa, University of Murcia, Murcia, Spain
Marcotte, Patrice . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-15, FB-41
marcotte@iro.umontreal.ca
DIRO, Université de Montréal, Montréal, Québec, Canada
Maroto, Concepcion . . . . . . . . . . . . . . . . . . . . . . . . . . FA-36, TE-36
cmaroto@eio.upv.es
Applied Statistics, Operations Research and Quality, Universitat Politecnica de Valencia, Valencia, Spain
Martínez Gamboa, Jeyson Andrés . . . . . . . . . . . . . . . . . . . ME-42
je-i-sson92@hotmail.com
Ingeniería Industrial, Universidad Libre, Bogotá, Colombia
Martello, Silvano . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-11
silvano.martello@unibo.it
DEIS, University of Bologna, Bologna, Italy
Martin-Campo, F. Javier . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-37
javier.martin.campo@ccee.ucm.es
Estadistica e Investigacion Operativa II, Universidad Complutense de Madrid, Pozuelo de Alarcón (Madrid), Spain
Martinez Sykora, Antonio . . . . . . . . . . . . . . . . . . . . . . . . . . HA-21
A.Martinez-Sykora@soton.ac.uk
Management School, University of Southampton, Southampton, United Kingdom
Martins, Pedro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-32
pmartins@iscac.pt
ISCAC, Polytechnic Institute of Coimbra and Operations Research Center, Coimbra, Portugal
Maruyama, Yukihiro . . . . . . . . . . . . . . . . . . . . . . . MA-09, MD-09
maruyama@nagasaki-u.ac.jp
General Economics, Nagasaki University, Nagasaki, Japan
Masuda, Yasushi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-35
masuda@ae.keio.ac.jp
Faculty of Science and Tech, Keio University, Yokohama,
Japan
Mat Kasim, Maznah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-37
maznah@uum.edu.my
School of Quantitative Sciences, Universiti Utara Malaysia,
Sintok, Kedah, Malaysia
Matos Dias, Joana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-39
joana@fe.uc.pt
Univ Coimbra - FEUC, Inesc Coimbra, Coimbra, Portugal
Matsatsinis, Nikolaos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-29
nikos@ergasya.tuc.gr
IFORS 2014 - Barcelona
Department of Production Engineering and Management,
Technical University of Crete, Chania, Greece
Matsui, Tomomi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-09
matsui.t.af@m.titech.ac.jp
Department of Social Engineering, Tokyo Institute of Technology, Tokyo, Japan
Matsui, Yasuko . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-09
yasuko@tokai-u.jp
Mathematical Sciences, Tokai University, Hiratsuka-shi,
Kanagawa, Japan
Mawengkang, Herman . . . . . . . . . . . . . . MB-17, MD-17, ME-17
mawengkang@usu.ac.id
Mathematics, The University of Sumatera Utara, Medan, Indonesia
May, Jerrold . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-06
jerrymay@katz.pitt.edu
KGSB, University of Pittsburgh, Pittsburgh, PA, United
States
Mazalov, Vladimir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-35
vmazalov@krc.karelia.ru
Karelia Research Center of Russian Academy of Sciences,
Institute of Appied Mathematical Research,Karelia Research
Center, Petrozavodsk, Karelia, Russian Federation
Mbiydzenyuy, Gideon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-04
gmb@bth.se
Department of Computer Science and Engineering, Blekinge
Institute of Technology, Karlshamn, Sweden
McDill, Marc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-36
mmcdill@psu.edu
Ecosystem Science and Management, Penn State University,
State College, Pennsylvania, United States
Meca, Ana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-22, TE-22
ana.meca@umh.es
Operations Research Center, Universidad Miguel Hernández,
Elche, Alicante, Spain
Mehrotra, Sanjay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-43
mehrotra@northwestern.edu
Industrial Engineering and Management Sciences, Northwestern University, Evanston, IL, United States
Meisel, Frank . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-44
frank.meisel@wiwi.uni-halle.de
Martin-Luther-University Halle-Wittenberg, Halle, Germany
Mejia Delgadillo, Gonzalo Enrique . . . . . . . . . . . . . . . . . . MA-40
gmejia@uniandes.edu.co
Industrial Engineering, Universidad de Los Andes, Bogota,
Colombia
Mendez-Aguirre, A. Carlos . . . . . . . . . . . . . . . . . . . . . . . . . . TD-41
cmendez@intec.unl.edu.ar
Intec (unl-conicet), Santa Fe, Santa Fe, Argentina
Menendez, Monica . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-04
monica.menendez@ivt.baug.ethz.ch
ETH, Zurich, Zurich, Switzerland
Menezes, Mozart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-03
mozartmenezes@me.com
Haskayne School of Business, University of Calgary, Calgary, Alberta, Canada
Merchant, Sue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-21
SESSION CHAIR INDEX
suemerchant@hotmail.com
Blue Link Consulting, Rickmansworth, Hertfordshire, United
Kingdom
Mertikopoulos, Panayotis . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-24
panayotis.mertikopoulos@imag.fr
Laboratoire d’Informatique de Grenoble, French National
Center for Scientific Research (CNRS), France
Mesa, Juan A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-01
jmesa@us.es
University of Seville, Sevilla, Spain
Meyer-Nieberg, Silja . HD-07, HE-07, MA-32, MB-32, ME-32,
TA-32, TB-32, HA-35, HD-35, HE-35, ME-35, TE-35
silja.meyer-nieberg@unibw.de
Department of Computer Science, Universität der Bundeswehr München, Neubiberg, Germany
Mihelcic, Goran . . . . . . . . . . . . . . . . . . . . . . TB-32, ME-35, TE-35
goran.mihelcic@unibw.de
Universität der Bundeswehr München, Germany
Miller-Hooks, Elise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-25
elisemh@umd.edu
University of Maryland, College Park, MD, United States
Mingozzi, Aristide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-11
mingozzi@csr.unibo.it
Department of Mathematics, University of Bologna, Cesena,
FC, Italy
Miralles, Cristobal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-24
cmiralles@omp.upv.es
Depto. Organización de Empresas, Universidad Politecnica
de Valencia, Valencia, Spain
Mizhidon, Klara . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-07
migka@mail.ru
Applied Mathematics, East Siberia State University of Technology and Management, Ulan-Ude, Russian Federation
Monaci, Michele . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-11
monaci@dei.unipd.it
D.E.I., University of Padua, Padova, Italy
Montoya-Torres, Jairo R. . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-40
jrmontoy@yahoo.com
Universidad de La Sabana, Colombia, and University of
Leeds, UK, Chia, Colombia
Morales, Juan Miguel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-07
jmmgo@dtu.dk
Applied Mathematics and Computer Science, Technical University of Denmark, Kgs. Lyngby, Denmark
Moreno, Eduardo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-29
eduardo.moreno@uai.cl
Faculty of Engineering and Sciences, Universidad Adolfo
Ibañez, Santiago, Chile
Moreno, Rodrigo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-10
r.moreno@imperial.ac.uk
Dept. of Electrical Engineering, University of Chile & Imperial College, Chile
Mosheiov, Gur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-13
msomer@huji.ac.il
School of Business, Hebrew University, Jerusalem, Israel
Mucherino, Antonio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-11
antonio.mucherino@irisa.fr
277
SESSION CHAIR INDEX
IFORS 2014 - Barcelona
IRISA, University of Rennes 1, Rennes, France
Mujica Mota, Miguel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-23
m.mujica.mota@hva.nl
Aviation Academy, Amsterdam University of Applied Sciences, Amsterdam, Netherlands
Mukhopadhyay, Samar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-27
samar@skku.edu
GSB, SungKyunKwan University, Seoul, Korea, Republic Of
Murali, Pavankumar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-20
pmurali@usc.edu
USC, CA, United States
Nachtigall, Karl . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-01
karl.nachtigall@tu-dresden.de
Faculty of Transport and Traffic Sciences, Institut for Logistics and Aviation, Technical University of Dresden, Dresden,
Sachsen, Germany
Naderi, Siamak . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-26
Siamak@sabanciuniv.edu
Faculty of Engineering and Natural Sciences, Sabanci University, Turkey
Ivey Business School, Western University, London, Ontario,
Canada
Oesterle, Jonathan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-40
jno@ipa.fraunhofer.de
Fraunhofer IPA, Germany
Ohimmou, Mustapha . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-36
mustapha.ouhimmou@etsmtl.ca
Logistics and Operations Engineering, École de Technologie
Supérieure, Montréal, québec, Canada
Ohnishi, Masamitsu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-30
ohnishi@econ.osaka-u.ac.jp
Graduate School of Economics, Osaka University, Toyonaka,
Osaka, Japan
Oladejo, Michael O . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-04
mikeoladejo2003@yahoo.co
Mathematics, Nigerian Defence Academy Kaduna, Kaduna
Nigeria, Kaduna, Kaduna, Nigeria
Olgun, Mehmet Onur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-30
onurolgun@sdu.edu.tr
Industrial Engineering, Süleyman Demirel University, Turkey
Nagaoka, Sakae . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-03
nagaoka@enri.go.jp
Air Traffic Management, Electronic Navigation Research Institute, Chofu, Tokyo, Japan
Oliu Barton, Miquel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-44
oliubart@gmail.com
Institut de Mathématiques, Université de Neuchâtel, Neuchâtel, Switzerland
Nagy, Gabor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-45
G.Nagy@ukc.ac.uk
Canterbury Business School, University of Kent, Canterbury,
Kent, United Kingdom
Oliveira, Bruno M.P. M. . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-30
bmpmo@fcna.up.pt
Fcnaup & Inesc-tec, Porto, Portugal
Nakade, Koichi. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-35
nakade@nitech.ac.jp
Department of Civil Engineering and Systems Management,
Nagoya Institute of Technology, Nagoya, Japan
Negreiros, Marcos José . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-02
negreiro@graphvs.com.br
Mestrado Estrado Profissional EM COMPUTAÇÃO, Universitade Estadual do Ceara, Fortaleza, Ceara, Brazil
Neiva de Figueiredo, Joao . . . . . . . . . . . . . . . . . . . . . . . . . . MD-32
jneiva@sju.edu
Management, St Josephs University, Philadelphia, PA, United
States
Ng, Tony . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-43
ngh@mail.smu.edu
Department of Statistical Science, Southern Methodist University, Dallas, Texas, United States
Nickel, Stefan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FC-50
stefan.nickel@kit.edu
Institute for Operations Research (IOR), Karlsruhe Institute
of Technology (KIT), Karlsruhe, Germany
Nonato, Maddalena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-43
nntmdl@unife.it
EndIF, Universita’ di Ferrara, Ferrara, Italy
O’Brien, Frances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-24
Frances.O-Brien@wbs.ac.uk
Warwick Business School, University of Warwick, Coventry,
United Kingdom
Odegaard, Fredrik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-15
fodegaard@ivey.uwo.ca
278
Oliveira, José Fernando . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-11
jfo@fe.up.pt
INESC TEC, Faculty of Engineering, University of Porto,
Porto, Portugal
Olthoff, Inken . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-28
olthoff@zib.de
Zuse Institute Berlin, Germany
Öner, Nihat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-37
nihatoner10@gmail.com
Industrial Engineering Department, TOBB University of Economics and Technology, Ankara, Turkey
Onoda, Takashi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-16
onoda@criepi.denken.or.jp
System Engineering Lab., CRIEPI, Tokyo, Japan
Oren, Shmuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-07
shmuel@berkeley.edu
IEOR, UC-Berkeley, Berkeley, CA, United States
Ouelhadj, Djamila . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-41
djamila.ouelhadj@port.ac.uk
Maths, University of Portsmouth, Portsmouth, United Kingdom
Oussedik, Sofiane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-01
soussedik@fr.ibm.com
IBM, France
Ozdemir, Deniz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-05
deniz.ozdemir@yasar.edu.tr
Dept. of International Logistics Management, Yasar University, Izmir, Turkey
Ozen, Ulas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-22
IFORS 2014 - Barcelona
ulas.ozen@ozyegin.edu.tr
Ozyegin University, Istanbul, Turkey
Ozener, Okan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-02
orsan.ozener@ozyegin.edu.tr
Industrial Engineering, Ozyegin University, Istanbul, Turkey
Ozer, Ozalp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-15
oozer@utdallas.edu
Jindal School of Management, The University of Texas at
Dallas, Richardson, TX, United States
Özkan, Ozan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-12
oozkan@selcuk.edu.tr
Mathematics, Selçuk University, KONYA, Turkey, Turkey
Özmen, Ayse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-35
ayseozmen19@gmail.com
Scientific Computing, Institute of Applied Mathematics,
Middle East Technical University, Ankara, Turkey
SESSION CHAIR INDEX
Park, Jonghun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-42
jonghun@snu.ac.kr
Industrial Engineering, Seoul National University, Seoul, Korea, Republic Of
Parkes, Andrew J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-33
ajp@cs.nott.ac.uk
School of Computer Science, University of Nottingham, Nottingham, United Kingdom
Pascoal, Marta . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-37
marta@mat.uc.pt
Departamento de Matemática, Universidade de Coimbra,
INESC-Coimbra, Coimbra, Portugal
Pavlenko, Liudmyla . . . . . . . . . . . . . . . . . . . TA-44, TB-44, TD-44
l.s.pavlenko@gmail.com
Academic Department, Ntuu Kpi, Kyiv, Ukraine, Ukraine
Ozsakalli, Gokberk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-05
gokberk.ozsakalli@gmail.com
Yasar University, Izmir, Turkey
Pearman, Alan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-19
a.d.pearman@leeds.ac.uk
Leeds University Business School, University of Leeds,
Leeds, West Yorkshire, United Kingdom
Pacino, Dario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-05
darpa@transport.dtu.dk
Transport, Technical University of Denmark (DTU), Kgs.
Lyngby, Denmark
Penn, Marion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-27
M.Penn@soton.ac.uk
School of Mathematics, University of Southampton,
Southampton, United Kingdom
Paixão, José . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-11, HD-39
jpaixao@fc.ul.pt
Dept. Statistics and Operations Research, Faculty of Sciences
- University of Lisbon, LISBOA, Portugal
Penn, Michal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-13
mpenn@ie.technion.ac.il
Industrial Engineering and Management, Technion, Haifa,
Israel
Paksoy, Turan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-39
tpaksoy@yahoo.com
Industrial Engineering, Selçuk University, Konya, Turkey
Penna, Puca Huachi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-02
ppenna@ic.uff.br
Instituto de Computacao, Universidade Federal Fluminense,
Niteroi, RJ, Brazil
Palancı, Osman . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-30
osmanpalanci@sdu.edu.tr
Mathematics, Suleyman Demirel University, Isparta, Turkey
Palma, Jaime . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-32
jaime.palma@itam.mx
Ingenieria Industrial y Operaciones, ITAM, Instituto Tecnológico Autónomo de México, Mexico DF, Distrito Federal,
Mexico
Papadaki, Katerina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-27
k.p.papadaki@lse.ac.uk
Management, London School of Economics and Political
Science, London, United Kingdom
Papamichail, Ioannis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-04
ipapa@dssl.tuc.gr
Production Engineering and Management, Technical University of Crete, Chania, Greece
Paraschiv, Florentina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-09
florentina.paraschiv@unisg.ch
Energy Finance, ior/cf HSG, Switzerland
Pardalos, Panos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-18, TE-18
pardalos@ufl.edu
ISE Department, University of Florida, Gainesville, Florida,
United States
Park, Jinwoo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-08
autofact@snu.ac.kr
Dept. of Industrial Engineering, Seoul National University,
Seoul, Korea, Republic Of
Perea, Federico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-14
perea@eio.upv.es
Estadística e Investigación Operativa Aplicadas y Calidad,
Universidad Politécnica de Valencia, Valencia, Spain
Perez, Ileana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-32
ileper@yahoo.com
Cali, Universidad San Buenaventura de Cali„ Cali, Valle del
Cauca, Colombia
Perić, Tunjo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-14
tperic@efzg.hr
Department of Mathematics, University of Zagreb, Faculty
of economics and business, Zagreb, Croatia
Petridis, Konstantinos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-08
kpetridi@fmenr.duth.gr
Department of Forestry and Management of the Environment
and Natural Resources, Democritus University of Thrace,
Orestiada, Greece
Petrosyan, Leon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-35
spbuoasis7@peterlink.ru
Applied Mathematics, St.Petersburg State University,
St.Petersburg, Russian Federation
Petrovic, Sanja . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-13
Sanja.Petrovic@nottingham.ac.uk
Division of Operations Management and Information Systems, Nottingham University Business School, Nottingham,
United Kingdom
279
SESSION CHAIR INDEX
IFORS 2014 - Barcelona
Pflug, Georg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-09
georg.pflug@univie.ac.at
Department of Statistics and Decision Support Systems, University of Vienna, Vienna, Austria
Pham Dinh, Tao . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-17, TB-17
pham@insa-rouen.fr
INSA Rouen, Rouen, France
Pickl, Stefan Wolfgang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-03
stefan.pickl@unibw.de
Department of Computer Science, UBw München
COMTESSA, Neubiberg-München, Bavaria, Germany
Pinto, Alberto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-30
aapinto1@gmail.com
Mathematics, University of Porto, Portugal
Pisciella, Paolo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-09
paolo.pisciella@unibg.it
Department of Management, Economics and Quantitative
Methods, University of Bergamo, Italy
Pishchulov, Grigory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-41
grigory.pishchulov@udo.edu
Faculty of Business, Economics and Social Sciences, TU
Dortmund University, Dortmund, Germany
Pla, LluisM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-36
lmpla@matematica.udl.es
Mathematics, University of Lleida, Lleida, Spain
Puetz, Markus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-43
markus.puetz@whl-lahr.de
Chair, Department of Managerial Accounting and Control,
WHL Graduate School of Business and Economics, Lahr,
Baden-Wuerttemberg, Germany
Quintanilla, Israel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-36
iquinta@cgf.upv.es
Cartographic Engineering, Universitat Politécnica de Valencia, Valencia, Spain
Quintero-Araújo, Carlos L. . . . . . . . . . . . . . . . . . . . . . . . . . MB-40
carlos.quintero5@unisabana.edu.co
International School of Economics and Administrative Sciences, Universidad de La Sabana, Chia, Cundinamarca,
Colombia
Rabiei, Nima . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-14
nima.rabiei@upc.edu
Applied Mathematics III, LACAN, Barcelona, Spain
Rademaker, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-24
michael.rademaker@ugent.be
Departement of Mathematical Modelling, Statistics and
Bioinformatics, Ghent University, Gent, Belgium
Raffray, Guilhem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-18
guilhem.raffray@cirad.fr
UMR Qualisud, CIRAD, Montpellier Cedex 5, France
Popescu, Ioana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-15
ioana.popescu@insead.edu
Decision Sciences, INSEAD, Singapore, Singapore
Rajkovič, Vladislav . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-42, FB-42
vladislav.rajkovic@gmail.com
Faculty of organizational sciences, University of Maribor,
Kranj, Slovenia
Postmus, Douwe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-29
d.postmus@umcg.nl
Epidemiology, University Medical Center Groningen,
Netherlands
Rakha, Hesham . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-04
hrakha@vt.edu
Virginia Tech, Virginia Tech, Blacksburg, Virginia, United
States
Potra, Florian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-14
potra@umbc.edu
Mathematics & Statistics, University of Maryland, Baltimore,
United States
Ralphs, Ted . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-30
tkralphs@lehigh.edu
Industrial and Systems Engineering, Lehigh University, Bethlehem, PA, United States
Powell, Warren . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-20
powell@princeton.edu
Department of Operations Research and Financial Engineering, Princeton University, Princeton, NJ
Ramalhinho Lourenco, Helena . . . . . . . . . . . . . . . . . . . . . . HB-40
helena.ramalhinho@upf.edu
UPF- Barcelona GSE, Barcelona, Spain
Preciado, Victor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-06
preciado@seas.upenn.edu
University of Pennsylvania, Philadelphia, PA, United States
Prigent, Jean-Luc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-34
jean-luc.prigent@u-cergy.fr
ThEMA, University of Cergy-Pontoise, Cergy-Pontoise,
France
Psaraftis, Harilaos N. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-05
hnpsar@gmail.com
Technical University of Denmark, Lyngby, Denmark
Puchinger, Jakob . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-42
jpuchinger@gmail.com
Mobility, AIT Austrian Institute of Technology GmbH, Wien,
Österreich, Austria
Puerto, Justo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-03
puerto@us.es
Estadistica e I.O., Universidad de Sevilla, Sevilla, Spain
280
Ramik, Jaroslav . . . . . . . . . . . . . . . . . . . . . . ME-26, TA-26, TB-26
ramik@opf.slu.cz
Dept. of Math. Methods in Economics, Silesian University,
School of Business, Karvina, Czech Republic
Ramos, Andres . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-10, TB-10
andres.ramos@iit.upco.es
Departamento de Organizacion Industrial - Instituto de Investigacion Tecnologica, Universidad Pontificia Comillas,
Madrid, Spain
Ramos, María Camila . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-15
mmramos@uc.cl
Pontificia Universidad Católica de Chile, Chile
Rand, Graham . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-28
g.rand@lancaster.ac.uk
Dept. of Management Science, Lancaster University, Lancaster, Lancashire, United Kingdom
Ranyard, John . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-21
jranyard@cix.co.uk
IFORS 2014 - Barcelona
Retired, Hope Valley, Derbyshire, United Kingdom
Rauner, Marion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-39
marion.rauner@univie.ac.at
Dept. Innovation and Technology Management, University
of Vienna, Vienna, Austria
Regan, Amelia C. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-25
aregan@uci.edu
Computer Science, University of California, Irvine, Irvine,
California, United States
Reisach, Ulrike . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-28, TA-45
ulrike.reisach@hs-neu-ulm.de
Information Management Faculty, Neu-Ulm University of
Applied Sciences, Neu-Ulm, Bavaria, Germany
Reyer, Ivan . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-16, TB-16, TE-16
reyer@forecsys.ru
Dorodnicyn Computing Centre of RAS, Moscow, Russian
Federation
Rezaei, Jafar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-06
j.rezaei@tudelft.nl
Transport and Logistics, Delft University of Technology,
Delft, Netherlands
Ribal, Javier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-36
frarisan@esp.upv.es
Economía y Ciencias Sociales, Universitat Politecnica de Valencia, Valencia, Spain
Rieck, Julia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-12
julia.rieck@tu-clausthal.de
Operations Research Group, Clausthal University of Technology, Clausthal-Zellerfeld, Germany
Riener, Cordian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-16
cordian.riener@aalto.fi
Aalto Science Institute, Aalto University, Helsinki, Finland
Roberti, Roberto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-11
roberto.roberti6@unibo.it
DEI, University of Bologna, Bologna, Italy
Robinson, Stewart . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-23, HE-34
s.l.robinson@lboro.ac.uk
School of Business and Economics, Loughborough University, Loughborough, United Kingdom
Roncoli, Claudio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-04
croncoli@dssl.tuc.gr
Dynamic Systems & Simulation Laboratory, Technical University of Crete (TUC), Chania, Greece
Rosset, Christian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-36
christian.rosset@bfh.ch
School of Agricultural, Forest and Food Sciences HAFL,
Bern University of Applied Sciences BFH, Zollikofen, BE,
Switzerland
Rotela Junior, Paulo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-34
paulo.rotela@gmail.com
IEPG - Instituto de Engenharia de Produção e Gestão,
UNIFEI - Universidade Federal de Itajubá, Itajubá, Minas
Gerais, Brazil
Rouwette, Etienne . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-23
e.rouwette@fm.ru.nl
Nijmegen School of Management, Radboud University Nijmegen, Nijmegen, Netherlands
SESSION CHAIR INDEX
Rubaszewski, Julie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-40
julie.rubaszewski@utt.fr
LOSI, Université de Technologie de Troyes, Troyes, France
Ruiz, Ruben . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-14
rruiz@eio.upv.es
Departamento de Estadistica e Investigación Operativa Aplicadas y Calidad, Universitat Politècnica de València, Valencia, Spain
Saat, Rapik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-05
mohdsaat@illinois.edu
Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, United States
Sabach, Shoham . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-38
ssabach@gmail.com
Institute for Numerical and Applied Mathematics, University
of Goettingen, Goettingen, Germany
Safaei Farahani, Samira . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-20
s.safaeifarahani@tudelft.nl
Energy and Industry, Delft University of Technology, Delft,
Zuid Holland, Netherlands
Safey El Din, Mohab . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-16
Mohab.Safey@lip6.fr
Paris 6, Paris, France
Sahman, Mehmet Akif . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-04
asahman@selcuk.edu.tr
Guneysinir Vocational School, Selcuk University, Konya,
Selçuklu, Turkey
Saldanha-da-Gama, Francisco . . . . . . . . . . . . . . . FA-03, HD-03
fsgama@fc.ul.pt
CIO/DEIO, University of Lisbon, Lisbon, Portugal
Salmeron, Javier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-09
jsalmero@nps.edu
Operations Research Dept., Naval Postgraduate School,
Monterey, CA, United States
Sandoh, Hiroaki . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-19
sandoh@econ.osaka-u.ac.jp
Graduate School of Economics, Osaka University, Toyonaka,
Osaka, Japan
Sanguineti, Marcello . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-31
marcello.sanguineti@unige.it
DIBRIS, University of Genoa, Genova, Italy
Sanjay, Kumar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-44, HB-44
sxk89@psu.edu
Black School of Business, Penn State University- Erie, Erie,
Pennsylvania, United States
Santos, José . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-37
zeluis@mat.uc.pt
Department of Mathematics, University of Coimbra, Coimbra, Portugal
Santos, Sérgio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-14
ssantos@ualg.pt
Faculdade de Economia, Universidade do Algarve and
CEFAGE, Faro, Portugal
Saraç, Tugba . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-21
tsarac@ogu.edu.tr
Department of Industrial Engineering, Eskisehir Osmangazi
University, Eskisehir, Turkey
281
SESSION CHAIR INDEX
IFORS 2014 - Barcelona
Sá Esteves, Jorge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-31
saesteves@ua.pt
Dep. of Mathematics, University of Aveiro, AVEIRO, Portugal
Scheithauer, Guntram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-21
Guntram.Scheithauer@tu-dresden.de
Mathematik, Technische Universität Dresden, Dresden, Germany
Schimmelpfeng, Katja . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-06
katja.schimmelpfeng@uni-hohenheim.de
Lehrstuhl für Beschaffung und Produktion, Universität Hohenheim, Stuttgart, Germany
Schlechte, Thomas . . . . . . . . . . . . . . . . . . . . . . . . . . MA-01, MB-01
schlechte@zib.de
Optimization, Zuse-Institute-Berlin, Berlin, Berlin, Germany
Schmidt, Marie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-01
m.schmidt@math.uni-goettingen.de
Institut für Numerische und Angewandte Mathematik,
Georg-August-Universität Göttingen, Göttingen, Germany
Schneur, Rina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-23
rina.schneur@verizon.com
Verizon, United States
Schweighofer, Markus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-16
markus.schweighofer@uni-konstanz.de
Fachbereich Mathematik und Statistik, Universität Konstanz,
Konstanz, Germany
Scutellà, Maria Grazia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-11
scut@di.unipi.it
Informatica, Universita’ di Pisa, Pisa, Italy
Secomandi, Nicola . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-20
ns7@andrew.cmu.edu
Tepper School of Business, Carnegie Mellon University,
Pittsburgh, PA, United States
Virginia Tech, Blacksburg, Virginia, United States
Sermpinis, Georgios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-26
Georgios.Sermpinis@glasgow.ac.uk
University of Glasgow, Glasgow, United Kingdom
Sevaux, Marc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-40
marc.sevaux@univ-ubs.fr
UMR 6285 - Lab-STICC - CNRS, Université de Bretagne
Sud, Lorient, France
Sevcovic, Daniel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-24
sevcovic@fmph.uniba.sk
Department of Applied Mathematics and Statistics, Comenius University, Bratislava, Slovakia
Shcherbanin, Yury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-05
shcherbaninya@mail.ru
Transport and Logistics Analyses and Forecasting, Russian
Academy of Sciences, Institute of Economic Forecasting,
Moscow, Russian Federation
Siddiqui, Sauleh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-07
siddiqui@jhu.edu
Johns Hopkins University, Baltimore, MD, United States
Silva, Lino . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-17
ra108980@ime.unicamp.br
Applied Mathematics, UNICAMP/UNIVASF, Petrolina, Pernambuco, Brazil
Sinha, Ankur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-18
ankur.sinha@aalto.fi
Department of Information and Service Economy, Aalto University School of Business, Helsinki, Finland
Slowinski, Roman . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-24
roman.slowinski@cs.put.poznan.pl
Institute of Computing Science, Poznan University of Technology, Poznan, Poland
Seddig, Katrin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-07
k.seddig@ensoc.de
Energy Solution Center e. V., Karlsruhe, Germany
Smidla, József . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-21
smidla@dcs.uni-pannon.hu
Department of Computer Science and Systems Technology,
University of Pannonia, Hungary
Segev, Danny . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-32
segevd@stat.haifa.ac.il
Statistics, University of Haifa, Israel
Sofer, Ariela . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-44
asofer@gmu.edu
SEOR, George Mason University, Fairfax, VA, United States
Segura, Marina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-36
masema@posgrado.upv.es
Applied Statistics, Operations Research and Quality, Universitat Politècnica de València, Valencia, Spain
Soler, Edilaine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-43
edilaine@fc.unesp.br
Departamento de Matemática, Faculdade de Ciências, UNESP - Univ Estadual Paulista, Bauru, SP, Brazil
Sen, Suvrajeet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-45
s.sen@usc.edu
Daniel J. Epstein Dept. of ISE, University of Southern California, Los Angeles, CA, United States
Sörensen, Kenneth . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-23, HA-40
kenneth.sorensen@uantwerpen.be
Faculty of Applied Economics, University of Antwerp,
Antwerpen, Belgium
Şengel, Öznur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-10
o.sengel@iku.edu.tr
Computer Engineering, İstambul Kültür University, İstanbul,
Bakırköy, Turkey
Sosic, Greys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-22, TB-22
sosic@marshall.usc.edu
Marshall School of Business, University of Southern California, Los Angeles, CA, United States
Şenol, Mehmet Burak . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-07
senolmehmet81@hotmail.com
Quality Management Directorate, Turkish Land Forces5.Main Maintenance Center, Ankara, Turkey
Soto, Ricardo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-25
ricardo.soto@ucv.cl
Computer Science, Pontificia Universidad Católica de Valparaíso, Valparaíso, Chile
Seref, Onur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-25
seref@vt.edu
Soufivand, Mona . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-09
m.soufivand@gmail.com
282
IFORS 2014 - Barcelona
University of Palermo, Italy
Sowlati, Taraneh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-38
taraneh.sowlati@ubc.ca
Wood Science, University of British Columbia, Vancouver,
BC, Canada
Speranza, M. Grazia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-06
speranza@eco.unibs.it
Dept. of Quantitative Methods, University of Brescia, Brescia, Italy
Staliński, Piotr . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-19
piotr_stalinski@yahoo.com
Department of Quantitative Methods in Management, WSBNLU, Nowy Sacz,
˛ Poland
Stankovic, Jelena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-29
jelena.stankovic@eknfak.ni.ac.rs
Department of Accounting, Mathematics and Informatics,
University of Nis, Faculty of Economics, Nis, Serbia
Starcevic, Dusan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-32
starcev@fon.rs
Faculty of Organizational Sciences, University of Belgrade,
Belgrade, Serbia
SESSION CHAIR INDEX
suzuki@econ.hokudai.ac.jp
Graduate School of Economics, Hokkaido University, Sapporo, Hokkaido, Japan
Suzuki, Tsutomu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-03
tsutomu@risk.tsukuba.ac.jp
Faculty of Engineeing, Information and Systems, University
of Tsukuba, Tsukuba, Ibaraki, Japan
Tammer, Christiane . . . . . . . . . . . . . . . . . . . . . . . . . . TA-18, TB-18
christiane.tammer@mathematik.uni-halle.de
Mathematics and Computer Science, Martin-LutherUniversity Halle-Wittenberg, Halle, Germany
Tanaka, Tamaki . . . . . . . . . . . . . . . . . . . . . . HA-37, ME-37, TA-37
tamaki@math.sc.niigata-u.ac.jp
Mathematics, Niigata University, Niigata, Niigata, Japan
Tancrez, Jean-Sébastien . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-07
js.tancrez@uclouvain.be
Louvain School of Management, Université catholique de
Louvain, Mons, Belgium
Tangian, Andranik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-24
andranik-tangian@boeckler.de
WSI, Hans Boeckler Foundation, Duesseldorf, Germany
Stecke, Kathryn E. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-27
KStecke@utdallas.edu
University of Texas at Dallas, RICHARDSON, TX, United
States
Taniguchi, Eiichi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-06
taniguchi@kiban.kuciv.kyoto-u.ac.jp
Department of Urban Management, Kyoto University, Kyoto,
Japan
Steiner, Winfried . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-19, TD-19
winfried.steiner@tu-clausthal.de
Marketing, Clausthal University of Technology, Institute of
Management and Economics, Clausthal-Zellerfeld, Germany
Tanino, Tetsuzo . . . . . . . . . . . . . . . . . . . . . . HA-37, ME-37, TA-37
tanino@eei.eng.osaka-u.ac.jp
Division of Electrical, Electronic and Information Engineering, Osaka University, Suita, Osaka, Japan
Steinshamn, Stein Ivar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-36
stein.steinshamn@nhh.no
Department of Business and Management Science, Norwegian School of Economics (NHH), Bergen, Norway
Tavasszy, Lorant . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-06
lori.tavasszy@tno.nl
TU Delft / TNO, Netherlands
Sterna, Malgorzata . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-13
Malgorzata.Sterna@cs.put.poznan.pl
Institute of Computing Science, Poznan University of Technology, Poznan, Poland
Steuer, Ralph E. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-34
rsteuer@uga.edu
Terry College of Business, University of Georgia, Athens,
GA, United States
Stewart, Theodor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-31
Theodor.Stewart@uct.ac.za
Statistical Sciences, University of Cape Town, Rondebosch,
South Africa
Stokic, Dejan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-34, MB-34
sdeyan@gmail.com
DataMain, Frankfurt, Germany
Street, Alexandre. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-10
street@ele.puc-rio.br
Electrical Engineering, Pontifical Catholic University of Rio
de Janeiro (PUC-Rio), Rio de Janeiro, Rio de Janeiro, Brazil
Strugnell, Dave . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-34
dave.strugnell@uct.ac.za
Actuarial Science, University of Cape Town, Rondebosch,
Western Cape, South Africa
Suzuki, Teruyoshi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-30
Taylan, Pakize . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-43, TE-43
pakizetaylan@yahoo.com
Mathematics, Dicle University, Diyarbakır, Turkey
Teghem, Jacques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-14
jacques.teghem@umons.ac.be
MathRO, Faculté Polytechnique/UMonss, Mons, Belgium
Teixeira de Almeida, Adiel . . . . . . . . . . . . . . . . . . . . . . . . . . HD-42
almeidaatd@gmail.com
Management Engineering, Universidade Federal de Pernambuco - UFPE, Recife, PE, Brazil
Terlaky, Tamás . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-17
terlaky@lehigh.edu
Industrial and Systems Engineering, Lehigh University, Bethlehem, Pennsylvania, United States
Teytelboym, Alex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-06
t8el@mit.edu
EECS, MIT, Cambridge, MA, United States
Thanassoulis, Emmanuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-10
e.thanassoulis@aston.ac.uk
Aston Business School, Aston University, Birmingham,
United Kingdom
Thomas, Valerie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-20
valerie.thomas@isye.gatech.edu
Industrial and Systems Engineering, Georgia Institute of
Technology, Atlanta, GA, United States
283
SESSION CHAIR INDEX
IFORS 2014 - Barcelona
Tichý, Tomás . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-34
tomas.tichy@vsb.cz
Department of Finance, Faculty of Economics, VSBTechnical University Ostrava, Ostrava, Czech Republic
Tofallis, Chris . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-32
c.tofallis@herts.ac.uk
Business School, University of Hertfordshire, Hatfield,
Herts., United Kingdom
Tomala, Tristan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-24
tomala@hec.fr
Economics and Decision Sciences, HEC Paris, Jouy en Josas,
France
Tomasgard, Asgeir . . . . . . . . . . . . . . . . . . . MA-07, TD-20, HE-29
asgeir.tomasgard@sintef.no
Applied economics and operations research, Sintef Technology and society, Trondheim, Norway
Tone, Kaoru . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-10
tone@grips.ac.jp
National Graduate Institute for Policy Studies, Tokyo, Japan
Torigoe, Norio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-35
nt1969torigoe@aol.com
TakeThink Inc., Hachioji, Tokyo, Japan
Toth, Paolo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-11
paolo.toth@unibo.it
DEI, University of Bologna, Bologna, Italy
Toyasaki, Fuminori . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-33
toyasaki@yorku.ca
York University, Toronto, Canada
Tragler, Gernot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-07
tragler@eos.tuwien.ac.at
OR and Control Systems, Vienna University of Technology,
Vienna, Austria
Trinks, Christian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-38
christian.trinks@umsicht.fraunhofer.de
Fraunhofer UMSICHT, Germany
Tseng, Hwai-En . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-29
hwai_en@seed.net.tw
Department of Industrial Engineering and Management,
National Chin-Yi University of Technology, Taiping City,
Taichung County, Taiwan
Tsui, Kwok Leung. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-22
kltsui@cityu.edu.hk
City University of Hong Kong, Kowloon, Hong Kong
nas Technical University, Vilnius, Lithuania
Tüzemen, Adem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-43
atuzemen@gmail.com
Business Administration, Tokat Gaziosmanpaşa University,
Faculty of Economics and Administrative Sciences, TOKAT,
Turkey
Ünlüyurt, Tonguc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-39
tonguc@sabanciuniv.edu
Manufacturing Systems/Industrial Engineering, Sabanci University, Ýstanbul, Turkey
Ursavas, Evrim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-05
e.ursavas@rug.nl
Operations, University of Groningen, Netherlands
Vaagen, Hajnalka . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-23
hajnalka.vaagen@sintef.no
Applied Economics and Operations Research, SINTEF,
Trondheim, Norway
Valenzuela, Jorge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-09
jvalenz@eng.auburn.edu
Auburn University, United States
van den Heever, Susara . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-01
svdheever@fr.ibm.com
IBM, France
Van Mieghem, Jan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-22
vanmieghem@kellogg.northwestern.edu
Kellogg School of Management, Northwestern University,
Evanston, IL, United States
van Vuuren, Jan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-11, HE-17
vuuren@sun.ac.za
Department of Industrial Engineering, Stellenbosch University, Stellenbosch, Western Cape, South Africa
Van Vyve, Mathieu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-41
mathieu.vanvyve@uclouvain.be
CORE, UCL, Louvain-la-neuve, – Select –, Belgium
Vanden Berghe, Greet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-13
greet.vandenberghe@cs.kuleuven.be
Computer Science, KU Leuven, Gent, Belgium
Vanhoucke, Mario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-12
mario.vanhoucke@ugent.be
Faculty of Economics and Business Administration, Ghent
University, Vlerick Business School, University College London, Ghent, Belgium
Tuncer Sakar, Ceren . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-18
cerents@hacettepe.edu.tr
Industrial Engineering, Hacettepe University, Ankara, Turkey
Vargas-Parra, M. Violeta . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-14
mariavioleta.vargas@uab.cat
Institute of Environmental Science and Technology (ICTA),
Universitat Autonoma de Barcelona, Barcelona, Barcelona,
Spain
Turner, John . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-15
john.turner@uci.edu
Paul Merage School of Business, UC-Irvine, Irvine, CA,
United States
Venel, Xavier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-24
xavier.venel@gmail.com
Department of Statistics and Operations Research, Tel aviv
University, Tel aviv, Israel
Turrini, Laura . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-32
laura.turrini@the-klu.org
Logistics, Kühne Logistics University, Hamburg, Germany
Verago, Rudi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-35
rudi.verago@ie.ibm.com
IBM, Dublin, Ireland
Turskis, Zenonas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-45
zenonas.turskis@vgtu.lt
Construction Technology and Management, Vilnius Gedimi-
Verleye, Derek . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-43
derek.verleye@ugent.be
Industrial Management, Ghent University, Zwijnaarde, Bel-
284
IFORS 2014 - Barcelona
gium
Vianna, Andréa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-21
vianna@fc.unesp.br
Computation, UNESP - Bauru, Bauru, São Paulo, Brazil
Vierhaus, Ingmar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-28
vierhaus@zib.de
Optimization, Zuse Institute Berlin, Berlin, Germany
Villas-Boas, Sergio B. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-11
sbvb@sbvb.com.br
PESC, Ufrj / Coppe, Rio de Janeiro, Rio de Janeiro, Brazil
Villumsen, Jonas Christoffer . . . . . . . . . . . . . . . . . . . . . . . . . FA-35
jonasvil@ie.ibm.com
IBM Research, Dublin, Ireland
Villwock, Rosangela . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-32
rosangelamat@hotmail.com
Universidade Estadual do Oeste do Paraná, Brazil
Vilutiene, Tatjana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-45
tatjana.vilutiene@vgtu.lt
Department of Construction Technology and Management,
Vilnius Gediminas Technical University, Vilnius, Lithuania
Vis, Iris F.A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-05
i.f.a.vis@rug.nl
Faculty of Economics and Business, Dep. of Operations,
University of Groningen, Groningen, Netherlands
Visagie, Stephan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-11
svisagie@sun.ac.za
Department of Logistics, University of Stellenbosch, Stellenbosch, South Africa
Vitoriano, Begoña. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-37
bvitoriano@mat.ucm.es
Estadística e Investigación Operativa I, Fac. Matemáticas,
Universidad Complutense de Madrid, Madrid, Spain
Vlachos, Dimitrios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-35
vlachos1@auth.gr
Mechanical Engineering, Aristotle University of Thessaloniki, Thessaloniki, Greece
SESSION CHAIR INDEX
PROS, Houston, United States
Wall, Friederike . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-44
friederike.wall@uni-klu.ac.at
Dept. for Controlling and Strategic Management, AlpenAdria-Universitaet Klagenfurt, Klagenfurt, Austria
Walther, Ursula . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-30
ursula.walther@hwr-berlin.de
Fb 1, Berlin School of Economics and Law, Berlin, Germany
Wan, Cheng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-28
cheng.wan@economics.ox.ac.uk
Economics, University of Oxford, Oxford, United Kingdom
Wan, Xiangwei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-29
xwwan@sjtu.edu.cn
Antai College of Economics and Management, Shanghai Jiao
Tong University, Shanghai, China
Wang, Cara . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-06
wangx18@rpi.edu
Civil and Environmental Engineering, Rensselaer Polytechnic Institute, Troy, New York, United States
Wang, Shin-Yun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-34
gracew@mail.ndhu.edu.tw
Department of Finance, National Dong Hwa University, Taiwan
Wassan, Niaz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-45
N.A.Wassan@ukc.ac.uk
Canterbury Business School, University of Kent, Canterbury,
Kent, United Kingdom
Watanabe, Takahiro. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-35
contact_nabe08@nabenavi.net
Graduate School of Social Sciences, Tokyo Metropolitan
University, Tokyo, Japan
Weber, Christoph . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-07
Christoph_Weber@uni-duisburg-essen.de
Universität Essen, Essen, Germany
Volkovich, Zeev (Vladimir) . . . . . . . . . . . . . . . . . . . . . . . . . MA-35
zeev@actcom.co.il
Ort Braude Academic College, Karmiel, Israel
Weber, Gerhard-Wilhelm . . . . . . . . . . . . . . . . . . . . . . . . . . MA-09,
TD-11, MD-17, ME-17, ME-27, TD-28, MA-30, MD-32,
FA-35, FB-36, HD-39, HE-44, TB-44, TD-44, HC-50
gweber@metu.edu.tr
Institute of Applied Mathematics, Middle East Technical
University, Ankara, Turkey
von Mettenheim, Hans-Jörg . . . . . . . . . . . . . . . . . . . . . . . . MD-26
mettenheim@iwi.uni-hannover.de
Leibniz Universität Hannover, Institut für Wirtschaftsinformatik, Hannover, Germany
Weber, Richard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-25
rweber@dii.uchile.cl
Department of Industrial Engineering, University of Chile,
Santiago, Chile
Voss, Stefan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-40, HE-40
stefan.voss@uni-hamburg.de
Wirtschaftsinformatik/Information Systems, University of
Hamburg, Hamburg, Germany
Weber, Valentin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-03
valentin.weber@amadeus.com
Operations Research, Amadeus sas, Sophia Antipolis Cedex,
France, France
Vujosevic, Mirko . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-04
mirkov@fon.bg.ac.rs
Faculty of Organizational Sciences, University of Belgrade,
Belgrade, Serbia
Weglarz, Jan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-12
jan.weglarz@cs.put.poznan.pl
Institute of Computing Science, Poznan University of Technology, Poznan, Poland
Waitz, Martin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-27
mwaitz@wu.ac.at
WU Vienna, Austria
Weintraub, Andrés . . . . . . . . . . MA-20, MB-20, MD-20, TA-36
aweintra@dii.uchile.cl
Industrial engineering, University of Chile, Santiago, Chile
Walczak, Darius . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-15
dwalczak@pros.com
Welling, Andreas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-08
andreas.welling@ovgu.de
285
SESSION CHAIR INDEX
IFORS 2014 - Barcelona
Faculty of Economics and Management, LS Financial Management and Innovation Finance, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
Wensing, Thomas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-19
wensingt@web.de
INFORM GmbH, Aachen, NRW, Germany
Wenstøp, Fred . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-24
fred.wenstop@bi.no
Strategy and Logistics, BI Norwegian Business School, Oslo,
Norway
Werners, Brigitte . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-39
or@rub.de
Fac. of Management and Economics, Ruhr University
Bochum, Bochum, Germany
White, Leroy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-23, HB-38
leroy.white@bris.ac.uk
Management Department, University of Bristol, Bristol,
United Kingdom
Wright, Mike . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-10
m.wright@lancaster.ac.uk
The Management School, Lancaster University, Lancaster,
Lancashire, United Kingdom
Wu, Cheng-Lung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-03
c.l.wu@unsw.edu.au
Aviation, UNSW Australia, Sydney, NSW, Australia
Wu, Chien-Wei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-27
cweiwu@ie.nthu.edu.tw
Department of Industrial Engineering and Engineering Management, National Tsing Hua University, HsinChu, Taiwan
Wu, Qi. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-29
qwu@se.cuhk.edu.hk
The Chinese University of Hong Kong, Hong Kong, Hong
Kong
Wu, Shining . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-15
shiningwu@ust.hk
Department of Industrial Engineering and Logistics Management, The Hong Kong University of Science and Technology,
Hong Kong, Hong Kong
Xu, Di . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-27
dxu@xmu.edu.cn
Management Science, Xiamen University, Xiamen, China
Xu, Jianjun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-37
jxu@zlc.edu.es
Zaragoza Logistics Center(ESG50985993), Zaragoza,
Zaragoza, Spain
Yakıt Ongun, Mevlüde . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-12
mevludeyakit@sdu.edu.tr
Mathematics, Süleyman Demirel University, Isparta, Turkey
Yalaoui, Alice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-40
alice.yalaoui@utt.fr
ROSAS, UTT, Troyes, France
Yalaoui, Farouk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-40
farouk.yalaoui@utt.fr
Institut Charles Delaunay, ICD LOSI, University of Technology of Troyes, Troyes, France
Yamada, Takako . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-30
takakoyamada@kwansei.ac.jp
286
School of Policy Studies, Kwansei Gakuin University, Sandashi, Hyougo, Japan
Yapıcı Pehlivan, Nimet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-39
nimet@selcuk.edu.tr
Statistics, Selcuk University, Konya, Turkey
Yau, Kelvin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-22
mskyau@cityu.edu.hk
Department of Management Sciences, City University of
Hong Kong, Hong Kong
Yildirak, Kasirga . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-42
kasirgayildirak@gmail.com.tr
IAM, METU, Ankara, Turkey
Yılmaz, Hafize . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-27
hafizeyilmaz@halic.edu.tr
Industrial Engineering, Halic University, İstanbul, Turkey
Yuan, Xiaoming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-38, TD-38
xmyuan@hkbu.edu.hk
Department of Mathematics, Hong Kong Baptist University,
Kowloon Tong, Hong Kong
Yuan, Yaxiang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-38, TE-38
yyx@lsec.cc.ac.cn
Institute of Computational Mathematics, Chinese Academy
of Sciences, Beijing, China
Yunusoglu, Mualla Gonca . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-27
gonca.yunusoglu@deu.edu.tr
Industrial Engineering, Dokuz Eylul University, Turkey
Zaslavski, Alexander . . . . . . . . . . . . . . . . MA-25, MB-25, MD-25
ajzasl@techunix.technion.ac.il
Technion, Haifa, Israel
Zenios, Stavros A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-43
zenioss@ucy.ac.cy
University of Cyprus, Nicosia, Cyprus
Zhang, Rachel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-15
rzhang@ust.hk
IELM, Hong Kong UST, Kowloon, Hong Kong
Zhou, Zhili . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-31
zhili@sg.ibm.com
IBM Research Collaboratory, Singapore, IBM Research, Singapore
Zhuang, Weifen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-39
wfzhuang@xmu.edu.cn
School of Management, Xiamen University, Xiamen, Fujian,
China
Zilinskas, Julius . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-18, TE-18
julius.zilinskas@mii.vu.lt
Institute of Mathematics and Informatics, Vilnius University,
Vilnius, Lithuania
Zimmermann, Jürgen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-12
juergen.zimmermann@tu-clausthal.de
Operations Research, TU Clausthal, Clausthal-Zellerfeld,
Germany
Zinder, Yakov . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-12
yakov.zinder@uts.edu.au
Department of Mathematical Sciences, University of Technology, Sydney, Sydney, NSW, Australia
Zografidou, Eleni . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-08
IFORS 2014 - Barcelona
ezografi@fmenr.duth.gr
Forestry and Management of the Environment and Natural Resourses, Democritus University of Thrace, Orestiada,
Greece
Zuidwijk, Rob . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-15
rzuidwijk@rsm.nl
SESSION CHAIR INDEX
Decision and Information Sciences, RSM Erasmus University, Rotterdam, Netherlands
Zuluaga, Luis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-16
lzuluagag@gmail.com
Industrial and Systems Engineering, Lehigh University,
United States
287
Author Index
Boukredera, Djamila . . . . . . . . . . . . . . . . . . MB-23, ME-29
boukredera@hotmail.com
Laboratoire LMA, University of bejaia, Bejaia, Algeria
ico, Distrito Federal, Mexico
Acuna Agost, Rodrigo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-03
rodrigoacunaagost@hotmail.com
Operations Research, Amadeus, Nice, France
A. S. Castro, Ricardo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-14
ricardo.alves.castro@fe.up.pt
Faculdade de Engenharia, Universidade do Porto, Portugal
Adachi, Koichi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-09
adachi@al.ics.saitama-u.ac.jp
Faculty of Engineering, Saitama University, Japan
Álvarez-Miranda, Eduardo . . . . . . . . . . . TB-11, HB-31, HE-31
ealvarez@utalca.cl
DMGI, Universidad de Talca, Curicó, Italy
Adams, Elspeth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-17
elspeth.adams@polymtl.ca
Polytechnique Montreal, Montreal, Canada
Aardal, Karen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-09
K.I.Aardal@tudelft.nl
Delft Institute of Applied Mathematics, Technische Universiteit Delft, Delft, Netherlands
Addas Porto, Natália . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-08
natalia@fem.unicamp.br
Energy Department, University of Campinas, Campinas, Sao
Paulo, Brazil
Ávila, Thais . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-02
thais.avila@uv.es
Statistics and Operations Research, University of Valencia,
Burjassot, Spain
Adebiyi, Olanrewaju Sulaimon . . . . . . . . . . . . . . . . . . . . . MA-37
lanre18april@gmail.com
Department of Business Administration,College of Management Sciences, Federal University of Agriculture, Abeokuta,
Ogun, Nigeria, Abeokuta, Ogun, Nigeria
Aïssani, Djamil . . . . . . . . . . . . . . . . . . . . . . . FA-31, FB-31, HA-35
lamos_bejaia@hotmail.com
Department of Operation Research, University of Bejaia, Bejaia, Algeria
Abad, Carlos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-20
ca2446@columbia.edu
Industrial Eng. and Operations Research Dept., Columbia
University, New York, NY, United States
Abdelouahab, Zaghrouti . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-43
Abdelouahab.Zaghrouti@gerad.ca
MAGI, Polytechnique, Montréal, Québec, Canada
Abgottspon, Hubert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-20
abgottspon@eeh.ee.ethz.ch
Power Systems Laboratory, ETH Zurich, Zurich, Zurich,
Switzerland
Abraham, Matan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-45
matanabraham@gmail.com
Actuarial Science, University of Cape Town, Cape Town,
Western Cape, South Africa
Abrahams, Alan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-25
abra@vt.edu
Virginia Tech, Blacksburg, VA, United States
Adekoya, Adebola . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-37
agadekoya@unilag.edu.ng
Business Administration, University of Lagos, Akoka, Yaba,
Lagos, Nigeria
Adelman, Daniel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-20
daniel.adelman@chicagobooth.edu
Booth School of Business, University of Chicago, Chicago,
IL, United States
Adelman, Dan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-15
dan.adelman@chicagoGSB.edu
Booth School of Business, University of Chicago, Chicago,
IL, United States
Adida, Elodie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-32
elodie.goodman@ucr.edu
School of Business Administration, University of California
at Riverside, United States
Aduenko, Alexander . . . . . . . . . . . . . . . . . . . . . . . . . HB-16, TE-16
aduenko1@gmail.com
Department of Control and Applied Mathematics, Moscow
Institute of Physics and Technology, Dolgoprudny, Russian
Federation
Abreu, Ana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-45
anacristina.abreu@hotmail.com
UFRJ, Rio de Janeiro, Brazil
Adulyasak, Yossiri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-41
yossiri@smart.mit.edu
Singapore - MIT Alliance for Research and Technology, Mit
- Smart, Singapore, Singapore
Abril Bucero, Marta. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-16
marta.abril_bucero@inria.fr
Inria Sophia Antipolis, France
Advani, Jai . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-23
jai.advani@accenture.com
Accenture, Bangalore, India
Açar, Ertürk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-29
eracar@ku.edu.tr
Industrial Engineering, Koç University, Istanbul, Turkey
Afsar, Sezin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-15
sezin.afsar@inria.fr
Dolphin, Inria Lille Nord Europe, LILLE, France
Acevedo, Andrés . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-37
acevedo83@gmail.com
Mechanical and Industrial Engineering, Concordia University, Montreal, Quebec, Canada
Afsharian, Mohsen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-10
m.afsharian@tu-braunschweig.de
Institute of Management Control and Business Accounting,
Technische Universität Braunschweig, Braunschweig, Germany
Aceves-García, Ricardo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-03
aceves@unam.mx
Sistemas, Universidad Nacional Autónoma de México, Méx-
288
Agell, Nuria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-42, TE-45
nuria.agell@esade.edu
IFORS 2014 - Barcelona
Information Systems Management, ESADE-URL, Spain
Ager, Alan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-36
aager@fs.fed.us
Western Wildland Environmental Threat Assessment Center,
USDA Forest Service, Pacific Northwest Research Station,
Prineville, Oregon, United States
Aghezzaf, El-Houssaine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-43
ElHoussaine.Aghezzaf@UGent.be
Industrial Management, Ghent University, Zwijnaarde, Belgium
Agra, Agostinho . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-05, MB-41
aagra@ua.pt
Matemática, Universidade de Aveiro, Aveiro, Portugal
Agrali, Semra . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-08
semra.agrali@gmail.com
Industrial Engineering, Bahcesehir University, Istanbul,
Turkey
Agrawal, Tinu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-40
tagrawal@imtnag.ac.in
Faculty Research Associate, IMT, Nagpur, Nagpur, MS, India
Aguayo, Ernesto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-31
ea.aguayo@upm.es
Technical University of Madrid, Madrid, Spain
Ahmed, Shabbir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-45
sahmed@isye.gatech.edu
School of Industrial & Systems Engineering, Georgia Tech,
Atlanta, Georgia, United States
Ahn, Heinz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-10
hw.ahn@tu-bs.de
Institut für Controlling und Unternehmensrechnung, TU
Braunschweig, Braunschweig, Germany
Ahn, Sejung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-16
sjahn@kisti.re.kr
Korea Institute of Science and Technology Information,
Seoul, Korea, Republic Of
Ait Haddadene, Hacene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-16
aithaddadenehacene@yahoo.fr
Faculty of Mathematics, Dept of Operations research,
USTHB University, Algiers, Algeria
Akartunali, Kerem . . . . . . . . . . . . . . . . . . . . . . . . . . TE-20, MB-41
kerem.akartunali@strath.ac.uk
Management Science, University of Strathclyde, Glasgow,
United Kingdom
Akdoğan, Yunus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-43
yakdogan@selcuk.edu.tr
Statistics Department, Science Faculty, Selcuk University,
Konya, Turkey
Akhavan-Tabatabaei, Raha . . . . . . . . . . . . . . . . . . . . . . . . . MA-22
r.akhavan@uniandes.edu.co
Departamento de Ingeneria Industrial, Universidad de los
Andes, Bogota, Colombia
Akkan, Can . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-10
canakkan@sabanciuniv.edu
School of Management, Sabanci University, Istanbul, Turkey
Akkerman, Renzo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-08
renzo.akkerman@tum.de
TUM School of Management, Technische Universität
AUTHOR INDEX
München, Munich, Germany
Akman Biyik, Ceren . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-27
cerenakman@gmail.com
Business Administration, Dokuz Eylul University / Turkiye,
Izmir, Turkey
Akoglu, Leman . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-25
lemanakoglu@gmail.com
Stony Brook University, Stony Brook, New York, United
States
Akpinar, Mustafa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-09
akpinar@sakarya.edu.tr
Computer Engineering, University of Sakarya, Sakarya,
Turkey
Aksakal, Erdem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-29
eaksakal@gazi.edu.tr
Industrial Engineering, Gazi University, Ankara, Turkey
Aksen, Deniz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-23
daksen@ku.edu.tr
College of Administrative Sciences and Economics, Koç University, Istanbul, Turkey
Aksin, Zeynep . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-15
zaksin@ku.edu.tr
Graduate School of Business, Koc University, Istanbul,
Turkey
Aktan, Mert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-35
mertaktan34@gmail.com
Business Administration, Cankiri Karatekin University,
CANKIRI, Turkey
Aktas, Ahmet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-14
aaktas@gazi.edu.tr
Department of Industrial Engineering, Gazi University,
Ankara, Turkey
Aktin, Tülin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-43
t.aktin@iku.edu.tr
Industrial Engineering Department, Istanbul Kültür University, Istanbul, Turkey
Al-Salem, Ameer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-21
ameer@qu.edu.qa
Department of Mechanical and Industrial Engineering, Qatar
University, Doha, Qatar, Qatar
Alabert, Aureli . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-21
Aureli.Alabert@uab.cat
Mathematics, Universitat Autònoma de Barcelona, Bellaterra, CATALONIA, Spain
Alagoz, Ali . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-04
aalagoz@selcuk.edu.tr
Faculty of Business Administration, Selcuk University,
Turkey
Alarcón-Bernal, Zaida Estefanía . . . . . . . . . . . . . . . . . . . . . FB-27
zaida_eab@comunidad.unam.mx
Sistemas, Universidad Nacional Autónoma de México, México, Distrito Federal, Mexico
Albareda Sambola, Maria . . . . . . . . . . . . . . . . . . . HB-03, HA-31
maria.albareda@upc.edu
Statistics and Operations Research, Technical University of
Catalonia, Terrassa, Spain
Albores, Pavel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-37, HA-38
289
AUTHOR INDEX
IFORS 2014 - Barcelona
p.albores@aston.ac.uk
Operations and Information Management, Aston Business
School, Birmingham, United Kingdom
Albornoz, Victor M. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-07
victor.albornoz@usm.cl
Departamento de Industrias, Universidad Tecnica Federico
Santa Maria, Santiago, Chile
Albu, Alla . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-09
alla.albu@mail.ru
Applied Optimization Problems, Institution of Russian
Academy of Sciences Dorodnicyn Computing Centre of
RAS, Moscow, Russian Federation
Albuquerque, Jones . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-41
jones.albuquerque@gmail.com
Statistics and Informatics, Ufrpe - Ines, Recife, Pernambuco,
Brazil
Alcaraz, Javier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-03
jalcaraz@umh.es
Dept. Estadística, Matemáticas e Informática, Universidad
Miguel Hernández de Elche, Elche, Alicante, Spain
Aldasoro, Unai . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-45
unai.aldasoro@ehu.es
Matemática Aplicada, University of the Basque Country
UPV/EHU, Eibar, Gipuzkoa, Spain
IOEC, Tehran, Iran, Islamic Republic Of
Alibeyg, Armaghan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-03
a_alibey@encs.concordia.ca
Mechanical and Industrial, Concordia University, Montreal,
Quebec, Canada
Aliefendioğlu, Kaan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-21
kaan.aliefendioglu@gmail.com
Industrial Engineering, Istanbul Kültür University, Istanbul,
Turkey
Allamigeon, Xavier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-24
xavier.allamigeon@inria.fr
INRIA and CMAP, Ecole Polytechnique, Palaiseau, France
Allaoui, Hamid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-19
hamid.allaoui@univ-artois.fr
University of Artois, Arras, France
Allen, Dave . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-23
dave.allen1@verizon.com
Business Analytics, Verizon, United States
Allowh, Ghada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-21
ka1003365@qu.edu.qa
Mechanical and Industrial Engineering, Qatar University,
Doha, Qatar, Qatar
Alegoz, Mehmet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-18
mehmetalegoz@anadolu.edu.tr
Industrial Engineering, Anadolu University, Turkey
Almada-Lobo, Bernardo . . . . . MB-04, FA-06, MA-41, MD-41
almada.lobo@fe.up.pt
Industrial Engineering and Management, Faculty of Engineering of Porto University, Porto, Portugal
Aleman, Dionne . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-25
aleman@mie.utoronto.ca
Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada
Almeder, Christian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-41
Almeder@europa-uni.de
Chair for Supply Chain Management, European University
Viadrina, Frankfurt (Oder), Germany
Alessi, Marco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-09
Alessi@eng.it
Engineering Ingegneria Informatica SPA., Palrmo, Italy
Almeida, Jonatas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-42
jonatasaa@yahoo.com.br
Universidade Federal de Pernambuco, Recife, Brazil
Alfakih, Abdo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-11
alfakih@uwindsor.ca
Mathematics and Statistics, University of Windsor, Windsor,
Ontario, Canada
Almeida-Filho, Adiel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-42
atalmeidafilho@yahoo.com.br
Management Engineering, Universidade Federal de Pernambuco, Recife, PE, Brazil
Alfandari, Laurent . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-15, FA-36
alfandari@essec.fr
ESSEC Business School, Cergy-Pontoise Cedex, France
Alonso Martínez, Maria Teresa . . . . . . . . . . . . . . . . . . . . . . HD-21
mariateresa.alonso@uclm.es
Department of mathematics, University of Castilla-La Mancha, Albacete, Spain
Algaba Birba, Oriol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-05
oalgaba@gmail.com
DTU, Denmark
Alguacil-Conde, Natalia . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-07
Natalia.Alguacil@uclm.es
Electrical Engineering, University of Castilla-La Mancha,
Ciudad Real, Ciudad Real, Spain
Ali, Montaz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-14
Montaz.Ali@wits.ac.za
University of Witwatersrand, Johannesburg, South Africa
Ali, Sadia Samar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-44
sadiasamarali@gmail.com
Operations Management, Fortune Institute of International
Business , New Delhi - 110057, India, New Delhi, India
Aliakbari, Arash . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-36
arashaliakbari@yahoo.com
290
Alonso-Ayuso, Antonio . . . . . . . . . . . . . . . HB-11, HA-20, HE-28
antonio.alonso@urjc.es
Statistics & Operations Research Department, Rey Juan Carlos University, Mostoles, Madrid, Spain
Alos, Dennise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-36
DENNIS.ALOS@roquette.com
Purchasing department, Roquette Laisa España, BenifaióValencia, Spain
Aloui, Abdelouhab . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-12
aaloui_abdel@yahoo.fr
Computer Science, University of Bejaia, Bejaia, Algeria
Alp, Osman . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-19
osmanalp@bilkent.edu.tr
Bilkent University, Ankara, Turkey
Alparslan Gok, Sirma Zeynep . . . . . . . . . . . . . . . . . . . . . . . HA-30
IFORS 2014 - Barcelona
zeynepalparslan@yahoo.com
Mathematics, Faculty of Arts and Sciences, Suleyman
Demirel University, Isparta, Turkey
Alpaslan, Melis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-02, TE-02
melisalpaslan@gmail.com
Industrial Engineering, Anadolu University, Eskişehir,
Turkey
Alshahrani, Mohammed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-26
mshahrani@kfupm.edu.sa
Mathematics and Statistics, King Fahd University of
Petroleum and Minerals (KFUPM), DHAHRAN, Other,
Saudi Arabia
AUTHOR INDEX
Amado, Carla . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-14, TB-14
camado@ualg.pt
Faculdade de Economia, Universidade do Algarve, Faro, Portugal
Amand, Guillaume . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-13
guillaume.amand@ulg.ac.be
HEC-Ulg, University of Liège, Liège, Belgium
Amar, A. D. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-34
amaramar@shu.edu
Management Department, Seton Hall University, South Orange, NJ, United States
Alshami, Mhd Hani . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-10
m.alshami@lancaster.ac.uk
The Management School, Lancaster University, United Kingdom
Amaro, Ana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-44
aamaro@iscac.pt
Applied Mathematics and Informatics, Iscac/ Ipc, Coimbra,
Portugal
Altan, Basak . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-27
basak.altan@ozyegin.edu.tr
Economics, Ozyegin University, Istanbul, Turkey
Ambrosino, Daniela . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-05
ambrosin@economia.unige.it
DIEM, University of Genova, Genova, Italy
Altay, Ayca . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-41
aycaaltay@yahoo.com
Industrial Engineering Department, Istanbul Technical University, Istanbul
Amedee-Manesme, Charles-Olivier . . . . . . . . . . . . . . . . . . TD-34
charles-olivier.amedee-manesme@fsa.ulaval.ca
Finance, Insurance and Real Estate, Laval Université, Quebec, QC, Canada
Altekin, F. Tevhide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-04
altekin@sabanciuniv.edu
Sabanci School of Management, Sabanci University, Istanbul, Turkey
Amen, Matthias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-43, TB-43
Matthias.Amen@web.de
Chair for Quantitative Accounting & Financial Reporting,
University of Bielefeld, Bielefeld, Germany
Altherr, Lena . . . . . . . . . . . . . . . . . . . . . . . . FA-08, TB-21, MA-43
lena.altherr@fst.tu-darmstadt.de
Chair of Fluid Systems, Technische Universität Darmstadt,
Darmstadt, Germany
Amjed, Tayyab . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-32
tayyab.amjed@students.mq.edu.au
Macquarie Graduate School of Management, Sydney, NSW,
Australia
Altindag, Ilkay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-39
ialtindag@selcuk.edu.tr
Statistics, Selçuk University, Konya, Turkey
Amodeo, Lionel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-13, MD-40
lionel.amodeo@utt.fr
Charles Delaunay Institute, University of Technology of
Troyes, Troyes, France
Altun, Adem Alparslan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-18
a_altun@hotmail.com
Computer Systems Education, Selcuk University Technical
Education Faculty, Turkey
Alumur, Sibel A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-03
salumur@etu.edu.tr
Industrial Engineering Department, TOBB University of Economics and Technology, Ankara, Turkey
Alvarez, María Jesús . . . . . . . . . . . . . . . . . . . . . . . . TB-08, MD-41
mjalvarez@tecnun.es
Organziación Industrial, TECNUN Universidad de Navarra,
San Sebastián, Gipuzcua, Spain
Alvarez-Valdes, Ramon . . . . . . . . . . . . . . HB-05, HA-21, HD-21
ramon.alvarez@uv.es
Statistics and Operations Research, University of Valencia,
Burjassot, Spain
Alves de Carvalho, Leonardo . . . . . . . . . . . . . . . . . . . . . . . . HB-34
lac_carvalho@hotmail.com
Instituto de Engenharia de Produção e Gestão, Universidade
Federal de Itajubá, Itajubá, Minas Gerais, Brazil
Alves, Daniel. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-41
daniel.fsalves@gmail.com
PESC/COPPE, Universidade Federal do Rio de Janeiro, Rio
de Janeiro, RJ, Brazil
Amole, Bilqis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-37
amolebb@gmail.com
Department of Business Administratio, University of Lagos,
Akoka. Lagos Nigeria, Lagos, Lagos, Nigeria
Amorim, Pedro . . . . . . . . . . . . . . . . . . . . . . MB-04, FA-06, MA-41
amorim.pedro@fe.up.pt
Industrial Engineering and Management, Faculty of Engineering of University of Porto, Porto, Portugal
Ampountolas, Konstantinos . . . . . . . . . . . . . . . . . . . . . . . . . HA-04
konstantinos.ampountolas@glasgow.ac.uk
School of Engineering, University of Glasgow, United Kingdom
Amrouche, Salima . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-18
Amrouchesalima@yahoo.fr
Dpt of Operations Research, Faculty of Mathematics, BabEzzouar, Algiers, Algeria
Amroun, Kamal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-12
k_amroun25@yahoo.fr
Sciences computer, University of Bejaia, Bejaia, Algeria
An, Daewoong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-34
daewoong.an@sk.com
SK Hynix, DRAM Development Division, Icheon,
Gyeonggi-do, Korea, Republic Of
291
AUTHOR INDEX
IFORS 2014 - Barcelona
Anderluh, Alexandra . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-33
alexandra.anderluh@wu.ac.at
Vienna University of Economics and Business (WU), Vienna,
Austria
Anderson, Edward . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-20
edward.anderson@sydney.edu.au
University of Sydney Business School, University of Sydney,
Sydney, NSW, Australia
Andersson, Göran . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-20, TB-20
andersson@eeh.ee.ethz.ch
Power Systems Laboratory, Zurich, Switzerland
Andersson, Henrik . . . . . . . . . . . . HA-05, TB-05, TE-05, ME-35
Henrik.Andersson@iot.ntnu.no
Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology,
Trondheim, Norway
versity of Athens, Zografou, Athens, Greece
Angulo-Meza, Lidia . . . . . . . . . . . . . . . . . . . . . . . . . HD-10, TD-14
lidia_a_meza@pq.cnpq.br
Production Engineering, Universidade Federal Fluminense,
Volta Redonda, Rio de Janeiro, Brazil
Anily, Shoshana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-22
anily@post.tau.ac.il
Faculty of Management, Tel Aviv University, Tel Aviv, Israel
Anjos, Miguel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-02, TE-17
anjos@stanfordalumni.org
Mathematics and Industrial Engineering & GERAD, Polytechnique Montreal, Montreal, Quebec, Canada
Ano, Katsunori . . . . . . . . . . . . . . ME-09, MB-30, MD-30, TA-30
k-ano@shibaura-it.ac.jp
Mathematical Sciences, Shibaura Institute of Technology,
Saitama-shi, Saitama-ken, Japan
Andersson, Jonas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-20
jonas.andersson@nhh.no
Finance and Management Science, Norwegian School of
Economics and Business Administration, Bergen, Norway
Ansell, Jake . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-34
J.Ansell@ed.ac.uk
Business Studies, The University of Edinburgh, Edinburgh,
United Kingdom
Andrade, Tiago . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-29
tiago-andrade-2@hotmail.com
Industrial Engineering, Puc - Rio, Rio de Janeiro, Rio de
janeiro, Brazil
Antioco, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-42
Michael.ANTIOCO@edhec.edu
EDHEC Business School, Roubaix, France
Andrade-Campos, António . . . . . . . . . . . . . . . . . . . . . . . . . . HE-43
gilac@ua.pt
University of Aveiro, Aveiro, Portugal
Antunes, Carlos Henggeler . . . . . . . . . . . . . . . . . . HD-09, HB-38
ch@deec.uc.pt
DEEC, University of Coimbra and INESC Coimbra, Coimbra, Portugal
André, Jean . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-29
jean.andre@airliquide.com
Applied Mathematics-Operations Research Team, Air Liquide, Les Loges en Josas, France
Aoudia-Rahmoune, Fazia . . . . . . . . . . . . . . . . . . . . TA-25, HA-35
foufourah@yahoo.fr
Operational Research, Laboratory LAMOS University of Bejaia, Bejaia, Algeria
Andreeva, Galina . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-34, TE-34
Galina.Andreeva@ed.ac.uk
Business School, University of Edinburgh, Edinburgh, United
Kingdom
Apanaviciene, Rasa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-45
rasa.apanaviciene@ktu.lt
Dept of Civil Engineering Technologies, Kaunas University
of Technology, Kaunas, Lithuania
Andretta, Marina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-21
andretta@icmc.usp.br
Icmc - Usp, São Carlos, São Paulo, Brazil
Aparajita, Upali . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-20
upali11@yahoo.com
Anthropology, Utkal University, Bhubaneswar, ORISSA, India
Andrianesis, Panagiotis . . . . . . . . . . . . . . . . . . . . . . HE-09, HB-22
pandrianesis@hotmail.com
Mechanical Engineering, University of Thessaly, Volos,
Greece
Andronikidis, Andreas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-23
andro@uom.gr
Business Administration, University of Macedonia, THESSALONIKI, Greece
Aneja, Yash . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-31
aneja@uwindsor.ca
Odette School of Business, University of Windsor, Windsor,
Ontario, Canada
Angelo, Simone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-22
simonealdrey@yahoo.com.br
Operational Research, Federal University of Rio de Janeiro UFRJ, Angra dos Reis, Rio de Janeiro, Brazil
Angelopoulos, Dimitrios . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-34
dangel@epu.ntua.gr
Electrical & Computer Engineering, National Technical Uni-
292
Appa, Gautam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-12
g.appa@lse.ac.uk
Management, London School of Economics, London, United
Kingdom
Apuli, Bernard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-20
blapuli@yahoo.com
ALTERPLAN, Quezon City, Philippines
Araújo, Eliseu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-11
araujo.eliseu28@gmail.com
UNIFESP, São José dos Campos, São Paulo, Brazil
Araújo, Maria Madalena . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-27
mmaraujo@dps.uminho.pt
Minho’s University, Portugal
Araújo, Olinto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-10
olinto@densis.fee.unicamp.br
CTISM, Universidade Federal de Santa Maria, Brazil
Arabatzis, Garyfallos . . . . . . . . . . . . . . . . . . . . . . . ME-08, MD-38
IFORS 2014 - Barcelona
garamp@fmenr.duth.gr
Forestry and Management of the Environment and Natural Resourses, Democritus University of Thrace, Orestiada,
Greece
Aragüés, Mònica . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-10
monica.aragues@citcea.upc.edu
Electrical Engineering, CITCEA-UPC, Spain
Arampantzi, Christina. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-06
fmem11005@fme.aegean.gr
Department of Financial & Management Engineering, University of the Aegean, Greece
Aranda Pinilla, Johan Alexander . . . . . . . . . . . . . . . . . . . MD-04
jaaranda@ucatolica.edu.co
Industrial Engineering, Universidad Católica de Colombia,
Bogotá, Colombia
Arango, Santiago . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-15
saarango@unal.edu.co
Universidad Nacional de Colombia, Medellín, Colombia
Aras, Necati . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-23
necati.aras@mcgill.ca
Faculty of Management, McGill University, Canada
Araujo Munhoz, Pablo Luiz . . . . . . . . . . . . . . . . . . . . . . . . MD-43
pablo.munhoz@gmail.com
LIA, Université d’Avignon et des Pays de Vaucluse, Avignon,
France
Archetti, Claudia . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-06, HB-45
archetti@eco.unibs.it
Department of Quantitative Methods, University of Brescia,
Brescia, Italy
Arda, Yasemin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-02, TE-13
Yasemin.Arda@ulg.ac.be
HEC Management School, University of Liège, Liège, Belgium
Ardalan, Ali . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-40
aardalan@odu.edu
College of Business and PA, Old Dominion University, Norfolk, VA, United States
Arenas-Parra, Mar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-26
mariamar@uniovi.es
Economía Cuantitativa, Universidad de Oviedo, Oviedo, Asturias, Spain
Arentze, Theo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-32
T.A.Arentze@tue.nl
TU/e, Eindhoven, Netherlands
Argyris, Nikolaos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-24
N.Argyris@warwick.ac.uk
Department of Statistics, University of Warwick, Coventry,
United Kingdom
Arias, Pol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-41
pol.arias5@gmail.com
University of Edinburgh, United Kingdom
AUTHOR INDEX
Economics and Business, Austria
Arikan, Yildiz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-08
yildiz.arikan@bahcesehir.edu.tr
Bahcesehir University, Istanbul, Turkey
Arini, Hilya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-33
hilya.mudrika@gmail.com
Mechanical and Industrial Engineering, Universitas Gadjah
Mada, Yogyakarta, Indonesia
Arlt, Josef . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-34
arlt@vse.cz
Department of Statistics and Probability, University of Economics, Prague, Prague, Czech Republic
Arltova, Marketa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-34
arltova@vse.cz
Department of Statistics and Probability, University of Economics, Prague, Prague, Czech Republic
Armborst, Kathrin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-15
Kathrin.Armborst@ruhr-uni-bochum.de
Faculty of Management and Economics, Ruhr University
Bochum, Bochum, Germany
Arns Steiner, Maria Teresinha . . . . . . . . . . . . . . MA-08, MB-32
maria.steiner@pucpr.br
Industrial Engineering Dept., PUCPR, Curitiba, Pr, Brazil
Aronsson, Martin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-01
martin@sics.se
SICS, KISTA, Sweden
Aros-Vera, Felipe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-44
arosvm@rpi.edu
Rensselaer Polytechnic Institute, Troy, New York, United
States
Arroyo, José Manuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-10
JoseManuel.Arroyo@uclm.es
Electrical Engineering, Universidad de Castilla- La Mancha,
Ciudad Real, Spain
Arruda, Edilson . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-22
efarruda@po.coppe.ufrj.br
Industrial Engineering Program, Universidade Federal do Rio
de Janeiro, Rio de Janeiro, RJ, Brazil
Arslan, Damla . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-12
guldamla_87@hotmail.com
Department of Mathematics, Science Institute, Isparta,
Turkey
Artigues, Christian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-02
artigues@laas.fr
LAAS, CNRS, Toulouse Cedex 4, France
Asad, Rami . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-02
rafif@aus.edu
Industrial Engineering, American University of Sharjah,
Sharjah, United Arab Emirates
Arieli, Itai . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-06
iarieli@tx.technion.ac.il
Industrial Engineering and Management, Technion, Israel
Asamov, Tsvetan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-45
tsvetan.asamov@gmail.com
Department of Operations Research and Financial Engineering, Princeton University, Princeton, New Jersey, United
States
Arikan, Emel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-33
earikan@wu.ac.at
Information Systems and Operations, Vienna University of
Asgeirsson, Eyjolfur . . . . . . . . . . . . . . . . . . . . . . . . HE-10, MD-19
eyjo@ru.is
School of Science and Engineering, Reykjavik University,
293
AUTHOR INDEX
IFORS 2014 - Barcelona
Reykjavik, Iceland
Ashimov, Abdykappar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-25
Ashimov37@mail.ru
Parametric Regulation, Kazakh National Technical University named after K. Satpayev, Almaty, Kazakstan
Aslan, Bulut . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-36
bulut.aslan@bilgi.edu.tr
Industrial Engineering, Istanbul Bilgi University, Istanbul,
Turkey
Asmild, Mette . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-14
meas@foi.ku.dk
University of Copenhagen, Frederiksberg, Denmark
Assadipour, Ghazal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-32
ghazal.assadipour@mun.ca
Memorial University of Newfoundland, St Johns, Canada
Assimakopoulos, Vasilis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-09
fsu@ece.ntua.gr
Electrical & Computer Engineering, National Technical University of Athens, Athens, Attica, Greece
Asta, Shahriar. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-33, HE-33
Sba@cs.nott.ac.uk
Computer Science, The University of Nottingham, Nottingham, Nottingham, United Kingdom
Astorino, Annabella . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-26
astorino@icar.cnr.it
ICAR, CNR, Rende, Italy
Astrakov, Sergey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-17
astrakov90@gmail.com
Design Technological Institute of Digital Techniques,
Novosibirsk, Russian Federation
Ata, Zeynep . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-37
zeynep.ata@boun.edu.tr
International Trade, Bogazici University, Istanbul, Turkey
Atalik, Gultekin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-07
gultekinatalik@anadolu.edu.tr
Statistics, Anadolu University, Eskisehir, Turkey
Atasever, Cem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-13
catasever@msn.com
Industrial Engineering, Eskişehir Osmangazi Üniversitesi,
Eskisehir, TURKEY, Turkey
Atoche, Wilmer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-10
watoche@pucp.edu.pe
Ingeniería Industrial, Pontificia Universidad Católica del
Perú, Lima, Peru
Atzeni, Italo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-10
italo.atzeni@upc.edu
Signal Theory and Communications, Universitat Politècnica
de Catalunya - Barcelona Tech, Barcelona, Spain
Auray, Stephane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-43
stephane.auray@ensai.fr
Economics, Ensai-CREST and ULCO, Bruz, France
Autenrieb, Niels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-33
auteagoe@mailbox.tu-berlin.de
Technical University of Berlin, Berlin, Germany
Avci, Buket . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-08
buketavci@smu.edu.sg
294
Operations Management, Singapore Management University,
Singapore, Singapore
Avci, Mustafa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-02
mustafa.avci@deu.edu.tr
Industrial Engineering, Dokuz Eylül University, İzmir,
Turkey
Avcioglu, Eray . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-08
eray.avcioglu@hotmail.com
Business Management Engineering, Politecnico di Milano,
Milan, Italy
Ayer, Turgay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-39
ayer@isye.gatech.edu
Industrial and Systems Engineering, Georgia Tech, Atlanta,
GA, United States
Ayli, Ezgi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-04
ezgiayli@sabanciuniv.edu
Industrial Engineering, Faculty of Engineering and Natural
Sciences, Sabanci University, Istanbul, Turkey
Ayre, Melanie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-43
Melanie.Ayre@csiro.au
Mathematics, Informatics and Statistics, CSIRO Australia,
South Clayton, Australia
Aysever, Şimal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-43
simalaysever@hotmail.com
Industrial Engineering Department, Istanbul Kültür University, Istanbul, Turkey
Aytaç, Özcan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-33
ozcan.aytac@deu.edu.tr
Industrial Eng., Dokuz Eylul Unv., Izmir, Turkey
Azevedo, Anibal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-05, TA-14
atanibal@yahoo.com
Production engineering, State University of Campinas,
Campinas, São Paulo, Brazil
Aziz, Azmin Azliza . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-39
star159@gmail.com
University of Malaya, Kuala Lumpur, Malaysia
Aziz, Haemin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-42
principal@lccl.org.uk
London Corporate College, London, United Kingdom
Azizi, Majid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-37
mazizi@ut.ac.ir
Department of Wood and Paper, Faculty of Natural Resources,University of Tehran, Karaj, Tehran, Iran, Islamic
Republic Of
Azizi, Nader . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-45
n.azizi@kent.ac.uk
Kent Business School, University of Kent, Chatham, Kent,
United Kingdom
Azizoglu, Meral . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-12
ma@metu.edu.tr
Department of Industrial Engineering, Middle East Technical
University, Ankara, Turkey
B. Hadj-Alouane, Atidel . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-41
atidel.hadj@enit.rnu.tn
Industrial Engineering, National Engineering School of Tunis, Tunis, Tunisia
Başoğlu, İsmail . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-34
IFORS 2014 - Barcelona
ismailbsgl@gmail.com
Department of Industrial Engineering, Boğaziçi University,
İstanbul, Turkey
Babic, Zoran . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-14
babic@efst.hr
Quantitative methods, Faculty of Economics, Split, Croatia
Babich, Vlad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-24
vob2@georgetown.edu
Georgetown University, Washington DC, United States
Bacao, Fernando . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-34
bacao@isegi.unl.pt
ISEGI, Universidade Nova de Lisboa, Lisboa, Lisboa, Portugal
AUTHOR INDEX
CNRS, University Clermont II, AUBIERE, France
Baisa, Brian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-41
bbaisa@amherst.edu
Dept of Economics, Amherst College, Amherst, MA, United
States
Bajalinov, Erik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-32
Bajalinov@NyF.Hu
Inst. of Mathematics and Informatics, University College of
Nyíregyháza, Nyíregyháza, Hungary
Bajor, Péter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-05
p.22567@gmail.com
Széchenyi István University, Győr, Hungary
Bach, Lukas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-01
lukas.bach@sintef.no
Aarhus University / SINTEF ICT, Aarhus V, Arhus, Denmark
Bakal, Ismail Serdar . . . . . . . . . . . . . . . . . . . . . . . . . TE-19, ME-40
isbakal@metu.edu.tr
Industrial Engineering, Middle East Technical University,
Ankara, Turkey
Bachmann, Chris . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-06
chris.bachmann@alumni.utoronto.ca
Civil Engineering, University of Toronto, Toronto, Ontario,
Canada
Baker, Erin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-20, TB-20
edbaker@ecs.umass.edu
Mechanical and Industrial Engineering, U. Mass Amherst,
Amherst, MA, United States
Backs, Sabrina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-35
sabrina.backs@uni-bielefeld.de
Department of Business Administration and Economics,
Bielefeld University, Bielefeld, Germany
Bakhrankova, Krystsina . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-03
krystsina.bakhrankova@sintef.no
Applied economics, SINTEF - Technology and society,
Trondheim, Norway
Badia, Francisco Germán . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-24
gbadia@unizar.es
University of Zaragoza, Spain
Bakhtiari, Sarah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-07
sara_292423@yahoo.com
Industrial Management Institute, Iran, Islamic Republic Of
Baek, Jun-Geol . . . . . . . . . . . . . . . . . . . . . . . FB-16, TE-32, MA-34
jungeol@korea.ac.kr
School of Industrial Management Engineering, Korea University, Seoul, Korea, Republic Of
Bakir, Onur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-35
nbakir@etu.edu.tr
Industrial Engineering, TOBB University of Economics and
Technology, Ankara, Turkey
Baesens, Bart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-25
bart.baesens@econ.kuleuven.ac.be
Decision
Sciences
and
Information
Mangement,
K.U.Leuven, Leuven, Leuven, Belgium
Bakker, Wim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-27, FA-40
w.h.bakker@utwente.nl
ITC, Enschede, Netherlands
Baesler, Felipe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-18
fbaesler@udd.cl
Industrial Engineering, Universidad del Desarrollo, Concepcion, Chile
Bagchi, Uttarayan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-06
Uttarayan.Bagchi@mccombs.utexas.edu
Information, Risk, & Operations Management, The Univ of
Texas at Austin, Austin, Texas, United States
Bagirov, Adil . . . . . . . . . . . . . . . . . . . . . . . . . HD-26, HE-26, TE-26
a.bagirov@ballarat.edu.au
School of Science, Information Technology & Engineering,
Faculty of Science, Federation University Australia, Ballarat,
Victoria, Australia
Bahadır, Cansu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-24
cansubahadir.91@gmail.com
Industrial Engineering, Istanbul Kültür University, Istanbul,
Turkey
Bahn, Olivier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-08
olivier.bahn@hec.ca
GERAD and MQG, HEC Montréal, Montréal, Qc, Canada
Baiou, Mourad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-03
baiou@isima.fr
Bakshi, Nitin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-22
nbakshi@london.edu
London Business School, London, United Kingdom
Baladincz, Emőke Ila . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-05
emoke.baladincz@gmail.com
Széchenyi István University, Győr, Hungary
Balakrishnan, Anant . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-15
anantb@utexas.edu
University of Texas at Austin, Austin, United States
Balakrishnan, Ramji . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-15
Ramji-balakrishnan@uiowa.edu
University of Iowa, Iowa City, ia, United States
Balas, Egon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-11
eb17@andrew.cmu.edu
Tepper School of Business, Carnegie Mellon University,
Pittsburgh, PA, United States
Balcik, Burcu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-04, TB-32
burcu.balcik@ozyegin.edu.tr
Ozyegin University, X, Turkey
Baldioti, Hugo Ribeiro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-29
hugo.baldioti@gmail.com
Electrical Engineering Department, Pontifical Catholic Uni-
295
AUTHOR INDEX
IFORS 2014 - Barcelona
versity of Rio de Janeiro, Rio de Janeiro, Rio de Janeiro,
Brazil
Balezentis, Tomas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-14
tomas@laei.lt
Lithuanian Institute of Agrarian Economics, Lithuania
Ball, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-03
mball@rhsmith.umd.edu
R H Smith School of Business, University of Maryland, College Park, MD, United States
Ballestero, Enrique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-38
eballe@esp.upv.es
Escuela Politecnica Superior de Alcoy, Technical University
of Valencia, Alcoy (Alicante), Spain
Ballestin, Francisco . . . . . . . . . . . . . . . . . . . . . . . . . FB-12, MA-39
Francisco.Ballestin@uv.es
Matematicas para la Economia, Universidad de Valencia, Valencia, Spain
Bana e Costa, Carlos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-10
carlosbana@ist.utl.pt
Centre of Management Studies of IST, Technical University
of Lisbon, Lisbon, Portugal
Banal Estanol, Albert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-07
albert.banalestanol@upf.edu
Universitat Pompeu Fabra, Barcelona, Spain
Banasik, Aleksander . . . . . . . . . . . . . . . . . . . . . . . . HB-08, MB-18
olek.banasik@wur.nl
Operations Research and Logistics, Wageningen University,
Wageningen, Gelderland, Netherlands
Banciu, Mihai . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-15
mmb018@bucknell.edu
School of Management, Bucknell University, Lewisburg, PA,
United States
Banerjee, Soumya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-45
soumyabanerjee@bitmesra.ac.in
Computer Sc.& Engg, BIT Mesra, Ranchi, Jharkhand, India
Baptista, Edmea Cássia . . . . . . . . . . . . . . . . . . . . . . TA-10, MD-43
baptista@fc.unesp.br
Departamento de matemática, Faculdade de Ciências, UnespUniv. Estadual Paulista, Brazil
United Kingdom
Barbósa-Póvoa, Ana Paula . . . . . . . . . . . . . . . . . . . . . . . . . . TB-44
apovoa@ist.utl.pt
Dept. De Engenharia e Gestao, IST, Lisbon, Portugal
Barber, Klaus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-36
kbarber@fs.fed.us
USDA Forest Service, Berkely, California, United States
Barceló, Jaume . . . . . . . . . . . . . . . . . . . . . . . HB-04, HE-04, TC-50
jaume.barcelo@upc.edu
Statistics and Operations Research, Universitat Politècnica
de Catalunya, Barcelona, Spain
Barcus, Ana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-23
A.Barcus@LSE.ac.uk
Dept of Management, LSE, Toronto, Ontario, Canada
Barfod, Michael Bruhn . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-37
mbb@transport.dtu.dk
Department of Transport, Technical University of Denmark,
Kgs. Lyngby, Denmark
Baringo, Luis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-09
Luis.Baringo@gmail.com
EEH - Power Systems Laboratory, ETH Zurich, Zürich,
Switzerland
Barkai, Ofer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-40
ofer@sce.ac.il
Industrial Engineering and Management, Shamoon College
of Engineering, Ashdod, Israel
Barlow, Euan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-20
euan.barlow@strath.ac.uk
University of Strathclyde, United Kingdom
Barnhart, Cynthia . . . . . . . . . . . . . . . . . . MB-03, MD-03, ME-03
cbarnhart@mit.edu
MIT, Cambridge, MA, United States
Barreiras, Alcinda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-43
asb@isep.ipp.pt
Mathematic, ISEP, Porto, Portugal
Barrena, Eva . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-01, HD-01
eva.barrena@cirrelt.ca
CIRRELT, HEC Montreal, Montreal, Canada
Baptiste, Pierre . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-02, TE-02
pbaptiste@polymtl.ca
de mathématiques et de Génie Industriel, École Polytechnique de Montréal, Montréal, Québec, Canada
Barron, Robert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-20
barron@ecs.umass.edu
Mechanical and Industrial Engineering, University of Massachusetts, Amherst, MA, United States
Baradar, Mohamadreza . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-07
baradar@kth.se
School of Electrical Engineering Department of Electric
Power Systems, KTH Royal Institute of Technology, Stockholm, Sweden
Barros, Ana Isabel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-33
ana.barros@tno.nl
Military Operations, TNO, The Hague, Netherlands
Barahona, Francisco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-03
barahon@us.ibm.com
IBM Research, United States
Barata, João . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-44
barata_joao@hotmail.com
Escola Naval - CINAV, Portugal
Barbati, Maria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-03
maria.barbati@port.ac.uk
Business School, University of Portsmouth, Portsmouth, UK,
296
Barros, Ana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-36
ana.gracio@portucelsoporcel.com
Forest Proctection, grupo Portucel Soporcel, Setúbal, Portugal
Barros, Regiane Silva de . . . . . . . . . . . . . . . . . . . . . ME-08, TD-18
rsbarros@fem.unicamp.br
Energy Department, Unicamp, Campinas, São Paulo, Brazil
Barroso, Luiz-Augusto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-10
granville@psr-inc.com
PSR, Rio de Janeiro, Brazil
IFORS 2014 - Barcelona
Bartolini, Enrico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-11
enrico.bartolini@unimore.it
DISMI, University of Modena and Reggio Emilia, Italy
Barton, Paul I. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-45
pib@mit.edu
Department of Chemical Engineering, MIT, Cambridge, MA,
United States
Barz, Christiane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-15
christiane.barz@anderson.ucla.edu
Anderson School of Management, UCLA, Los Angeles, CA,
United States
AUTHOR INDEX
Baucells, Manel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-15, TE-31
manel.baucells@upf.edu
Economics and Business, Universitat Pompeu Fabra,
Barcelona, Spain
Baudach, Jens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-35
baudach@itl.tu-dortmund.de
Institute of Transport Logistics, TU Dortmund University,
Dortmund, NRW, Germany
Baumann, Philipp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-25
philipp.baumann@pqm.unibe.ch
Department of Business Administration, University of Bern,
Bern, Switzerland
Basán, Natalia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-21
basan.natalia@gmail.com
Instituto de Desarrollo Tecnológico para la Industria
Química, Santa Fe, Santa Fe, Argentina
Bauso, Dario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-24
dario.bauso@unipa.it
DICGIM, Università di Palermo, Palermo, Italy
Baset, Salman . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-30
sabaset@us.ibm.com
IBM T. J. Watson Research Center, Yorktown Heights, NY,
United States
Baviera-Puig, Amparo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-36
ambapui@upv.es
Economics and Social Sciences, Universitat Politècnica de
València, Valencia, Spain
Bastert, Oliver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-28
oliverbastert@fico.com
FICO, Munich, Germany
Baydoğan, Mustafa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-42
mustafa.baydogan@boun.edu.tr
Department of Industrial Engineering, Boğaziçi University,
İstanbul, Turkey
Bastian-Pinto, Carlos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-34
carbastian@gmail.com
Mangement, Ibmec, Rio de Janeiro, RJ, Brazil
Bastin, Fabian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-20
bastin@iro.umontreal.ca
Computing Science and Operations Research, University of
Montreal, Montreal, Quebec, Canada
Basu, Sumanta . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-15
sumanta@iimcal.ac.in
Operations Management, Indian Institute of Management
Calcutta, Kolkata, West Bengal, India
Bayindir, Z. Pelin . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-19, ME-40
bpelin@metu.edu.tr
Department of Industrial Engineering, Middle East Technical
University, Ankara, Turkey
Baykasoğlu, Adil . . . . . . . . . . . . . . . . . . . . . HA-12, HD-15, HE-23
adil.baykasoglu@deu.edu.tr
Industrial Engineering, Dokuz Eylül University, Izmir,
Turkey
Baynal, Kasım . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-16
kbaynal@yahoo.com
Industrial Engineering, Kocaeli University, Kocaeli, Turkey
Batmaz, Inci . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-22
ibatmaz@metu.edu.tr
Department of Statistics, Middle East Technical University,
Ankara, Turkey
Bärmann, Andreas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-01
baermann@mathematik.tu-darmstadt.de
Department Mathematik, FAU Erlangen-Nürnberg, Germany
Batselier, Jordy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-12
jordy.batselier@ugent.be
Faculty of Economics and Business Administration, Ghent
University, Ghent, Belgium
Baysal, Gülendam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-35
gbaysal@uni-bonn.de
Ecology and Natural Resources Management, Center for Development Research (ZEF), Germany
Batsyn, Mikhail . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-39
mbatsyn@hse.ru
Laboratory of Algorithms and Technologies for Networks
Analysis, National Research University Higher School of
Economics, Nizhny Novgorod, Russian Federation
Bayturk, Engin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-21, HB-43
e.bayturk@iku.edu.tr
Department of Industrial Engineering, Istanbul Kultur University, Istanbul, Turkey
Battaïa, Olga . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-13
battaia@emse.fr
IE & Computer Science, Ecole des Mines de Saint Etienne,
Saint Etienne, France
Battini, Daria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-13
Daria.battini@unipd.it
Università di Padova, Italy
Battiti, Roberto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-40
battiti@disi.unitn.it
DISI - Dipartimento di Informatica e Telecomunicazioni,
Universita’ di Trento, Trento, Italy
Bazhanov, Andrei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-15
bazhanov@econ.queensu.ca
Queens University, Kingston, Canada
Beck, Amir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-38
becka@ie.technion.ac.il
Faculty of Industrial Engineering and Management, Technion
- Israel Institute of Technology, Haifa, Israel
Beck, Marissa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-41
mrbeck@stanford.edu
Dept of Economics, Stanford University, Stanford, CA,
United States
Becker, Joana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-30
297
AUTHOR INDEX
IFORS 2014 - Barcelona
joanaeuro2012@gmail.com
Mathematics, University of Porto, Porto, Porto, Portugal
Becker, Kai Helge . . . . . . . . . . . . . . . . . . . . . . . . . . MA-23, MB-23
kai.becker@qut.edu.au
Mathematical Sciences, Faculty of Science & Technology,
Queensland University of Technology, Brisbane, Australia
Beg, Sayara . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-23, FA-34
sayara@datanut.co.uk
Data Science, Operational Research Consultancy, London,
United Kingdom
Begen, Mehmet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-08
mbegen@ivey.uwo.ca
Ivey Business School, Western University, London, ON,
Canada
Behling, Roger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-26
rbehling@impa.br
Instituto de Matemática Pura e Aplicada, Rio de Janeiro, Rio
de Janeiro, Brazil
Behrens, Doris. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-27
Doris.Behrens@aau.at
Controlling and Strategic Management, University of Klagenfurt, Klagenfurt, Austria
Bekker, James . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-36
jb2@sun.ac.za
Industrial Engineering, Stellenbosch University, Stellenbosch, Western Cape, South Africa
Belloso, Javier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-41
javier.belloso@unavarra.es
Engineering Mathematics, Universidad Publica Navarra,
Spain
Belo Filho, Márcio Antônio Ferreira . . . . . . . . . . . . . . . . . FA-06
marciobelof@gmail.com
Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo, São Carlos, São Paulo, Brazil
Belov, Gleb . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-21
bg37@gmx.net
Numerical Mathematics, TU Dresden, Dresden, Germany
Belton, Valerie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-31
val.belton@strath.ac.uk
Dept. Management Science, University of Strathclyde, Glasgow, United Kingdom
Beltran-Royo, Cesar. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-08
cesar.beltran@urjc.es
Estadística e Investigación Operativa, Universidad Rey Juan
Carlos, Móstoles, Madrid, Spain
Belyakov, Anton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-25
anton.belyakov@tuwien.ac.at
Mathematical Methods in Economics, Vienna University of
Technology, Vienna, Austria
Ben Amor, Sarah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-31
benamor@telfer.uottawa.ca
Telfer School of Management, University of Ottawa, Ottawa,
Ontario, Canada
Bektas, Tolga . . . . . . . . . . . . . . . . . HB-02, TE-03, TB-41, MA-42
T.Bektas@soton.ac.uk
University of Southampton, School of Management,
Southampton, United Kingdom
Ben David, Arie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-24
abendav@hit.ac.il
Holon Institute of Technology, Holon, Israel
Belacel, Nabil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-16
nabil.belacel@nrc.gc.ca
Knowldge discovery group, NRC-Institute for Information
Technology-e-Business, Moncton, New Brunswick, Canada
Benade, Johannes Gerhardus . . . . . . . . . . . . . . . . . HE-17, FB-36
jgbenade@ml.sun.ac.za
Department of Logistics, Stellenbosch University, Matieland,
Western Cape, South Africa
Belarmino, Jenifer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-20
jenifer_belarmino@yahoo.com
DSWD, Quezon City, Philippines
Benavent, Enrique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-11
Enrique.Benavent@uv.es
Estadistica e Investigación Operativa, Universitat de València, Burjassot, Valencia, Spain
Belenguer, Jose M. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-02
jose.belenguer@uv.es
Estadistica i Investigació Operativa, Universitat de València,
Burjassot, Valencia, Spain
Belenky, Alexander . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-42
abelenky@mit.edu
Department of Mathematics for Economics, National Research University Higher School of Economics and MIT,
Moscow, Russian Federation
Belien, Jeroen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-21, MB-39
Jeroen.Belien@kuleuven.be
Center for Information Management, Modeling and Simulation, KU Leuven, Brussels, Benin
Bell, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-08
pbell@ivey.ca
Western Univesity, Ivey Business School, London, Ontario,
Canada
Belloni, Alexandre . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-06
abn5@duke.edu
Duke University, Durham, NC, United States
298
Benchetrit, Yohann . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-21
Yohann.benchetrit@g-scop.grenoble-inp.fr
Laboratoire G-SCOP, Grenoble, France
Benchimol, Pascal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-24
pascal.benchimol@polytechnique.edu
CMAP, Ecole Polytechnique, Palaiseau, France
Bender, Marco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-39
mbender@math.uni-goettingen.de
Institute for Numerical and Applied Mathematics, University
of Goettingen, Germany
Bender, Matthias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-02
mbender@fzi.de
Information Process Engineering, FZI Research Center for
Information Technology, Karlsruhe, Germany
Benito, Antonio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-38
anbebe@esp.upv.es
Economics and Social Sciences, Technical University of Valencia, Alcoy, Alicante, Spain
Benito-Sarriá, Germán . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-38
IFORS 2014 - Barcelona
anbebe@ono.com
Universitat Politècnica de València, Spain
Benjaafar, Saif . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-33
saif@sutd.edu.sg
Engineering Systems and Design, Singapore University of
Technology and Design, Singapore, Singapore, Singapore
Bennell, Julia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-03, HA-21
jab2@soton.ac.uk
School of Management, University of Southampton,
Southampton, Hampshire, United Kingdom
Benoit, Dries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-42
dries.benoit@ugent.be
Ghent University, Gent, Belgium
Benson, Hande . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-17
benson@drexel.edu
Decision Sciences, Drexel University, Philadelphia, PA,
United States
Bensoussan, Alain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-30
alain.bensoussan@utdallas.edu
School of Management, University of Texas at Dallas,
Richardson, TX, United States
Bental, Benjamin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-25
bbental@econ.haifa.ac.il
Economics, University of Haifa, Haifa, Israel, Israel
Bento, Glaydston . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-14, FB-26
glaydstonc@gmail.com
Mathematics, Federal University of Goiás, Goiania, Goiás,
Brazil
Beraldi, Patrizia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-45
patrizia.beraldi@unical.it
Department of Mechanical, Energy and Management Engineering, University of Calabria, Rende (CS), ITALY, Italy
Berg, Bjorn . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-43
bberg2@gmu.edu
Systems Engineering & Operations Research Department,
George Mason University, Fairfax, VA, United States
Bergmann, Lisa Katharina . . . . . . . . . . . . . . . . . . . . . . . . . . FA-10
katharina.bergmann@tuhh.de
Institute for Operations Research and Information Systems,
Hamburg University of Technology, Hamburg, Hamburg,
Germany
AUTHOR INDEX
jbermeo@alumni.unav.es
Economics and Bussines Administration, University of
Navarra, Baranain, Navarra, Spain
Bernales, Alejandro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-10
Alejandro.BERNALES@banque-france.fr
Dept. of Industrial Engineering - University of Chile & Research Department - Banque de France, Santiago, Chile
Bernstein, Andrey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-20
andrey.bernstein@epfl.ch
School of Computer and Communications Sciences, École
Polytechnique Fédérale de Lausanne (EPFL), Lausanne,
Switzerland
Berrachedi, Abdelhafid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-12
abdelhafid_berrachedi@yahoo.fr
Recherche Opérationnelle, Faculté Des Mathématiques, Algiers, Algeria
Berrais, Abdelaziz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-14
berrais.abdelaziz@yahoo.com
Computer Science, Taibah University, Badr, Medinah Monawarah, Saudi Arabia
Bertazzi, Luca . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-41
bertazzi@eco.unibs.it
Dept. of Quantitative Methods, University of Brescia, Brescia, Italy
Bertocchi, Marida . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-09
marida.bertocchi@unibg.it
Department of Management, Economics and Quantitative
Methods, University of Bergamo, Bergamo, BG, Italy
Bertrand, Jean-Louis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-19
jean-louis.bertrand@essca.fr
Finance, ESSCA, Angers, France
Besbes, Walid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-14
walid.besbes@fsegs.rnu.tn
Quantitative methods, Faculty of Economics and Management of Sfax, Sfax, Sfax, Tunisia
Besinovic, Nikola . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-01
n.besinovic@tudelft.nl
Delft University of Technology, Delft, Netherlands
Bettinelli, Andrea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-02
andrea.bettinelli@unibo.it
DEI, Università di Bologna, Bologna, Italy
Bergner, Martin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-39
bergner@or.rwth-aachen.de
Operations Research, RWTH Aachen University, Aachen,
Germany
Betts, Gavin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-38
g.betts@hull.ac.uk
Hull University Business School, University of Hull, Hull,
East Yorkshire, United Kingdom
Berlin, Julian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-40
julian.r.berlin@gmail.com
CITG, TU Delft, Delft, Suid-Holland, Netherlands
Bettstetter, Christian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-27
Christian.Bettstetter@uni-klu.ac.at
Universität Klagenfurt, Klagenfurt, Austria
Berman, Oded . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-03
berman@rotman.utoronto.ca
Rotman School of Management, University of Toronto,
Toronto, ON, Canada
Bi, Yalin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-15
biyalin@gmail.com
Mathematical Sciences, University of Southampton, S,
United Kingdom
Bermúdez, Alfredo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-21
alfredo.bermudez@usc.es
Matemática Aplicada, Universidad de Santiago de Compostela, Santiago de Compostela, Spain
Biagioni Martins, Luiz Geraldo . . . . . . . . . . . . . . . . . . . . . HB-34
lgbiagioni@yahoo.com.br
Ibmec RJ, Rio de Janeiro, Rio de Janeiro, Brazil
Bermeo, Juan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-08, TE-08
Bianchi-Aguiar, Teresa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-19
mtbaguiar@fe.up.pt
299
AUTHOR INDEX
IFORS 2014 - Barcelona
INESC TEC, Faculty of Engineering, University of Porto,
Portugal
University of Chicago Booth School of Business, Chicago,
IL, United States
Bichescu, Bogdan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-39
bbichescu@utk.edu
Statistics, Operations, and Management Science, The University of Tennessee, Knoxville, TN, United States
Bischoff, Martin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-18
Martin.Bischoff@siemens.com
Corporate Technology, Siemens AG, München, Germany
Bichler, Martin. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-41, TE-43
martin.bichler@in.tum.de
Informatics, TU München, Garching, Germany
Bieda, Boguslaw . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-20
bbieda@zarz.agh.edu.pl
Management, AGH-University of Science and Technology,
Krakow, Poland
Bivona, Enzo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-09
Enzo.Bivona@unipa.it
DEMS, University of Palermo, Palermo, Italy
Bıçakcıoğlu, Nilay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-40
nilaybicakcioglu@gmail.com
International Business and Trade, Dokuz Eylul University
Faculty of Business, İzmir, Turkey
Bierkandt, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-33
michael.bierkandt@ipoint-systems.de
iPoint-systems GmbH, Reutlignen, Germany
Bjørndal, Endre . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-20
endre.bjorndal@nhh.no
Dept. of Business and Management Science, NHH Norwegian School of Economics, Bergen, Norway
Bierlaire, Michel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-01
michel.bierlaire@epfl.ch
Enac Inter Transp-or, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
Bjørndal, Mette . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-20
mette.bjorndal@nhh.no
Department of Business and Management Science, NHH
Norwegian School of Economics, Bergen, Norway
Bierwirth, Christian . . . . . . . . . . . . . . . . . . . . . . . . . HA-02, HD-29
christian.bierwirth@wiwi.uni-halle.de
Martin-Luther-University Halle-Wittenberg, Halle, Germany
Blackburn, Robert . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-21, HC-50
robert.blackburn@basf.com
BASF, Germany
Bilbao-Terol, Amelia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-26
ameliab@uniovi.es
University of Oviedo, Oviedo, Spain
Blanco, Christian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-08
christian.blanco.2016@anderson.ucla.edu
UCLA Anderson School of Management, Los Angeles, CA,
United States
Bilgen, Bilge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-08, HB-13
bilge.bilgen@deu.edu.tr
Industrial Engineering, Dokuz Eylul University, Izmir,
Turkey
Bilgiç, Burcu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-43
brcbilgic@gmail.com
Mathematics, Institute of Science, Diyarbakır, Turkey
Bilgic, Taner . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-03
taner@boun.edu.tr
Industrial Engineering, Bogazici University, Istanbul, Turkey
Billaut, Jean-Charles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-12
jean-charles.billaut@univ-tours.fr
University of Tours, Tours, France
Billinge, Simon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-11
sb2896@columbia.edu
Applied Physics and Applied Mathematics, Columbia University, New York, New York, United States
Billio, Monica . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-38
billio@unive.it
Department of Economics, University Ca’ Foscari of Venice,
Venice, Italy
Bimpikis, Kostas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-06
kostasb@stanford.edu
Stanford GSB, Stanford, CA, United States
Birbil, S. Ilker . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-17
sibirbil@sabanciuniv.edu
Manufacturing Systems/Industrial Engineering, Sabanci University, Tuzla, Istanbul, Turkey
Birge, John . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-09, FB-20, TD-24
john.birge@chicagobooth.edu
300
Blanco, Víctor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-03
vblanco@ugr.es
Quant. Methods for Economics & Business, Universidad de
Granada, Granada, Spain
Blanquero, Rafael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-21
rblanquero@us.es
Estadística e Investigación Operativa, Universidad de Sevilla,
Seville, Spain
Blazewicz, Jacek . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-13
jblazewicz@cs.put.poznan.pl
Institute of Computing Science, Poznan University of Technology, Poznan, Poland
Bley, Thomas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-33
thomas.bley@ipoint-systems.de
iPoint-systems gmbh, Germany
Block, Joachim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-03
archibald@ieee.org
Institut für Theoretische Informatik, Mathematik und Operations Research, Universität der Bundeswehr München,
Neubiberg, Germany
Bloemhof, Jacqueline . . . . . . . . . . . . . . . . HB-08, HA-41, MA-42
jacqueline.bloemhof@wur.nl
Operations Research and Logistics, Wageningen University,
Wageningen, Netherlands
Blot, Joel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-25
Joel.Blot@univ-paris1.fr
University Paris 1, Paris, France
Blum, Christian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-40
christian.c.blum@gmail.com
IKERBASQUE and University of the Basque Country, San
IFORS 2014 - Barcelona
Sebastian, – Please Select (only U.S. / Can / Aus), Spain
Bocanegra, Silvana . . . . . . . . . . . . . . . . . . . . . . . . . . TD-17, HD-41
silvana@deinfo.ufrpe.br
Department of Statistics and Informatics, Universidade Federal Rural de Pernambuco, Recife, Pernambuco, Brazil
Bock, Stefan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-13, TB-43
sbock@winfor.de
WINFOR (Business Computing and Operations Research)
Schumpeter School of Business and Economics, University
of Wuppertal, Wuppertal, NRW, Germany
Bodur, Merve . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-11
merve.bodur@boun.edu.tr
Department of Industrial Engineering, Boğaziçi University,
Istanbul, Turkey
Boggia, Antonio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-36
boggia@unipg.it
DSEEA, University of Perugia, Perugia, Italy
Bohanec, Marko . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-42, FB-42
marko.bohanec@ijs.si
Department of Knowledge Technologies, Jozef Stefan Institute, Ljubljana, Slovenia
Boillot, Adrien . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-01
adrien.boillot@ensta.org
Innovation & Research, SNCF, France
Bokov, Pavel M. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-11
pavel.bokov@necsa.co.za
Radiation and Reactor Theory, South African Nuclear Energy
Corporation SOC Ltd, Pretoria, South Africa
Boland, John . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-08
john.boland@unisa.edu.au
School of Mathematics and Statistics, University of South
Australia, Mawson Lakes, South Australia, Australia
Boland, Natashia . . . . . . . . . . . . . . FA-06, FA-15, HE-29, TD-39
natashia.boland@newcastle.edu.au
School of Mathematical and Physical Sciences, The University of Newcastle, Callaghan, NSW, Australia
Bolia, Nomesh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-01, MA-22
nomesh@mech.iitd.ac.in
Department of Mechanical Engineering, Indian Institute of
Technology (IIT), Delhi, New Delhi, Delhi, India
Boloori, Fatemeh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-36
boloori@azaruniv.ac.ir
Mathematics, Azarbayjan Shahid Madani University, Iran,
Islamic Republic Of
Bolte, Jérôme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-38
jerome.bolte@tse-fr.eu
21 Allée de Brienne, University Toulouse Capitole, Toulouse
(Cedex), France
Bomze, Immanuel . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-16, HE-26
immanuel.bomze@univie.ac.at
Dept. of Statistics and OR, University of Vienna, Vienna,
Austria
Bonnans, J. Frederic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-20
Frederic.Bonnans@inria.fr
Projet Sydoco, INRIA, Le Chesnay, France
Bonomo, Flavia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-35
fbonomo@dc.uba.ar
AUTHOR INDEX
Computer Science, University of Buenos Aires, Buenos
Aires, Argentina
Bordin, Chiara . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-09
chiara.bordin2@unibo.it
Department of Electrical, Electronic and Information Engineering (DEI), University of Bologna, Bologna, Italy, Italy
Borenich, Andrea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-04
andrea.borenich@uni-graz.at
Universität Graz, Austria
Borges, Diogo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-14
diogo.borges@fe.up.pt
Universidade Católica Portuguesa, Porto, Portugal
Borges, Jose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-36, TA-36
joseborges@isa.utl.pt
Instituto Superior de Agronomia, Portugal
Borggrefe, Frieder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-34
fborggrefe@gmail.com
Systems Analysis and Technology Assessment, German
Aerospace Center (DLR), Stuttgart, Germany
Borgwardt, Steffen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-45
borgwardt@ma.tum.de
Fakultät für Mathematik, Technische Universität München,
Garching, Bayern, Germany
Borndörfer, Ralf . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-01
borndoerfer@zib.de
Optimization, Zuse-Institute Berlin, Berlin, Germany
Borovskiy, Yuriy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-25
yuborovskiy@gmail.com
Kazakh National Technical University named after K. Satpayev, Almaty, Kazakstan
Borreguero, Tamara . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-13
tamara.borreguero@military.airbus.com
Technical University Madrid, Madrid, Madrid, Spain
Borror, Connie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-21
conni@asu.edu
Arizona State University, Phoenix, United States
Bortolini, Marco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-13
marco.bortolini3@unibo.it
Department of Industrial Engineering, University of Bologna,
Bologna, Italy
Bos, Jaap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-38
j.bos@maastrichtuniversity.nl
Finance Department, Maastricht University, Maastricht, Limburg, Netherlands
Bosco, Adamo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-41
adamo.bosco@gmail.com
Elettronica, Informatica e Sistemistica, Università della Calabria, Italy
Bossenger, Wayne . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-11
Spartacvs08@gmail.com
Logistics, Stellenbosch University, Somerset West, Western
Province, South Africa
Botequim, Brigite . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-36
bbotequim@isa.ulisboa.pt
Forestry Department, The School of Agriculture, University
of Lisbon, Lisbon, Portugal
301
AUTHOR INDEX
IFORS 2014 - Barcelona
Botte, Marilisa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-01
marilisabotte@tiscali.it
Department of Civil, Architectural and Environmental Engineering, ’Federico II’ University of Naples, Naples, Italy
Botterud, Audun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-20
abotterud@anl.gov
Decision and Information Sciences Division, Argonne National Laboratory, Lemont, United States
ria
Boute, Robert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-32
robert.boute@vlerick.com
Vlerick Business School and KU Leuven, Belgium
Bovo, Cristian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-09
cristian.bovo@polimi.it
Department of Energy, Politecnico di Milano, Milano, Italy
Böttger, Diana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-07
diana.boettger@wifa.uni-leipzig.de
Institute for Infrastructure and Resource Management, University of Leipzig, Leipzig, Germany
Boyaci, Burak . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-06
b.boyaci@lancaster.ac.uk
Management Science, Lancaster University, Lancaster,
United Kingdom
Bouallouche-Medjkoune, Louiza . . . . . . . . . . . . . . . . . . . . . FA-31
louiza-medjkoune@yahoo.fr
University of Bejaia, Bejaia, Algeria
Boyacı, Ahmet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-16
ahmet_boyaci@hotmail.com.tr
Management, Hitit University, Çorum, Turkey
Bouamama, Salim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-17
bouamamas@gmail.com
Université de M’sila, Algeria
Boysen, Nils . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-13
nils.boysen@uni-jena.de
Lehrstuhl für ABWL/ Operations Management, FriedrichSchiller-Universität Jena, Jena, Germany
Bouarab, Hocine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-02
hocine.bouarab@gerad.ca
MAGI, Polytechnique, Montreal, Qc, Canada
Boucherie, Richard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-39
r.j.boucherie@utwente.nl
Stochastich Operations Research, University of Twente, Enschede, Netherlands
Boudia, Mourad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-03
mourad.boudia@amadeus.com
Operations Research and Innovation, Amadeus, Sophia Antipolis, France
Boudries, Abdelmalek. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-16
am_boudries@yahoo.fr
University of Bejaia, university of Setif, Algeria, Béjaia, Algeria
Bouibed, Karima . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-26
karima.bouibed@gmail.com
Operational Research Department, University of Béjaia, Bejaia, Algeria
Boulougouris, Evangelos . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-20
evangelos.boulougouris@strath.ac.uk
Department of Naval Architecture, Ocean & Marine Engineering, University of Strathclyde, Glasgow, United Kingdom
Bouman, Paul . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-01, FA-40
PBouman@rsm.nl
Technology & Operations Management, Rotterdam School
of management, Erasmus University, Rotterdam, Netherlands
Bounkhel, Messaoud . . . . . . . . . . . . . . . . . . . . . . . . HA-26, HD-30
bounkhel@ksu.edu.sa
Department of Mathematics, King Saud University, Riyadh,
Saudi Arabia
Bouritas, Theodore . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-05
bouritas@aueb.gr
Athens University of Economics and Business, Athens,
Greece
Bouroubi, Sadek . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-39
bouroubis@yahoo.fr
Faculty of Mathematics, Dept of Operations research,
USTHB University, Laboratory L’IFORCE, Algiers, Alge-
302
Bozic, Caslav . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-16, FA-38
caslav.bozic@kit.edu
Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Bozkaya, Burcin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-03
bbozkaya@sabanciuniv.edu
Sabanci School of Management, Sabanci University, Istanbul, Turkey
Bradley, Randy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-39
rbradley@utk.edu
Accounting and Information Management, The University of
Tennessee, Knoxville, TN, United States
Brandao, Jose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-23
sbrandao@eeg.uminho.pt
Management, University of Minho; CEMAPRE — ISEG,
University of Lisbon, Braga, Portugal
Brandeau, Margaret L. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MC-50
brandeau@stanford.edu
Stanford University, Stanford, United States
Brandenburg, Marcus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-08
marcus.brandenburg@tu-berlin.de
Department of Production Management, Technische Universität Berlin, Berlin, Germany
Brandt, Felix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-02
brandt@fzi.de
Information Process Engineering, FZI Research Center for
Information Technology, Karlsruhe, Germany
Brasil, Daniel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-37
daniel@dcc.ufmg.br
DCC, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
Braune, Roland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-12
roland.braune@jku.at
Institute for Production and Logistics Management, Johannes
Kepler University, Linz, Austria
Brauneis, Alexander . . . . . . . . . . . . . . . . . . . . . . . . MB-44, MD-44
alexander.brauneis@aau.at
Finance & Accounting, University of Klagenfurt, Klagenfurt,
Austria
IFORS 2014 - Barcelona
AUTHOR INDEX
Brauner, Nadia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-13
president@roadef.org
G-SCOP - Grenoble, Grenoble, France
Bronfman, Andres . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-02, HD-03
abronfman@unab.cl
Universidad Andres Bello, Santiago, Chile
Bravo, Cristian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-25
crbravo@utalca.cl
Departamento de Modelamiento y Gestión Industrial, Universidad de Talca, Curicó, VII Region del Maule, Chile
Brooks, Paul . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-26
jpbrooks@vcu.edu
VCU, United States
Bravo, Mauricio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-02
mbravour@gmail.com
Industrial Engineering, University of Concepción, Concepción, Chile
Bravo, Mila . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-38
mibrasel@epsa.upv.es
Universitat Politècnica de València, Alcoy, Spain
Brotcorne, Luce . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-15
Luce.Brotcorne@inria.fr
INRIA, Villeneuve d’Ascq, France
Brown, Mark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-03
mark.brown@enri.go.jp
Air Traffic Management, Electronic Navigation Research Institute, Chofu, Tokyo, Japan
Brás, Isabel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-09
ibras@ua.pt
Mathematics, University of Aveiro, Aveiro, Portugal
Bruckner, Thomas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-07
bruckner@wifa.uni-leipzig.de
Institute for Infrastructure and Resources Management, Universität Leipzig, Leipzig, Germany
Breda, Maria São João . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-38
msjbreda@fpce.uc.pt
Institute of Cognitive Psychology, University of Coimbra,
Coimbra, Portugal
Brugha, Cathal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-24, FA-27
Cathal.Brugha@ucd.ie
Management Information Systems, University College
Dublin, Dublin 4, Ireland
Breunig, Ulrich . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-42
ulrich.breunig@univie.ac.at
Business Administration, University of Vienna, Vienna, Austria
Bruni, Maria Elena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-45
mariaelena.bruni@unical.it
Department of Mechanical, Energy and Management Engineering, unical, cosenza, italy, Italy
Brewer, Joel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-38
Joel.D.Brewer@conocophillips.com
Geophysical Technology, ConocoPhillips, Houston, TX,
United States
Brunner, Jens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-06
jens.brunner@wiwi.uni-augsburg.de
University of Augsburg, Germany
Brewster, Christopher . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-37
C.A.BREWSTER@aston.ac.uk
Operations and Information Management, Aston University,
Birmingham, United Kingdom
Brezina, Ivan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-02
brezina@euba.sk
Department of Operations Research and Econometrics, University of Economics in Bratislava, Bratislava, Slovakia
Briand, Cyril . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-22
briand@laas.fr
Laas - Cnrs, Toulouse Cedex 4, France
Brieden, Andreas . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-25, TB-45
andreas.brieden@unibw.de
Universität der Bundeswehr München, Neubiberg, Germany
Brimberg, Jack . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-45
Jack.Brimberg@rmc.ca
Department of Business Administration, Royal Military College of Canada, Kingston, Canada
Briskorn, Dirk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-04, FA-13
briskorn@uni-wuppertal.de
University of Wuppertal, Germany
Brison, Valérie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-29
valerie.brison@umons.ac.be
Mathematics and Operational Research, UMONS, Belgium
Brito, Thiago . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-42
tbbrito@gmail.com
Logistics, USP/FAAP, Brazil
Brunner, Markus . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-15, TB-43
markus.brunner@tum.de
TUM School of Management, Technische Universität
München, Munich, Germany
Bruno, Giuseppe . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-03, TB-44
giuseppe.bruno@unina.it
Dipartimento di Ingegneria Industriale, Università Federico
II di Napoli, Napoli, IT, Italy
Brusset, Xavier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-19
xavier.brusset@essca.fr
Centre of expertise and Research in Retailing, ESSCA School
of Management, Boulogne Billancourt, France
Bucarey, Victor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-08
vbucarey@gmail.com
Departamento de Ingeniería Industrial, Universidad de Chile,
Chile
Buchheim, Christoph . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-11
christoph.buchheim@tu-dortmund.de
Fakultät für Mathematik, Technische Universität Dortmund,
Germany
Buchwald, Torsten . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-21
torsten.buchwald@tu-dresden.de
TU Dresden, Germany
Bucksteeg, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-07
michael.bucksteeg@uni-due.de
Chair for Energy Economics, University Duisburg-Essen, Essen, Germany
Builes, Luis Alejandro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-40
luis.builes@colmayor.edu.co
303
AUTHOR INDEX
IFORS 2014 - Barcelona
Facultad de Arquitectura e Ingeniería, Institución Universitaria Colegio Mayor de Antioquia, Medellin, Antioquia,
Colombia
Bulbul, Kerem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-12, FB-17
bulbul@sabanciuniv.edu
Manufacturing Sys. & Industrial Eng., Sabanci University,
Istanbul, Turkey
Bulbul, Pinar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-19
pinar.bulbul@metu.edu.tr
Middle East Technical University, Ankara, Turkey
Bulgarini, Niccolo’ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-41
niccolo.bulgarini@unifi.it
Dipartimento di Ingegneria dell’Informazione, Universita’
degli Studi di Firenze, Florence, Tuscany, Italy
Buljubasic, Mirsad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-28
mirsad.buljubasic@mines-ales.fr
LGI2P Research Center, Ecole des Mines d’Ales, Nimes,
Gard, France
gburlak@uaem.mx
Centro de Investigaciones en Ingeniería y Ciencias Aplicadas,
Universidad Autónoma del Estado de Morelos, Cuernavaca,
Mexico
Busing, Frank M.T.A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-42
busing@fsw.leidenuniv.nl
Leiden University, Leiden, Netherlands
Buskens, Erik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-39
e.buskens@umcg.nl
Department of Epidemiology, University Medical Centre
Groningen, Groningen, Netherlands
Buttrey, Samuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-22
buttrey@nps.edu
Operations Research, Naval Postgraduate School, Monterey,
CA, United States
Büyükköroğlu, Taner. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-07
tbuyukkoroglu@anadolu.edu.tr
Mathematics, Anadolu University, Eskisehir, Turkey
Bull, Simon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-01, MA-28
simbu@dtu.dk
Management Engineering, The Technical University of Denmark, Denmark
Bychkov, Ilya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-39
il.bychkov@gmail.com
National Research University Higher School of Economics,
Russian Federation
Bullejos Gonzalez, Manuel . . . . . . . . . . . . . . . . . . . . . . . . . . HE-04
manuel.bullejos@upc.edu
UPC, Spain
Caballero, Rafael . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-37, TD-37
rafael.caballero@uma.es
Applied Economics Mathematic, University Malaga, Malaga,
Spain
Bunder, Rachel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-15
Rachel.Bunder@uon.edu.au
School of Mathematics and Physical Sciences, University of
Newcastle, Callaghan, NSW, Australia
Bunn, Derek . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-09, TB-10
DBunn@london.edu
London Business School, London, United Kingdom
Burger, Alewyn . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-11, HE-17
apburger@sun.ac.za
Department of Logistics, Stellenbosch University, Stellenbosch, Western Cape, South Africa
Burger, Katharina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-38
katharina.burger@bristol.ac.uk
Civil Engineering, University of Bristol, Bristol, United
Kingdom
Burgholzer, Wolfgang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-33
wolfgang.burgholzer@wu.ac.at
Department of Information Systems and Operations, WU Vienna University of Economics and Business, Austria
Buriol, Luciana S. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-10
lsburiol@inf.ufrgs.br
Universidade Federal do Rio Grande do Sul, Porto Alegre,
Brazil
Burkart, Christian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-31
cburkart@wu.ac.at
Institute for Transport and Logistics Management, WU Vienna, Vienna, Austria
Caballini, Claudia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-05
claudia.caballini@unige.it
DIBRIS - Department of Informatics, Bioengineering,
Robotics and System Engineering. CIELI - Italian Centre
of Excellence in Integrated Logistics, University of Genova,
Genova, Italy, Italy
Cabo Nodar, Marta . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-14
marta.cabo@itam.mx
Department of Mathematics, Instituto Tecnológico
Autónomo de México, México, D.F., Mexico
Cabra, Hermilo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-35
hcabra2@its.jnj.com
Ethicon Surgical Care, Cincinnati, Ohio, United States
Cabrejos, Juan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-21
juan.cabrejos@outlook.com
Pontificia Universidad Católica del Perú, Peru
Cabrera, Guillem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-41
gcabreraa@uoc.edu
Universitat Oberta de Catalunya, Spain
Cabrera-Ríos, Mauricio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-18
mauricio.cabrera1@upr.edu
Industrial Engineering, University of Puerto Rico at
Mayagüez, Mayagüez, PR, United States
Cacchiani, Valentina . . . . . . . . . . . . . . . . . . . . . . . . . HA-01, TB-11
valentina.cacchiani@unibo.it
DEI, University of Bologna, Bologna, Italy
Burkhardt, Thomas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-30
tburkha@uni-koblenz.de
Campus Koblenz, IfM, Universitaet Koblenz-Landau,
Koblenz, Germany
Cada, Roman . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-09
cadar@kma.zcu.cz
Department of Mathematics, University of West Bohemia,
Czech Republic
Burlak, Gennadiy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-35
Cadarso, Luis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-01, MD-03
304
IFORS 2014 - Barcelona
luis.cadarso@urjc.es
Rey Juan Carlos University, Fuenlabrada, Madrid, Spain
AUTHOR INDEX
Faculdade de Engenharia, Universidade do Porto, Porto, Portugal
Cadenillas, Abel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-30
abel@ualberta.ca
Mathematical Sciences, University of Alberta, Edmonton,
Alberta, Canada
Camara Pereira, Carlos Eduardo da . . . . . . . . . . . . . . . . . FB-03
carloseduardo@iag.puc-rio.br
IAG - Departamento de Administração, PUC-Rio, Rio de
Janeiro, Rio de Janeiro, Brazil
Cai, Desmond . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-20
wccai@caltech.edu
California Institute of Technology, Pasadena, United States
Cambazard, Hadrien . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-21
hcambazard@gmail.com
Operations Research, G-SCOP, Grenoble, France
Cai, Shun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-43
caishun@xmu.edu.cn
Management Science, Xiamen University, China
Camiz, Sergio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-45
sergio.camiz@uniroma1.it
Dipartimento di Matematica Guido Castelnuovo, Sapienza
Università di Roma, Roma, Roma, Italy
Cailloux, Olivier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-24
olivier.cailloux@uva.nl
Institute for Logic, Language and Computation, University
of Amsterdam, Netherlands
Camponogara, Eduardo . . . . . . . . . . . . . . . . . . . . . . FB-13, FA-28
eduardo.camponogara@ufsc.br
Federal University of Santa Catarina, Brazil
Çağlıyangil, Mehmet . . . . . . . . . . . . . . . . . . . . . . . . FB-40, ME-42
mehmet.cagliyangil@gmail.com
Business Administration, Dokuz Eylül University, izmir,
izmir, Turkey
Campora, Simone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-01
simone.campora@libero.it
Department of Civil, Architectural and Environmental Engineering, ’Federico II’ University of Naples, Naples, Italy
Çakır, Volkan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-15, HD-15
volkancakir@arel.edu.tr
Industrial Engineering, Istanbul Arel University, Istanbul,
Turkey
Campos Hernández, Gonzalo Eduardo . . . . . . . . . . . . . . ME-14
gonzalo.campos.h@gmail.com
Ingeniería Industrial, Universidad Autónoma de Chile, Talca,
Del Maule, Chile
Calabrese, Raffaella . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-38
rcalab@essex.ac.uk
University of Essex, Colchester, United Kingdom
Campos, Vicente . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-45
campos@uv.es
Estadistica i Investigacio Operativa, University of Valencia,
Burjassot, Spain
Calafat Marzal, Consuelo . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-36
macamar3@esp.upv.es
Economy and Social Sciences, Universitat Politecnica de Valencia, Valencia, Valencia, Spain
Calderon, Jaime . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-08
jpipe36@hotmail.com
University Santiago de Cali, Cali, Valle del Cauca, Colombia
Çalış, Aslı. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-16
aslicalis@gazi.edu.tr
Industrial Engineering, Gazi University, Ankara, Turkey
Çalık, Ahmet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-39
ahmetcalik@selcuk.edu.tr
Statistics, Selcuk University, Konya, Turkey
Calle Salazar, Juan Esteban . . . . . . . . . . . . . . . . . . . . . . . . . FA-23
juan.calle@decisionware.net
DecisionWare, Colombia
Calleja, Gema . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-13
gema.calleja@upc.edu
IOC-DOE, UPC, Barcelona, Spain
Camps, Jordi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-41
j.camps19@gmail.com
School of Engineering Barcelona, Universitat Politecnica de
Catalunya, La Garriga, Catalunya, Spain
Canales, Cristian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-07
ccanales@ifop.cl
Instituto de Fomento Pesquero, Valparaiso, Chile
Canca, David . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-01, HD-01
dco@us.es
School of Engineers, University of Seville., Seville, Spain
Candia-Véjar, Alfredo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-31
acandia@utalca.cl
Departamento de Modelación y Gestión Industrial, Universidad de Talca, Curicó, Chile
Canelas, Alfredo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-17
acanelas@fing.edu.uy
Instituto de Estructuras y Transporte, Facultad de Ingeniería,
Universidad de la República, Montevideo, Uruguay
Calleja, Pedro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-22
calleja@ub.edu
Economical, Financial and Actuarial Mathematics, University of Barcelona, Barcelona, Spain
Cangalovic, Mirjana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-17
canga@fon.bg.ac.rs
Laboratory for Operational Research, Faculty of Organizational Sciences, University of Belgrade, Belgrade, Serbia,
Serbia
Calvete, Herminia I. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-11
herminia@unizar.es
Métodos Estadísticos, Universidad de Zaragoza, Zaragoza,
Spain
Cano, Emilio L. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-20
emilio.lopez@urjc.es
Statistics and Operations Research, Rey Juan Carlos University, Móstoles (Madrid), Spain
Camanho, Ana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-14, MA-35
acamanho@fe.up.pt
Cano, Javier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-31
javier.cano@urjc.es
305
AUTHOR INDEX
IFORS 2014 - Barcelona
Rey Juan Carlos University, Spain
Institute of Computing, UFAM, Manaus, Amazonas, Brazil
Cansu, Ummugulsum . . . . . . . . . . . . . . . . . . . . . . . . TB-12, TD-12
cansuummugulsum@gmail.com
Secondary Science and Mathematics Education, Middle East
Technical University, ankara, Turkey
Caricato, Pierpaolo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-13
pierpaolo.caricato@unisalento.it
Dip.to di Ingegneria dell Innovazione, Università del Salento,
Lecce, LE, Italy
Canzani, Elisa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-03
elisa.canzani@unibw.de
Department of Computer Science, Universität der Bundeswehr München, München, Germany
Carle, Marc-André. . . . . . . . . . . . . . . . . . . . . . . . . . HE-36, MD-36
marc-andre.carle@forac.ulaval.ca
Génie mécanique, Université Laval, Quebec, Quebec, Canada
Cao, Buyang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-40
caobuyang@tongji.edu.cn
School of Software Engineering, Tongji University, Shanghai, China
Cao, Guangming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-45
Guangming.Cao@beds.ac.uk
Business School, University of Bedfordshire, Luton, Bedfordshire, United Kingdom
Carling, Christian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-08
christian.carling@foi.se
Division of Defence Analysis, Swedish Defence Research
Agency, Stockholm, Sweden
Carlo, Hector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-05
hector.carlo@upr.edu
Industrial Engineering Department, University of Puerto Rico
— Mayagüez, Mayagüez, PR, Puerto Rico
Cao, Karl-Kien . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-34
Karl-Kien.Cao@dlr.de
German Aerospace Center (DLR), Stuttgart, Germany
Carlyle, Matthew . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-33
mcarlyle@nps.navy.mil
Operations Research, Naval Postgraduate School, Monterey,
California, United States
Cao, Qi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-39
q.cao@umcg.nl
Department of Epidemiology, University Medical Centre
Groningen, Groningen, Netherlands
Carmona, Carlos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-04
carlos.carmona@upc.edu
inLab FIB, Universitat Politècnica de Catalunya BarcelonaTECH, Barcelona, Spain
Cao, Xi-Ren . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-29
xrcao@sjtu.edu.cn
Shanghai Jiao Tong University, Shanghai, China
Carmona, Manuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-28
mcarmona@palisade.com
Palisade UK Ltd., West Drayton, United Kingdom
Cao, Zhigang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-11
zhigangcao@amss.ac.cn
Chinese Academy of Sciences, Beijing, China
Carneiro, Carlos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-08
digiart_caria@terra.com.br
Computer Modelling, SENAI-CIMATEC, Salvador, Bahia,
Brazil
Capek, Roman . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-08
capekrom@fel.cvut.cz
Department of Control Engineering, Czech Technical University in Prague, Prague, Czech Republic
Caporin, Massimiliano . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-38
massimiliano.capori@unipd.it
University of Padua, Padova, Italy
Cappanera, Paola . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-11
paola.cappanera@unifi.it
Dipartimento di Sistemi e Informatica, University of Florence, Florence, Italy
Caprara, Alberto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-26
alberto.caprara@unibo.it
DEIS, Universita di Bologna, Bologna, Italy
Carapito, Ana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-09
carapito@ubi.pt
Mathematics, University of Beira Interior, Portugal
Cardoen, Brecht . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-39
brecht.cardoen@vlerick.com
Vlerick Business School, Belgium
Cardonha, Carlos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-13
chcardo@br.ibm.com
Systems of Engagement and Insight, IBM Research - Brazil,
São Paulo, São Paulo, Brazil
Cardoso Dias, Bruno . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-11
bruno.dias@icomp.ufam.edu.br
306
Caro, Felipe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-08
fcaro@anderson.ucla.edu
UCLA Anderson School of Management, Los Angeles, CA,
United States
Caro, Gegoire . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-34
caro@swissquant.ch
swissQuant Group AG, Zürich, Switzerland
Caron, Filip . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-25
filip.caron@econ.kuleuven.be
Decision Sciences and Information Management, KU Leuven, Leuven, Belgium
Carpentier, Pierre-Luc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-20
plcarpentier@gmail.com
CIRRELT and MAGI, École Polytechnique de Montréal,
Montréal, Québec, Canada
Carrasco, Miguel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-17
migucarr@gmail.com
Facultad de Ingeniería y Ciencias Aplicadas, Universidad de
los Andes, Chile
Carreras, Ashley . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-38
acarreras@dmu.ac.uk
Leicester Business School, De Montfort University, Leicester, United Kingdom
Carrizosa, Emilio . . . . . . . . . . . . . . . . . . . . . TE-21, TB-25, HB-31
ecarrizosa@us.es
Estadistica e Investigacion Operativa, Universidad de Sevilla,
IFORS 2014 - Barcelona
Sevilla, Spain
Carstens, Birte . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-08
birte.carstens@student.kit.edu
Karlsruhe Institute Of Technology, Germany
Casabayó, Monica . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-45
monica.casabayo@esade.edu
Marketing, ESADE-URL, Barcelona, Barcelona, Spain
Casacio, Luciana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-28
luciana@densis.fee.unicamp.br
FEEC, Unicamp, Campinas, São Paulo, Brazil
Casas Riascos, Jose de Jesus . . . . . . . . . . . . . . . . . . . . . . . . ME-40
Jose.Casas2205@gmail.com
School of Industrial Engineering, Universidad del Valle, Cali,
Valle del Cauca, Colombia
Casas, Jordi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-04
casas@aimsun.com
Barcelona
Casas-Méndez, Balbina. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-21
balbina.casas.mendez@usc.es
Universidade de Santiago de Compostela, Santiago de Compostela, Spain
Casazza, Marco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-28
marco.casazza@unimi.it
OptLab, Università degli Studi di Milano, Italy
Casorrán-Amilburu, Carlos . . . . . . . . . . . . . . . . . . . . . . . . . FB-41
casorranamilburu@gmail.com
Informatique, Université Libre de Bruxelles, Bruxelles, Belgium
Casquilho, Miguel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-44
mcasquilho@ist.utl.pt
Dept. of Chemical Engineering, Istituto Superior Tecnico,
Lisbon, Portugal
AUTHOR INDEX
Cataldo, Alejandro . . . . . . . . . . . . . . . . . . . . . . . . . . TB-02, MB-15
aecatald@uc.cl
Departamento de Ingeniería Industrial y de Sistemas, Pontifica Universidad Católica de Chile, Chile
Catanzaro, Daniele . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-11
dacatanz@ulb.ac.be
Operations, Rijksuniversiteit Groningen, Groningen, Netherlands
Cattrysse, Dirk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-01
dirk.cattrysse@cib.kuleuven.be
Centre for Industrial Management/Traffic & Infrastructure,
KU Leuven, Heverlee, Belgium
Catusse, Nicolas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-13
nicolas.catusse@grenoble-inp.fr
Grenoble INP / G-SCOP, France
Cauley, Fattaneh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-35
cauley@purdue.edu
Quantitative Methods, Purdue University, West Lafayette,
IN, United States
Caux, Stéphane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-08
caux@laplace.univ-tlse.fr
LAPLACE, Toulouse, France
Cavalcante, Victor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-13
victorf.cavalcante@gmail.com
IBM Research Brazil, Campinas
Cavdaroglu, Nur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-19
nur.cavdaroglu@khas.edu.tr
Business Administration, Kadir Has University, İstanbul,
Turkey
Cavellucci, Celso . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-09
ccavellucci@gmail.com
Universidade Estadual de Campinas, Campinas, Brazil
Castañer-Garriga, Anna . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-24
acastaner@ub.edu
Universitat de Barcelona, Barcelona, Spain
Cay, Tayfun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-04
tcay@selcuk.edu.tr
Geomatic Engineering, University of selcuk, Konya, Turkey
Castaing, Jeremy . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-03, TB-06
jctg@umich.edu
Industrial and Operations Engineering, U. Michigan, Ann
Arbor, United States
Cáceres, Ma Teresa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-36
caceres@us.es
Matemática Aplicada I, Universidad de Sevilla, Sevilla, Spain
Castellini, Cesare . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-36
cesare.castellini@unipg.it
Department of Agricultural, Food and Environmental Sciences, University of Perugia, Perugia, Italy, Italy
Castellucci, Pedro B. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-32
pbc@icmc.usp.br
Universidade de São Paulo, São Carlos, SP, Brazil
Castro, Jordi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-17, TE-17
jordi.castro@upc.edu
Dept. of Statistics and Operations Research, Universitat Politecnica de Catalunya, Barcelona, Catalonia, Spain
Castro, Pedro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-42
pedrin_horacio@hotmail.com
STATISTIC, UNESP, Presidente Prudente, São Paulo, Brazil
Catalão, João P. S. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-09
catalao@ubi.pt
University of Beira Interior, Covilhã, Portugal
Cayir, Beyzanur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-45
beyzanur_cayir@hotmail.com
Industrial Engineering, Hitit University, ÇORUM, Turkey
Cayirli, Tugba . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-39
tugba.cayirli@ozyegin.edu.tr
Management, Ozyegin University, Istanbul, Turkey
Côté, Jean-François . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-41
Jean-Francois.Cote@fsa.ulaval.ca
Opérations et systèmes de décision, Université Laval,
Québec, Québec, Canada
Cechlarova, Katarina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-12
katarina.cechlarova@upjs.sk
Institute of Mathematics, P.J. Safarik University, Kosice, Slovakia
Ceciliano Meza, Jose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-29
jlcecilianomeza@wichita.edu
Ingustrial and Manufacturing Engineering Department, Wichita State University, Wichita, KS, United States
307
AUTHOR INDEX
IFORS 2014 - Barcelona
Çelebi, Emre . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-10
ecelebi@khas.edu.tr
Industrial Engineering, Kadir Has University, Istanbul,
Turkey
Cello, Marco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-31
marco.cello@dist.unige.it
University of Genoa, Italy
Centeno Hernáez, Efraim . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-10
efraim.centeno@upcomillas.es
Instituto de Investigación Tecnológica, Universidad Pontificia Comillas, Madrid, Spain
Ceparano, Maria Carmela . . . . . . . . . . . . . . . . . . . . . . . . . . ME-25
milena.ceparano@gmail.com
Department of Economics and Statistics, University of
Naples Federico II, Napoli, NA, Italy
Ceppi, Sofia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-06
soceppi@microsoft.com
Microsoft Research, Cambridge, United Kingdom
Cerdeira, J. Orestes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-01
orestes@isa.utl.pt
Matematica, Inst. Sup.de Agronomia, Lisboa, Portugal
Cerny, Michal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-42
cernym@vse.cz
Department of Econometrics, University of Economics,
Prague, Prague, Czech Republic
Ceron Naranjo, Katherine . . . . . . . . . . . . . . . . . . . . . . . . . . ME-40
kathe.ceron20@gmail.com
School of Industrial Engineering, Universidad del Valle, Cali,
Valle, Colombia
Ceselli, Alberto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-11
alberto.ceselli@unimi.it
Dipartimento di Informatica, Università degli Studi di Milano, Crema, CR, Italy
Ceyhan, Gökhan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-18
gceyhan@metu.edu.tr
Industrial Engineering, Middle East Technical University,
Ankara, Turkey
mithunchakraborty@seas.wustl.edu
Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri, United States
Chakraborty, Soumyakanti . . . . . . . . . . . . . . . . . . . . . . . . . HD-15
soumyakc@xlri.ac.in
Informations Systems, XLRI, Jamshedpur, Jamshedpur,
Jharkhand, India
Chan, Pui Yin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-29
pychan@se.cuhk.edu.hk
System Engineering and Engineering Management, The Chinese University of Hong Kong, Hong Kong, N/A, China
Chandra, Saurabh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-05
saurabh@iimidr.ac.in
Operations Management, Indian Institute of Management Indore, Indore, MP, India
Chang, Chiao-Chen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-42
aka@mail.ndhu.edu.tw
International Business, National Dong Hwa University,
Hualien, Taiwan
Chang, Dong Shang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-23
changds@mgt.ncu.edu.tw
Business Administration, National Central of University,
Jhongli, Taiwan
Chang, Gang-Len . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-04
gang@umd.edu
Department of Civil & Environmental Engineering, University of Maryland, College Park, Maryland, United States
Chang, Kuo-Hao . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-27
chang@mx.nthu.edu.tw
Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchy, Taiwan
Chang, Kuochung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-27
kcchang@mail.ndhu.edu.tw
International Business, National DongHwa University,
Hualien, Taiwan
Chang, Mei-Shiang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-40
mschang@cycu.edu.tw
Chung Yuan Christian University, Taiwan
Chaabane, Amin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-40
amin.chaabane@etsmtl.ca
Departement of Automated Manufacturing Engineering,
École de Technologie Supérieure, Montreal, Quebec, Canada
Chang, Tsung-Sheng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-02
tsc@nctu.edu.tw
Department of Transportation and Logistics Management,
National Chiao Tung University, Taiwan
Chaabane, Nadia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-22
nadia.chaabane@laas.fr
LAAS-CNRS, Toulouse, France
Chao, Yu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-14, TB-14
yc@chu.edu.tw
Business Administration, Chung Hua University, Hsinchu,
Taiwan
Chaipunya, Parin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-37
chaipunya.p@gmail.com
Mathematics, King Mongkut’s University of Technology
Thonburi, Bangkok, Thailand
Chaiwuttisak, Pornpimol . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-39
molchaiwuttisak@outlook.com
Operational Research, University of Southampton,
Southampton, Hamsphire, United Kingdom
Chakraborty, Arnab . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-23
arnab.d.chakraborty@accenture.com
Accenture Analytics, Bangalore, India
Chakraborty, Mithun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-22
308
Chassein, André . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-01
chassein@mathematik.uni-kl.de
Mathematics, Technische Universität Kaiserslautern, Kaiserslautern, Germany
Chatha, Kamran . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-04
kamranali@lums.edu.pk
Lahore University of Management Sciences, Lahore, Pakistan
Chaves, Antônio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-05
antonio.chaves@unifesp.br
Federal São Paulo State University, São José dos Campos,
São Paulo, Brazil
IFORS 2014 - Barcelona
Chaves, Antonio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-11
antoniochaves@gmail.com
UNIFESP, Brazil
Chavez - Hurtado, Jose Luis . . . . . . . . . . . . . . . . . . . . . . . . . TD-19
martedead@gmail.com
Metodos Cuantitativos, CUCEA, Universidad de Guadalajara, Mexico, Zapopan, Jalisco, Mexico
Chelouah, Rachid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-40
rc@eisti.eu
Computer Science, EISTI, Cergy, France
Chen, Argon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-19
achen@ntu.edu.tw
Industrial Engineering, National Taiwan University, Taiwan
Chen, Bo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-04
b.chen@warwick.ac.uk
Warwick Business School, University of Warwick, Coventry,
United Kingdom
Chen, Chao . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-18, ME-44
changshacc@163.com
National University of Defense Technology, Science and
Technology on Information Systems Engineering Laboratory, changsha, China
Chen, Chie-bein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-26
cbchen@mail.ndhu.edu.tw
International Business, National Dong Hwa University,
Hualien, Taiwan
Chen, Dipeng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-09
chen_dpeng@hotmail.com
Centrica Storage, Staines, United Kingdom
Chen, Jian-Shun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-37
m09903032@chu.edu.tw
Chung Hua University, Hsinchu, Taiwan
Chen, Jiang Hang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-01
jianghang.chen@epfl.ch
EPFL, Switzerland
Chen, Ming Yuan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-37
mychen@me.concordia.ca
Concordia University, Canada
Chen, Qiushi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-39
chenqiushi0812@gatech.edu
Industrial and Systemd Engineering, Georgia Institute of
Technology, Atlanta, GA, United States
Chen, Sheu-Hua . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-34, TE-43
shchen@ncut.edu.tw
Distribution Management Dept., National Chin-Yi University
of Technology, Taichung, Taiwan
Chen, Wen-Chih . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-10
wenchih@faculty.nctu.edu.tw
Dept of Industrial Engineering and Management, National
Chiao Tung University, Hsinchu, Taiwan
Chen, Wenyi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-33
wchen@zlc.edu.es
MIT-Zaragoza International Logistics Program, Spain
Chen, Xin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-13
chenx_dlut@163.com
School of Software, Dalian University of Technology, Dalian,
AUTHOR INDEX
Liaoning Province, China
Chen, Xi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-33
chen1664@umn.edu
Industrial and Systems Engineering, University of Minnesota,
Minneapolis, Minnesota, United States
Chen, Xujin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-06, TD-11
xchen@amss.ac.cn
Institute of Applied Mathematics, Academy of Mathematics
and Systems Science, Chinese Academy of Sciences, Beijing, China
Chen, Yi-Chih . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-26
poseidon0112@yahoo.com.tw
Department of Mathematical Sciences, Taipei, Taiwan
Chen, Yi-chun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-23
ycchcu@gmail.com
BA, NCU, Jhongli, Taiwan
Chen, Ying-Ju . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-22
chen@ieor.berkeley.edu
UC Berkeley, Berkeley, CA, United States
Chen, Yong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-20
yong-chen@uiowa.edu
Mechanical and Industrial Engineering, University of Iowa,
Iowa City, Iowa, United States
Chen, Yu-Wang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-27
Yu-wang.chen@mbs.ac.uk
Manchester Business School, Manchester, United Kingdom
Chen, Yubo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-23
chenyubo@sem.tsinghua.edu.cn
School of Economics and Management, Tsinghua University,
Beijing, China
Chen, Zhong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-32
ZhongChen@baf.cuhk.edu.hk
Decision Science and Managerial Economics, The Chinese
University of Hong Kong, Hong Kong
Chenavaz, Régis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-07
r.chenavaz@gmail.com
KEDGE Business School, France
Cheng, Guangquan . . . . . . . . . . . . . . . . . . . . . . . . . . FB-18, ME-44
cougar008@sina.com
National University of Defense Technology, Science and
Technology on Information Systems Engineering Laboratory, Changsha, China
Chernikov, Dmitry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-14
dmitry-chernikov@uiowa.edu
Mechanical and Industrial Engineering, University of Iowa,
Iowa City, IA, United States
Cherri, Adriana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-21
adriana@fc.unesp.br
Mathematics, UNESP - Bauru, Bauru, SP, Brazil
Chesney, Marc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-08
chesney@isb.uzh.ch
Swiss Banking Institute, University of Zurich, Zurich,
Switzerland
Chhatwal, Jagpreet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-39
JChhatwal@mdanderson.org
Department of Health Services Research, MD Anderson Cancer Center, Houston, TX, United States
309
AUTHOR INDEX
IFORS 2014 - Barcelona
Chiabaut, Nicolas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-04
nicolas.chiabaut@entpe.fr
Université de Lyon, ENTPE / IFSTTAR, Vaulx en Velin,
France
Chiang, Johannes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-13
jkchiang@nccu.edu.tw
Management Information Systems, National Chengchi University, Taipei, Taiwan
Chin, Yang-Chieh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-31
yccjerry@gmail.com
International Business, Asia University, Taichung, Taiwan
Chiou, Hua-Kai . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-45
hkchiou@cc.cust.edu.tw
Department of International Business, China University of
Science and Technology, Taipei, Taiwan
Chiou, Suh-Wen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-04
chiou@mail.ndhu.edu.tw
Information Management, National Dong Hwa University,
Hualien, Taiwan
Chipoyera, Honest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-14
honest.chipoyera@wits.ac.za
School of Statistics & Actuarial Science, University of of the
Witwatersrand, Johannesburg, Gauteng, South Africa
Choe, Byunghak . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-42
cbh@gwnu.ac.kr
Metal and Advanced Materials Engineering, GangneungWonju National University, Gangneung, GW, Korea, Republic Of
Choi, Dong Gu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-20
dgchoi@kier.re.kr
Korea Institute of Energy Research, Daejeon, Korea, Republic Of
Choi, Jin Young . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-13
choijy@ajou.ac.kr
Industrial Engineering, Ajou University, Suwon, Keonggido, Korea, Republic Of
Choi, Kyungim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-23
kichoi@ts2020.kr
Safe Research Office, Korea Transportation Safety Authority,
Ansan-si, Gyeonggi-do, Korea, Republic Of
Chong, Josephine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-35
chongsc@cuhk.edu.hk
The Chinese University of Hong Kong, Hong Kong
Choo, Eng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-29
choo@sfu.ca
Faculty of Business Administration, Simon Fraser University,
Burnaby, BC, Canada
Trondheim, Norway
Christmann, Fernanda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-14
fernanda.christmann@grad.ufsc.br
Department of Information Science, Federal University of
Santa Catarina, Florianopolis, SC, Brazil
Christodoulou, Giorgos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-22
gchristo@liv.ac.uk
Computer Science, University of Liverpool, Liverpool,
United Kingdom
Chu, Chengbin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-19
chengbin.chu@ecp.fr
Ecole Centrale Paris, Paris, France
Chu, Ta-Chung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-37
tcchu@mail.stust.edu.tw
Department of Management and Information Technology,
Southern Taiwan University of Science and Technology, Taiwan
Chua, Geoffrey A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-04
gbachua@ntu.edu.sg
Nanyang Business School, Nanyang Technological University, Singapore, Singapore
Chung, Beom-suk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-42
bumdol03@snu.ac.kr
Seoul National University, Korea, Republic Of
Chung, Ki Ho . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-37
khchung@ks.ac.kr
Kyungsung University, Busan, Korea, Republic Of
Church, Richard . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-18, TD-36
church@geog.ucsb.edu
Geography, University of California, Santa Barbara, Santa
Barbara, CA, United States
Ciarallo, Frank . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-08
frank.ciarallo@wright.edu
College of Engineering & Computer Science, Wright State
University, Dayton, Ohio, United States
Cicek, Eren . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-37
ecicek13@ku.edu.tr
Industrial Engineering, Koc University, Istanbul, Turkey
Čičková, Zuzana. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-02
cickova@euba.sk
Department of Operations Research and Econometrics, University of Economics in Bratislava, Bratislava, Slovakia
Cifuentes Rubiano, Julián . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-10
julian.cifuentes@upc.edu
Operations Research, Technical University of Catalonia,
Barcelona, Cataluña, Spain
Chow, Joseph . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-25, HD-25
joseph.chow@gmail.com
Civil Engineering, Ryerson University, Toronto, Canada
Cigdem Baz, Berna . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-33
bcigdem@hvkk.tsk.tr
Scientific Decision Support Department, Turkish Air Force
Command, Çankaya, Ankara, Turkey
Christensen, Adam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-07
adam.christensen@jhu.edu
Johns Hopkins University, Baltimore, United States
Çimen, Emre . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-16
ecimen@anadolu.edu.tr
Industrial Engineering, Anadolu Universty, Eskişehir, Turkey
Christiansen, Marielle . . . . . . . . . HA-05, HD-05, TA-05, TE-05
marielle.christiansen@iot.ntnu.no
Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology,
Ciomek, Krzysztof . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-24
k.ciomek@gmail.com
Poznan University of Technology, Poznań, Poland
310
IFORS 2014 - Barcelona
Ciuffo, Biagio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-04
biagio.ciuffo@jrc.ec.europa.eu
Institute for Energy and Transport, European Commission
Joint Research Centre, Ispra, Italy
Claassen, G.D.H. (Frits) . . . . . . . . . . . . . . . . . . . . . HB-08, MB-18
frits.claassen@wur.nl
Operations Research and Logistics, Wageningen University,
Wageningen, Netherlands
Claramunt, M. Mercè . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-24
mmclaramunt@ub.edu
Universitat de Barcelona, Barcelona, Spain
Clark, Nick . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-36
nickclark1000@gmail.com
Trapeze Group, Toronto, Canada
Clarke, Nancy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-17
nancy.clarke@acadiau.ca
Mathematics and Statistics, Acadia University, Wolfville,
Nova Scotia, Canada
Claro, João . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-36
jclaro@fe.up.pt
INESC Porto, Faculty of Engineering, University of Porto,
Portugal
Clausen, Uwe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-06, HD-35
Uwe.Clausen@iml.fraunhofer.de
Director, Fraunhofer-Institute for Materialflow and Logistics
(IML), Dortmund, Germany
Clemente, Gabriela . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-36
gclemente@tal.upv.es
Tecnología de Alimentos, Universitat Politecnica de Valencia, Valencia, Valencia, Spain
Cleophas, Catherine . . . . . . . . . . . . . . . . . . . . . . . . . TA-03, HD-40
catherine.cleophas@rwth-aachen.de
School of Business and Economics, RWTH Aachen, Aachen,
Germany
Cliville, Vincent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-31
vincent.cliville@univ-savoie.fr
University of Savoie, Annecy, France
Coakes, Elayne . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-34
coakese@westminster.ac.uk
Business Information and Management, Westminster Business School, London, United Kingdom
Coban, Elvin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-13
elvin.coban@ozyegin.edu.tr
Industrial Engineering, Ozyegin University, Istanbul, Turkey
Codina, Esteve . . . . . . . . . . . . . . . FA-01, HA-01, ME-01, HD-16
esteve.codina@upc.edu
Statistics and Operational Research, UPC, Barcelona, Spain
Coelho Jr, Claudionor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-41
coelho@dcc.ufmg.br
Computer Science Department, UFMG, Belo Horizonte, Minas Gerais, Brazil
Coelho, Bernardete . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-43
bcoelho@ua.pt
Department of Mechanical Engineering, University of
Aveiro, Aveiro, —, Portugal
Coelho, Igor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-06
igor.machado@gmail.com
AUTHOR INDEX
Institute of Computing, Fluminense Federal University,
Niterói, Rio de Janeiro, Brazil
Coelho, Leandro . . . . . . . . . . . . . . . . . . . . . . HA-01, TB-02, FB-06
leandro.coelho@cirrelt.ca
Operations and Decision Systems, Université Laval, Quebec,
QC, Canada
Coemert, Alican . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-12
acocomert@gmail.com
ASELSAN, Ankara, Turkey
Cohen Kadosh, Simona . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-29
cohensim@post.bgu.ac.il
Ben-Gurion University, Israel
Cohen-Vernik, Dinah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-15
dv6@rice.edu
Jones Graduate School of Business, Rice University, United
States
Cohn, Amy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-03, TB-06
amycohn@umich.edu
University of Michigan, United States
Coletsos, John . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-21
coletsos@math.ntua.gr
Applied Mathematical and Physical Sciences, National Technical University of Athens, Athens, Attica, Greece
Collado, Ricardo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-20
collado.ricardo@gmail.com
Howe School of Technology Management, Stevens Institute
of Technology, United States
Collignan, Antoine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-18
antoine.collignan@cirad.fr
UMR QualiSud, Food Process Engineering Research Unit,
Montpellier SupAgro, Montpellier Cedex 5, France
Colombi, Marco . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-02, MA-11
marco.colombi@ing.unibs.it
Department of Information Engineering, University of Brescia, Brescia, Italy
Comas Marti, Joana M. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-07
joana.comas@epfl.ch
TOM, EPFL, Lausanne, Switzerland
Cominetti, Roberto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-28
rccc@dii.uchile.cl
Industrial Engineering, Universidad de Chile, Santiago, Chile
Conejo, Antonio J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-09
Antonio.Conejo@uclm.es
Electrical Engineering, University of Castilla - La Mancha,
Ciudad Real, Spain
Conlong, Desmond . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-07
Des.Conlong@sugar.org.za
Conservation Ecology and Entomology, Stellenbosch University, Stellenbosch, Western Cape, South Africa
Constantino, Miguel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-36
miguel.constantino@fc.ul.pt
University of Lisbon, Lisbon, Portugal
Contreras, Ivan . . . . . . . . TD-02, FA-03, HB-31, HE-31, HE-37
icontrer@encs.concordia.ca
Concordia University, Montreal, Canada
Contreras, Javier . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-09, ME-10
311
AUTHOR INDEX
IFORS 2014 - Barcelona
Javier.Contreras@uclm.es
University of Castilla - La Mancha, Ciudad Real, Spain
Instituto de Engenharia Mecânica e Gestão Industrial, Porto,
Portugal
Contreras-Huerta, Luis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-23
lsebastian.contrerash@gmail.com
Universidad Diego Portales, Santiago, Chile
Correia, Paulo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-08, TD-18
pcorreia@fem.unicamp.br
Energy Department, Unicamp, Campinas, SP, Brazil
Copado Méndez, Pedro Jesús . . . . . . . . . . . . . . . . . . . . . . . . TD-41
pedrojesus.copado@urv.cat
Departament d’Enginyeria Química, Universidad Rovira i
Virgili, Spain
Corrente, Salvatore . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-24
salvatore.corrente@unict.it
Economics and business, University of Catania, Catania,
Italy, Italy
Corberan, Angel . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-02, ME-02
angel.corberan@uv.es
Estadistica e Investigacion Operativa, Universitat de Valencia, Burjasot, Valencia, Spain
Cortés, Cristián . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-02, MD-44
ccortes@ing.uchile.cl
Civil Engineering Department, Universidad de Chile, Santiago, Chile
Corbett, Charles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-08
charles.corbett@anderson.ucla.edu
UCLA Anderson School of Management, Los Angeles, CA,
United States
Costa e Silva, Eliana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-01
eos@estgf.ipp.pt
ESTGF - Polytechnic of Porto, Felgueiras, Portugal
Corchero, Cristina . . . . . . . . . . . MA-10, MB-10, ME-10, TD-10
ccorchero@irec.cat
Electrical Engineering Research Area, Catalonia Institute for
Energy Research, Sant Adria del Besos, Spain
Cordeau, Jean-François . . . . . . . . . . . . . . . . . . . . . MB-36, HA-41
jean-francois.cordeau@hec.ca
Department of Logistics and Operations Management, HEC
Montréal, Montreal, Canada
Cordeiro, Isabel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-34
icordeiro@eeg.uminho.pt
Escola de Economia e Gestão, Universidade do
Minho/CEMAPRE, ISEG, Braga, Portugal
Cordova, Marcelo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-26
cordova.mm@gmail.com
Electrical Engineering, Federal University of Santa Catarina,
Florianopolis, Santa Catarina, Brazil
Corman, Francesco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-01
f.corman@tudelft.nl
Transport Engineering and Logistics, Maritime and Transport
Technology, Delft University of Technology, Delft, Netherlands
Cornejo, Oscar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-18
ocornejo@ucsc.cl
Ingeniería Industrial, Facultad de Ingenieria-Universidad
Católica de Concepción, Concepcion, Concepcion, Chile
Corominas, Albert . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-13, TB-44
albert.corominas@upc.edu
IOC-DOE, UPC, Barcelona, Spain
Correa Morales, Juan Carlos . . . . . . . . . . . . . . . . . . . . . . . ME-09
jccorrea@unal.edu.co
Estadística, Universidad Nacional de Colombia, Medellín,
Antioquia, Colombia
Correa, Rogrigp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-15
rodrigo.0305@hotmail.com
UNILASALLE, Porto Alegre, Brazil
Correia, Aldina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-26
aic@estgf.ipp.pt
Mathematics, Estgf-ipp / Ciicesi, Amarante, Portugal
Correia, Nuno . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-27
nuno.correia@inegi.up.pt
312
Costa, Alysson M. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-32
alysson.costa@unimelb.edu.au
Department of Mathematics and Statistics, University of Melbourne, Melbourne, VIC, Australia
Costa, Ana Paula . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-31, TE-42
apcabral@hotmail.com
Management Engineering, Universidade Federal de Pernambuco, Recife, PE, Brazil
Costa, M. Teresa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-27
mco@isep.ipp.pt
ISEP - School of Engineering, Polytechnic Institute of Porto,
Porto, Portugal
Costa, Virginia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-11
virscosta@gmail.com
COPPE, Federal University of Rio de Janeiro, Rio de Janeiro,
Rio de Janeiro, Brazil
Couce Vieira, Aitor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-31
aitorcouce@securenok.com
Secure-NOK AS, Stavanger, Norway
Cousins, Simon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-25
simon.cousins.10@ucl.ac.uk
Computer Science, University College London, London,
United Kingdom
Coussement, Kristof . . . . . . . . . . . . . . . . . . FB-40, HE-40, HB-42
k.coussement@ieseg.fr
IESEG School of Management, Lille, France
Couto, Fernanda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-12
nandavdc@gmail.com
COPPE/sistemas, UFRJ, Nova Iguaçu, Rio de Janeiro, Brazil
Coves, Anna M. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-32
anna.maria.coves@upc.edu
Institute of Industrial and Control Engineering, UPC,
Barcelona, Spain
Crainic, Teodor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-02
TeodorGabriel.Crainic@cirrelt.ca
CIRRELT, Montreal, Canada
Crama, Yves . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-02
Y.Crama@ulg.ac.be
HEC - Management School, University of Liège, Liege, Belgium
IFORS 2014 - Barcelona
AUTHOR INDEX
Cranmer, Alexana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-20
acranmer@umass.edu
University of Massachusetts, United States
Culus, Jean-François . . . . . . . . . . . . . . . . . . . . . . . . HB-11, MA-12
culus@univ-tlse2.fr
UAG, Fort de France, Martinique
Crawford, Broderick . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-25
broderick.crawford@ucv.cl
Pontificia Universidad Catolica de Valparaiso, Chile
Cunha, Claudio B. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-20
cbcunha@usp.br
Dept. of Transportation Engineering, Escola Politecnica University of Sao Paulo, Sao Paulo, SP, Brazil
Creemers, Stefan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-09
s.creemers@ieseg.fr
IESEG School of Management, Lille, France
Creti, Anna . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-14
anna.creti@polytechnique.edu
U. Paris Ouest and Ecole Polytechnique, France
Cribben, Ivor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-19
cribben@ualberta.ca
University of Alberta, Edmonton, AB, Canada
Cristal, Irina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-40
irina.cristal@gmail.com
Faculty of Spatial Planning, Technical University of Dortmund, Dortmund, Germany
Crone, Sven F. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-15
s.crone@lancaster.ac.uk
Department of Management Science, Lancaster University
Management School, Lancaster, United Kingdom
Crook, Jonathan . . . . . . . . . . . . . . . . . . . . . . HD-34, TE-34, TA-43
j.crook@ed.ac.uk
University of Edinburgh Business School, University of Edinburgh, Edinburgh, Lothian, United Kingdom
Cruz Neto, João Xavier da . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-26
jxavier@ufpi.edu.br
Mathematics, Federal University of Piaui, Teresina, Piaui,
Brazil
Cruz-Zambrano, Miguel . . . . . . . . . . . . . . . . . . . . MA-10, MB-10
mcruz@irec.cat
Energy Economics Group, Institut de Recerca en Energia de
Catalunya, Sant Adria del Besos, Spain
Csercsik, Dávid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-09
csercsik@scl.sztaki.hu
Mta Krtk, Pecs, Hungary
Cuartero, Jordi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-36
JORGE.CUARTERO@roquette.com
Purchasing department, Roquette Laisa España, BenifaióValencia, Spain
Cui, Jian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-32
jian.cui@gmail.com
TU Darmstadt, Stuttgart, Baden-Württemberg, Germany
Cui, Jinchuan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-10
cjc@amss.ac.cn
Institute of Applied Mathematics, Chinese Academy of Sciences, Bheijin, China
Cui, Xiangyu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-29
cui.xiangyu@mail.shufe.edu.cn
School of Statistics and Management, Shanghai University
of Finance and Economics, China
Cui, Yao . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-15
cuiyao@umich.edu
University of Michigan, Ann Arbor, United States
Cunha, Rodolfo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-14
cunha.rodolfo@gmail.com
State University of Campinas, LIMEIRA, Sao Paulo, Brazil
Cyrino Oliveira, Fernando Luiz . . . . . . . . . . . . . . . . . . . . . . TA-29
cyrino@puc-rio.br
Industrial Engineering, Pontifical Catholic University of Rio
de Janeiro, Brazil
D’Acierno, Luca . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-01
luca.dacierno@unina.it
Department of Civil, Architectural and Environmental Engineering, ’Federico II’ University of Naples, Naples, Italy
D’Amato, Egidio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-30
egidio.damato@unina2.it
Dipartimento di Ingegneria Industriale e dell’Informazione,
Seconda Università degli Studi di Napoli, Aversa, CE, Italy
D’Ambrosio, Claudia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-11
dambrosio@lix.polytechnique.fr
LIX, CNRS - Ecole Polytechnique, Palaiseau, France
D’Amours, Sophie . . . . . . . . . . . . . . . . . . . . . . . . . . HE-36, MD-36
Sophie.Damours@gmc.ulaval.ca
Universite Laval, Forac-Cirrelt, Quebec, Canada
D’Ariano, Andrea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-01
a.dariano@dia.uniroma3.it
Dipartimento di Ingegneria, Università degli Studi Roma Tre,
Rome, Italy
D. Nasiri, Saeideh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-06
dnassiri.sae@gmail.com
STOR-i DTC, Lancaster University, lancaster, United Kingdom
Daamen, Winnie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-04
w.daamen@tudelft.nl
Transport & Planning, Delft University of Technology, Delft,
Netherlands
Dagdeviren, Metin . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-07, TB-29
metindag@gazi.edu.tr
Department of Industrial Engineering, Engineering Faculty,
Ankara, Turkey
Dai, Wanyang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-31
nan5lu8@netra.nju.edu.cn
Mathematics, Nanjing University, Nanjing, China
Daliot, Ariel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-43
arield@mprest.com
mPrest System LTD, Petach-Tikva, Israel
Dall’Aglio, Marco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-30
mdallaglio@luiss.it
Dept of Economics and Business, LUISS University, Rome,
Italy
Damak, Mohamed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-34
mohamed.damak@standardandpoors.com
Research, Standard & Poor’s, Paris, France, France
313
AUTHOR INDEX
IFORS 2014 - Barcelona
Damay, Jean . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-01
jean.damay@sncf.fr
Innovation & Research, SNCF, Paris, France
Dash, Sanjeeb . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-11
sanjeebd@us.ibm.com
IBM, Yorktown Heights, New York, United States
Dambreville, Frédéric . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-17
submit@fredericdambreville.com
DGA, Arcueil, France
Daskalaki, Sophia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-43
sdask@upatras.gr
Engineering Sciences, University of Patras, Patras, Greece
Danach, Kassem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-33
kassem_danach@live.com
LGI2A, Universite de l’Artois, Tyr, Sud, Lebanon
Datta, Dilip . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-32
ddatta@tezu.ernet.in
Mechanical Engineering, Tezpur University, Tezpur, India
Dang, Chuangyin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-25
mecdang@cityu.edu.hk
Systems Engineering & Engineering Management, City University of Hong Kong, Kowloon, Hong Kong
Datta, Partha . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-35
ppdatta@iimcal.ac.in
Operations Management, IIM Calcutta, Kolkata, West Bengal, India
Dang, Nguyen Thi Thanh . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-33
nguyenthithanh.dang@student.kuleuven.be
Computer Science, KU Leuven, Kortrijk, Belgium
Datta, Subhash. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-27
subhash.datta@gmail.com
Centre for Inclusive Growth and Sustainable Development,
GURGAON, Haryana, India
Dangaard Brouer, Berit . . . . . . . . . . . . . . . . . . . . . . TD-05, TE-05
blof@man.dtu.dk
DTU Management Engineering, Technical University of
Denmark - DTU, Kongens Lyngby, Denmark
Daniele, Elia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-30
elia.daniele@iwes.frauhofer.de
Fraunhofer IWES Institut fur Windenergie und Energiesystemtechnik, Oldenburg, Germany
Danielson, Mats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-31
mad@dsv.su.se
Dept. of Computer and Systems Sciences, Stockholm University, Kista, -, Sweden
Dauglien, Ala . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-45
ala.daugeliene@ktu.lt
Department of Civil Engineering Technologies, Kaunas University of Technology, Kaunas, Lithuania
Daultani, Yash . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-44
yash@iiml.ac.in
Operations Management, Indian Institute of Management
Lucknow, Lucknow, Uttar Pradesh, India
Davenport, Guy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-33
guy.davenport@bayer.com
Bayer CropScience, Belgium
Danloup, Nicolas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-19
ndanloup@hotmail.fr
LGI2A, University of Artois, Arras, France
David, Amy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-32
amydavid@uic.edu
University of Illinois at Chicago, Chicago, United States
Daraeepour, Ali . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-20
ad224@duke.edu
Duke University, Durham, North Carolina, United States
Davidov, Ori . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-24
davidov@stat.haifa.ac.il
Statistics, University of Haifa, Haifa, Israel
Dargam, Fatima . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-42
F.Dargam@SimTechnology.com
SimTech Simulation Technology, Graz, Austria
Davies, David . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-20
David.Davies@pet.hw.ac.uk
Institute of Petroleum Engineering, Heriot-Watt University,
Edinburgh, Select State, United Kingdom
Darkow, Inga-Lena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-21
inga-lena@darkow.de
Supply Chain Management, Universität Bremen / BASF, Germany
Darwin, Allysha Rahmi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-17
darwinallysharahmi@yahoo.com
Housing, Building and Planning, University Sains Malaysia,
Malaysia
Das, Ajay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-34
ajay.das@baruch.cuny.edu
Management, Baruch College, New York, NY, United States
Das, Sanmay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-22
sanmay@seas.wustl.edu
Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri, United States
Dash, Gordon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-30
ghdash@uri.edu
Finance and Decision Sciences, University of Rhode Island,
Kingston, RI, United States
314
Day, Sandy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-20
sandy.day@strath.ac.uk
Department of Naval Architecture, Ocean & Marine Engineering, University of Strathclyde, Glasgow, United Kingdom
Díaz Díaz, José Carlos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-25
jcdiazdiaz@yahoo.es
DISMI, Università degli Studi di Modena e Reggio Emilia,
Reggio Emilia, Emilia Romagna, Italy
Díaz-Madroñero, Manuel . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-26
fcodiama@cigip.upv.es
Research Centre on Production Management and Engineering, Universitat Politècnica de València, Alcoy, Spain
de Araujo, Silvio . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-41, ME-41
saraujo@ibilce.unesp.br
Departamento de Matemática Aplicada, Universidade Estadual Paulista-UNESP, São José do Rio Preto, São Paulo, Brazil
De Baets, Bernard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-24
IFORS 2014 - Barcelona
Bernard.DeBaets@ugent.be
Ghent University, Belgium
De Beukelaer, Herman . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-33
Herman.DeBeukelaer@UGent.be
Applied Mathematics, Computer Science and Statistics,
Ghent University, Gent, Belgium
De Bock, Koen W.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-40
k.debock@ieseg.fr
Department of Marketing; IESEG Expertise Center for
Database Marketing (IESEG-ECDM), IESEG School of
Management, Lille, France
De Boeck, Liesje . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-21
liesje.deboeck@kuleuven.be
Center for Information Management, Modeling and Simulation, KU Leuven, Brussels, Belgium
De Brucker, Klaas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-37
klaas.debrucker@kuleuven.be
Faculty of Economics and Business - Research Centre for
Economics and Corporate Sustainability (CEDON), KU Leuven - University of Leuven (Campus HU Brussel), Belgium,
Brussels, Belgium
De Bruecker, Philippe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-21
philippe.debruecker@kuleuven.be
Research Center for Operations Management, KU Leuven,
Leuven, Belgium
De Causmaecker, Patrick . . . . . . . . . . . . . . . . . . . . FB-05, HD-33
Patrick.DeCausmaecker@kuleuven-kortrijk.be
Computer Science/CODeS, Katholieke Universiteit Leuven,
Kortrijk, Flanders, Belgium
De Jaeger, Simon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-21
simon.dejaeger@kuleuven.be
CEDON, KU Leuven, Brussels, Belgium
de Jonge, Bram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-32
b.de.jonge@rug.nl
Operations, University of Groningen, Groningen, Netherlands
de Keijzer, Bart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-22
dekeijzer@dis.uniroma1.it
Department of Computer, Control, and Management Engineering, Sapienza University of Rome, Rome, Italy
de Koster, René . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-04
rkoster@rsm.nl
Rotterdam School of Management, Erasmus University Rotterdam, Rotterdam, Netherlands
de la Riva, Enrique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-34
enrique.delariva@sandp.com
Global Business Intelligence, Standard & Poor’s, Madrid,
Spain
de Laat, David . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-16
mail@daviddelaat.nl
DIAM, Delft University of Technology, Delft, Netherlands
De Leone, Renato. . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-03, ME-34
renato.deleone@unicam.it
School of Science and Technologies, Università di Camerino,
Camerino, MC, Italy
De Los Santos Pineda, Alicia . . . . . . . . . . . . . . . . . . . . . . . . . FA-01
aliciasantospineda@gmail.es
Matemática Aplicada II, Universidad de Sevilla, Sevilla,
AUTHOR INDEX
Spain, Spain
De Meyer, Arnoud . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-22
arnouddemeyer@smu.edu.sg
SMU, Singapore, Singapore
De Meyer, Geert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-33
geert.demeyer@bayer.com
Bayer CropScience, Belgium
De Moraes, Angela . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-34
a.r.f.de-moraes@sms.ed.ac.uk
Mangement Science and Business Economics, University of
Edinburgh, Edinburgh, United Kingdom
de Oliveira, Manuela Maria . . . . . . . . . . . . . . . . . . . . . . . . MA-35
moliveira@ipma.pt
IPMA, Portugal
de Oliveira, Welington . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-26
welingtonluis@gmail.com
IMPA, Rio de Janeiro, Rio de Janeiro, Brazil
De Prada Gil, Mikel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-10
mdeprada@irec.cat
Electrical Engineering Department, IREC, Sant Adria del
Besos, Barcelona, Spain
De Schutter, Bart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-20
b.deschutter@tudelft.nl
Delft Center for Systems and Control, Delft University of
Technology, Delft, Netherlands
De Smet, Yves . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-45
yves.de.smet@ulb.ac.be
Smg - Code, Université Libre de Bruxelles, Bruxelles, Belgium
de Souza, Ligia C. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-06
li.correasouza@gmail.com
Instituto Nacional de Pesquisas Espaciais, São José dos Campos, SP, Brazil
de Villiers, Anton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-17
antondev@sun.ac.za
Department of Logistics, Stellenbosch University, Matieland,
Western Cape, South Africa
De Wolf, Daniel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-43
daniel.dewolf@univ-littoral.fr
TVES, Université du Littoral, Dunkerque Cedex 1, France
De-los-Santos, Alicia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-01
aliciasantos@us.es
Matemática Aplicada II, University of Seville, Seville, Spain
Debo, Laurens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-22
Laurens.Debo@chicagobooth.edu
Booth School of Business, University of Chicago, Chicago,
United States
Deckmyn, Gaby . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-36
gaby.deckmyn@uantwerpen.be
University of Antwerpen UA, Wilrijk, Belgium
Decouttere, Catherine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-06
catherine.decouttere@kuleuven.be
Katholieke Universiteit Leuven, Leuven, Belgium
Deepho, Jitsupa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-37
jitsupa.deepho@mail.kmutt.ac.th
Mathematics, King Mongkut’s University of Technology
315
AUTHOR INDEX
IFORS 2014 - Barcelona
Thonburi, Bangkok, Thailand
Deeratanasrikul, Lalida . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-40
lalida.d@gmail.com
Tokyo Institute of Technology, Japan
Defourny, Boris . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-20
defourny@lehigh.edu
Industrial & Systems Engineering, Lehigh University, Bethlehem, PA, United States
Defraeye, Mieke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-09
mieke.defraeye@kuleuven.be
Research Center for Operations Management, KU Leuven,
Leuven, Belgium
deFreitas, Rosiane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-11
rosiane@icomp.ufam.edu.br
Institute of Computing, Ufam / Ufrj, Brazil
Defryn, Christof . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-23
christof.defryn@uantwerpen.be
Engineering Management, University of Antwerp, Antwerp,
Belgium
Degel, Dirk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-39
dirk.degel@rub.de
Faculty of Management and Economics, Ruhr University
Bochum, Bochum, Germany
Deghan, Alireza . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-37
Alirezadehghan52@yahoo.com
Wood and Paper, University of Tehran, Iran, Islamic Republic
Of
Degl’Innocenti, Marta . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-38
M.Deglinnocenti@soton.ac.uk
Southampton Management School, University of Southampton, Southampton, United Kingdom
Dehmer, Matthias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-03
matthias.dehmer@univie.ac.at
Bundeswehr Universität München, Germany
Deineko, Vladimir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-30
v.deineko@warwick.ac.uk
Warwick Business School, Warwick University, Coventry,
United Kingdom
Dekker, Rommert . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-05, TE-05
rdekker@few.eur.nl
Erasmus University Rotterdam, Rotterdam, Netherlands
Del Valle, Jennifer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-43
jjhamlyn@utep.edu
Mathematical Sciences, University of Texas at El Paso, El
Paso, TX, United States
Delbos, Frédéric . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-18
frederic.delbos@ifpen.fr
IFP Energies Nouvelles, Rueil-Malmaison, France
Deleplanque, Samuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-13
deleplanque.samuel@gmail.com
LIMOS, Saint-Flour, France
Delgadillo, Remberto Emanuel . . . . . . . . . . . . . . . . . . . . . . HB-31
emanuel.dc0@gmail.com
Departamento de Computación, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Argentina
Delgado, Alexandrino . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-05
316
Alexandrino.Delgado@unicv.edu.cv
DECM, Universidade de cabo Verde, Mindelo, Cape Verde
Delhoume, Frederic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-43
delhoume@fr.ibm.com
IBM, Gentilly, France
Dell’Amico, Mauro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-25
dellamico@unimore.it
DISMI, University of Modena and Reggio Emilia, Reggio
Emilia, Italy
Dell, Robert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-30, TD-33
dell@nps.edu
Operations Research, Naval Postgraduate School, Monterey,
CA, United States
Delorme, Xavier . . . . . . . . . . . . . . . . . . . . . . HB-13, HE-13, TB-13
delorme@emse.fr
Fayol-emse, Cnrs, Umr 6158, Limos, Ecole des Mines de
Saint Etienne, Saint Etienne, France
Demange, Marc . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-12, MB-12
demange@essec.edu
ESSEC Business School and LAMSADE UMR 7243, Paris,
France
Dembczynski, Krzysztof . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-24
kdembczynski@cs.put.poznan.pl
Institute of Computing Science, Poznan University of Technology, Poznan, Poland
DeMiguel, Victor . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-10, TD-22
avmiguel@london.edu
Decision Sciences, London Business School, London, United
Kingdom
Demir, A. Yonca . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-36
ydemir@bilgi.edu.tr
Business Administration, Istanbul Bilgi University, Istanbul,
Turkey
Demir, Emrah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-33, MD-42
e.demir@tue.nl
School of Industrial Engineering, Eindhoven University of
Technology, Eindhoven, Netherlands
Demirci, Duygu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-18
dmrcdyg@gmail.com
Anadolu University, Eskişehir, Turkey
Demirok Donmez, Nurcan . . . . . . . . . . . . . . . . . . . . . . . . . . HD-37
n.demirok@iku.edu.tr
Industrial Engineering, Istanbul Kultur University, Istanbul,
Turkey
Deng, Changrong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-06
changrong.deng@duke.edu
Duke University, Durham, NC, United States
Deng, Shiming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-19
dengsm@gmail.com
Huazhong University of Science and Technology, Wuhan,
China
Deng, Zhibin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-17
zdeng2@ncsu.edu
School of Management, University of Chinese Academy of
Sciences, Beijing, China
Denoyel, Victoire . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-15
victoire.denoyel@essec.edu
IFORS 2014 - Barcelona
Operations Management and Decision Sciences, ESSEC
Business School, Cergy-Pontoise, France
Densing, Martin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-09
martin.densing@psi.ch
Energy Economics, PSI, Villigen, Switzerland
Denton, Brian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-06, HA-43
btdenton@umich.edu
Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI, United States
dePrada, Cesar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-41
prada@autom.uva.es
Systems Engineering and Automatc Control, University of
Valladolid, Valladolid, Spain, Spain
Dereniowski, Dariusz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-17
deren@eti.pg.gda.pl
Department of Algorithms and System Modeling, Gdańsk
University of Technology, Gdańsk, Poland
Derinkuyu, Kürşad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-08
kursad@utexas.edu
Logistics Management, University of Turkish Aeronautical
Association, Ankara, Turkey
Derron, Marc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-27
mderroncom@gmail.com
Unil, Switzerland
Desai, Jitamitra . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-39
jdesai@ntu.edu.sg
School of Mechanical and Aerospace Engineering, Nanyang
Technological University, Singapore
Desaulniers, Guy . . . . . . . . . . . . . . . . . . . . MA-03, TD-05, HE-41
Guy.Desaulniers@gerad.ca
École Polytechnique de Montréal and GERAD, Montréal,
Canada
Deshmukh, Ashutosh . . . . . . . . . . . . . . . . . . . . . . . . HA-44, HB-44
avd1@psu.edu
Penn State University- Erie, Erie, PA, United States
Deshpande, Ajay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-20
ajayd@us.ibm.com
IBM T J Watson Research Center, United States
Despotis, Dimitris . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-10, HB-10
despotis@unipi.gr
Department of Informatics, University of Piraeus, Piraeus,
Greece
Desrosiers, Jacques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-11
jacques.desrosiers@hec.ca
Management Science, HEC Montreal, Montreal, Quebec,
Canada
Dessouky, Maged . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-25
maged@usc.edu
Industrial and Systems Engineering, University of Southern
California, Los Angeles, United States
DeTombe, Dorien . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-29
detombe@nosmo.nl
Methodology of Societal Complexity, Chair Euro Working
Group, Amsterdam, Netherlands
Deus, Rui . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-44
goncalves.deus@marinha.pt
DAI - Divisão de Análise de Informação, DAGI, Direção de
AUTHOR INDEX
Análise e Gestão da Informação - CINAV, Lisboa, Portugal
Deutsch, Yael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-22
yaely@tx.technion.ac.il
Business School, University of Toronto, Toronto, Canada
Devine, Mel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-10
meldevine07@gmail.com
University of Limerick, Ireland
Dewilde, Thijs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-01
Thijs.Dewilde@cib.kuleuven.be
Centre for Industrial Management/Traffic & Infrastructure,
KU Leuven, University of Leuven, Leuven, Belgium
deWitte, Paula . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-31
pauladw2008@gmail.com
Secure-NOK AS, Houston, Texas, United States
Dey, Prasanta Kumar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-32
p.k.dey@aston.ac.uk
Aston, Birmingham, United Kingdom
Dhaenens, Clarisse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-40
Clarisse.Dhaenens@lifl.fr
Lifl / Inria, Villeneuve d’Ascq cedex, France
Dhara, Anulekha . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-26
anulekha.dhara@gmail.com
Mathematics, Indian Institute of Technology Gandhinagar,
Ahmedabad, Gujarat, India
Dhesi, Gurjeet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-24
dhesig@lsbu.ac.uk
Business Studies, London South Bank University, London,
United Kingdom
Dhingra, Ashwani Kumar . . . . . . . . . . . . . . . . . . . . FB-14, HD-33
ashwani_dhingra1979@rediff.com
Department of Mechanical Engineering, University Institute
of Engineering & Technology, Rohtak, 124001, India
Dhingra, Sunita . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-14, HD-33
sunitadhingramdu@rediff.com
Department of Computer Science & Engineering, University
Institute of Engineering & Technology, Rohtak, Haryana, India
Di Francesco, Massimo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-05
mdifrance@unica.it
Department of Mathematics and Computer Science, University of Caligari, Caligari, Italy
Di Lorenzo, David . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-41
dilorenzo@dsi.unifi.it
University of Florence, Firenze, Italy
Di Luca, Camilla. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-30
cdiluca@luiss.it
Economics and Finance, LUISS Guido Carli, Roma, Italy
Di Martinelly, Christine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-19
c.dimartinelly@ieseg.fr
Management, Leseg School of Management, Lille, Nord,
France
Di Puglia Pugliese, Luigi . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-45
luigi.dipugliapugliese@unical.it
DIMEG: Department of Mechanical, Energy and Management Engineering, University of Calabria, Rende, Italy, Italy
Dias, Luis C. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-31
317
AUTHOR INDEX
IFORS 2014 - Barcelona
lmcdias@fe.uc.pt
Faculdade de Economia / INESC Coimbra, Univ. Coimbra,
Coimbra, Portugal
Diaz, Javier . . . . . . . . . . . . . . . . . . . . . . . . . ME-09, FA-23, MD-34
javidiaz@unal.edu.co
Sistemas e Informatica, Universidad Nacional de Colombia,
Medellin, Antioquia, Colombia
Diaz, Rafael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-40
rdiaz@odu.edu
Virginia Modeling, Analysis, & Simulation Center, Old Dominion University, Suffolk, VA, United States
Diekmann, Daniel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-35
diekmann@itl.tu-dortmund.de
Institute of Transport Logistics, TU Dortmund University,
Germany
Digges La Touche, Emily . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-04
e.touche.11@ucl.ac.uk
Civil Engineering, UCL, London, United Kingdom
Dimarelis, Efstathios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-42
e.dimarelis@student.tue.nl
Eindhoven University of Technology, Eindhoven, Netherlands
Dimitrakopoulos, Roussos. . . . . . . . . . . . . . . . . . . . . . . . . . . HA-29
roussos.dimitrakopoulos@mcgill.ca
Mining and Materials Engineering, McGill University, Montreal, Quebec, Canada
Dimitrov, Ned . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-32, TE-33
ned@nps.edu
Operations Research, Naval Postgraduate School, Monterey,
CA, United States
Diner, Oznur Yasar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-17
oznur.yasar@khas.edu.tr
Computer Engineering, Kadir Has University, Istanbul,
Turkey
Disney, Stephen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-40
disneysm@cardiff.ac.uk
Cardiff Business School, Cardiff University, Cardiff, Wales,
United Kingdom
Divan, Deepak . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-20
deepak.divan@ece.gatech.edu
Electrical and Computer Engineering, Georgia Institute of
Technology, Atlanta, United States
Divnic, Tomica . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-39
tomadivnic@gmail.com
Department of Mathematics, Faculty of Natural Sciences and
Mathematics, Kragujevac, Serbia
Djikanovic, Jasenka . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-04
djikanovic3@hotmail.com
Management, Faculty of Organizational Sciences, Belgrade,
Serbia
Djimadoumbaye, Noubara . . . . . . . . . . . . . . . . . . . . . . . . . . TA-20
ted_noubara@yahoo.fr
University of Massachusetts, Amherst, MA, United States
Doan, Xuan Vinh. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-04
X.Doan@warwick.ac.uk
Warwick Business School, University of Warwick, Coventry,
United Kingdom
318
Dobrovnik, Mario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-06
mario.dobrovnik@wu.ac.at
Institute of Transport and Logistics Management, Vienna
University of Business and Economics, Vienna, Vienna, Austria
Dobson, Gregory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-43
greg.dobson@simon.rochester.edu
Simon School, University of Rochester, Rochester, NY,
United States
Dodin, Bajis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-12
bdodin@alfaisal.edu
College of Business, Alfaisal University, Riyadh, Saudi Arabia
Doerner, Karl . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-12
karl.doerner@jku.at
Institute for Production and Logistics Management, Johannes
Kepler University Linz, Linz, Austria
Doerr, Kenneth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-13
khdoerr@nps.edu
Graduate School of Business and Public Policy, Naval Postgraduate School, Monterey, CA, United States
Dogdu, Elif . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-27
elif.dogdu@deu.edu.tr
Department of Industrial Engineering, Dokuz Eylül University, İzmir, Turkey
Doherty, Neil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-44
michaeljmortenson@gmail.com
Loughborough University, Coventry, United Kingdom
Dolgui, Alexandre . . . . . . . . . . . . . . . . . . . . HB-13, HE-13, TB-13
dolgui@emse.fr
IE & Computer Science, Ecole des Mines de Saint Etienne,
Saint Etienne, France
Dolinajcová, Miroslava . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-23
mdolinajcova@gmail.com
University of Economics in Bratislava, Slovakia
Dolinskaya, Irina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-32
dolira@northwestern.edu
Industrial Engineering and Management Sciences, Northwestern University, Evanston, IL, United States
Dollevoet, Twan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-01, TA-01
dollevoet@ese.eur.nl
Econometric Institute, Erasmus University of Rotterdam,
Rotterdam, Netherlands
Dolmatova, Marina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-08
ms.marina.dolmatova@gmail.com
Computational Mathematics and Cybernetics, Lomonosov
Moscow State University, Moscow, Russian Federation
Domingues, Ana Rita . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-31
arsdomingues@gmail.com
INESC Coimbra, Coimbra, Portugal
Domonkos, Tomas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-23
tomas.domonkos@savba.sk
Institute of Economic research, Slovak Academy of Sciences,
Bratislava, Slovakia
Dongxuan, Wei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-03
dxwei@chd.edu.cn
Highway School, Chang’an University, Xi’an, Shaanxi,
China
IFORS 2014 - Barcelona
Dopazo, Esther . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-26
edopazo@fi.upm.es
Lenguajes y Sistemas Informáticos, Universidad Politecnica
de Madrid, Boadilla del Monte, Madrid, Spain
Dorneles, Arton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-10
arton.dorneles@inf.ufrgs.br
Instituto de Informática, Universidade Federal do Rio Grande
do Sul, Porto Alegre, RS, Brazil
Dos Santos, Maria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-33
maria.dossantos@kerp.at
R & D, Weee, KERP Competence Center Electronics & Environment, Vienna, Austria
Doukas, Haris . . . . . . . . . . . . . . . . . . . . . . . TB-18, MD-34, HD-42
h_doukas@epu.ntua.gr
Electrical & Computer Engineering, Decision Support Systems Lab, National Technical University of Athens, Greece
Doumpos, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-16, TA-29
mdoumpos@dpem.tuc.gr
School of Production Engineering and Management, Technical University of Crete, Chania, Greece
Drabas, Tomasz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-03
drabas.t@gmail.com
School of Aviation, The University of New South Wales,
Queenscliff, NSW, Australia
Drakopoulos, Kimon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-06
kimondr@mit.edu
EECS, MIT, Cambridge, MA, United States
Dregert, Swetlana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-15
dregert@controlling.rwth-aachen.de
Controlling, RWTH Aachen, Aachen, NRW, Germany
Drevon, Thibault . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-12
thibault.drevon@etu.univ-tours.fr
Laboratoire d’Informatique, Polytech’Tours, Tours, France
Dreyer, Kathryn . . . . . . . . . . . . . . . . . . . . . MD-22, FA-34, HA-45
kathrynadreyer@gmail.com
Health Intelligence Unit, Medscheme, Cape Town, Western
Cape, South Africa
Drezgic, Sasa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-29
sdrezgic@efri.hr
University of Rijeka, Faculty of Economics, Rijeka, Croatia
Drezner, Zvi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-45
zdrezner@fullerton.edu
ISDS, California State University, Fullerton, California,
United States
Dris, Djamal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-32
drisdjamal@yahoo.fr
Commercial Sciences, Bejaia University, Bejaia, Algeria
Drori, Yoel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-38
yoel.drori@gmail.com
School of Mathematical Sciences, Tel Aviv University, Tel
Aviv, Israel
Drosos, Dimitris . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-44
ddrosos@aegean.gr
Information and Communication Systems Engineering, University of the Aegean, Samos Island, Greece
Drummond, Lucia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-43
AUTHOR INDEX
lucia@ic.uff.br
Computer Science, Fluminense Federal University, Niteroi,
Rio de Janeiro, Brazil
Du Toit, Tiny . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-16
Tiny.DuToit@nwu.ac.za
School of Computer, Statistical and Mathematical Sciences,
North-West University, Potchefstroom, North-West, South
Africa
Du, Gang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-44
tddg@tju.edu.cn
College of Management and Economics, Tianjin University,
Tianjin, China
Duan, Yanqing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-45
Yanqing.Duan@beds.ac.uk
Business School, University of Bedfordshire, Luton, Bedfordshire, United Kingdom
Duarte, Abraham . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-37, TD-40
a.duarte@escet.urjc.es
URJC, Spain
Duarte, Abraham . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-37
abraham.duarte@urjc.es
Computer Sciences, Universidad Rey Juan Carlos, Madrid,
Spain
Dubeau, François . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-36
francois.dubeau@usherbrooke.ca
Mathématiques, Université de Sherbrooke, Sherbrooke (Qc),
Canada
Dueñas, Pablo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-10
pablo.duenas@iit.upcomillas.es
Universidad Pontificia Comillas, Spain
Duenyas, Izak . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-15
duenyas@umich.edu
University of Michigan, Ann Arbor, United States
Duhamel, Christophe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-37
christophe.duhamel@isima.fr
LIMOS, Université Clermont-Ferrand II, Aubière, France
Dulá, José . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-26
jdula@vcu.edu
School of Business, Virginia Commonwealth University,
Richmond, United States
Duleba, Szabolcs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-32
duleba@nyf.hu
Economics and Logistics, College of Nyíregyháza, Nyíregyháza, Hungary
Dullaert, Wout . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-42
wout.dullaert@vu.nl
Faculty of Economics and Business Administration, VU University Amsterdam, Amsterdam, Netherlands
Dundar, Abdullah Oktay . . . . . . . . . . . . . . . . . . . . ME-04, MB-18
aodundar@selcuk.edu.tr
Selcuk University, Konya, Turkey
Dunstall, Simon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-43
Simon.Dunstall@csiro.au
Mathematics, Informatics and Statistics, CSIRO, South Clayton, Victoria, Australia
Durak, Mehmet Yahya . . . . . . . . . . . . . . . . . . . . . . . FA-16, FB-16
mehmetyahyadurak@gmail.com
319
AUTHOR INDEX
IFORS 2014 - Barcelona
Department of Industrial Engineering, Istanbul Kultur University, Istanbul, Turkey
Duran, Ahmet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-43
gazelhunter@hotmail.com
Selcuk Unİversİty, konya, selcuklu, Turkey
Durán, Guillermo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-35
gduran@dm.uba.ar
University of Buenos Aires, Argentina
Durduran, Savas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-43
durduran@selcuk.edu.tr
Selcuk University, Konya, Selcuklu, Turkey
Durkan, Mehmet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-32
mehmet_durkan@yahoo.com
Turkish Air Force, balıkesir, Turkey
Durlofsky, Louis J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-28
lou@stanford.edu
Stanford University, Stanford, United States
Dursun, Pinar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-39
dursunpi@itu.edu.tr
Industrial Engineering, Istanbul Technical University, Istanbul, Turkey
Dussault, Jean-Pierre . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-36
Jean-Pierre.Dussault@usherbrooke.ca
Université de Sherbrooke, Québec, Canada
Dutta, Amitava . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-06
adutta@gmu.edu
School of Management, George Mason University, Fairfax,
VA, United States
Dutta, Pallab . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-35
pallabk2014@email.iimcal.ac.in
IIM Calcutta (alumnus), Kolkata, West Bengal, India
Duxbury, Phil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-11
duxbury@pa.msu.edu
Physics and Astronomy, Michigan State University, East
Lansing, Michigan, United States
Duzdar, Irem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-29
iremd82@gmail.com
Industrial Engineering, Istanbul Arel University, Istanbul,
Turkey
Düzdar, Irem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-15
iremduzdar@arel.edu.tr
İstanbul Arel University, Istanbul, Turkey
Duzgit, Zehra . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-13
zehra.duzgit@bilgi.edu.tr
Department of Industrial Engineering, Bogazici University,
Istanbul, Turkey
Dvalishvili, Phridon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-09
pridon.dvalishvili@tsu.ge
Computer Science, Tbilisi State University, Tbilisi, Georgia
Dyer, Danny . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-17
dyer@math.mun.ca
Mathematics and Statistics, Memorial University of Newfoundland, St. John’s, Newfoundland, Canada
Dyk, Wesley . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-29
wdyk@nobleenergyinc.com
Noble Energy, Inc., Denver, CO, United States
320
Dzhafarov, Vakif . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-07
vcaferov@anadolu.edu.tr
Mathematics, Anadolu University, Eskisehir, Turkey
Dziuba, Oksana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-44
oksana.dziuba86@gmail.com
National Technical University of Ukraine "Kyiv Polytechnic
Institute", Kyiv, Ukraine
Dziurzynski, Lukasz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-45
lukaszad@gmail.com
Airbnb, United States
Ebara, Hiroyuki . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-25
ebara@kansai-u.ac.jp
The Faculty of Engineering Science, Kansai University,
Suita, Osaka, Japan
Eberhard, Andrew . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-39
andy.eb@rmit.edu.au
Mathematical and Geospatial Sciences Dept., RMIT University, Melbourne, Victoria, Australia
Ebrahim Nejad, Alireza . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-41
a_ebra@encs.concordia.ca
Mechanical and Industrial Engineering, Concordia University, Montreal, quebec, Canada
Ecer, Billur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-27
billurecer@gazi.edu.tr
Industrial Engineering, Yıldırım Beyazıt University, Faculty
of Engineering and Natural Sciences, Ankara, Turkey
Ederer, Thorsten . . . . . . . . . . . . . . . . . . . . . FA-08, TB-21, MA-43
ederer@mathematik.tu-darmstadt.de
Mathematics, Technische Universität Darmstadt, Darmstadt,
Hessen, Germany
Edinger Munk Plum, Christian . . . . . . . . . . . . . . . . . . . . . . TE-05
Christian.Edinger.Munk.Plum@maersk.com
Operations Research - DTU Management, Network Advanced Solutions - Maersk Line, Copenhagen K, Denmark
Edirisinghe, Chanaka . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-19
chanaka@utk.edu
College of Business Administration, University of Tennessee,
Knoxville, TN, United States
Egerer, Jonas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-07, MD-07
je@wip.tu-berlin.de
TU Berlin / DIW Berlin, Berlin, Germany
Eggereide, Baard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-33
beg@ffi.no
FFI, Norway
Egging, Ruud . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-07, MB-07
ruud.egging@iot.ntnu.no
Industrial Economics and Technology Management, NTNU,
Trondheim, Norway
Egorova, Lyudmila . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-30
lyude@inbox.ru
National Research University Higher School of Economics,
Moscow, Russian Federation
Ehrgott, Matthias . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-04, TE-44
m.ehrgott@lancaster.ac.uk
Management Science, Lancaster University, Lancaster,
United Kingdom
IFORS 2014 - Barcelona
Eide, Aslak . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-03
Aslak.Eide@sintef.no
Sintef Ict, Oslo, Norway
Einhorn, Mark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-11
einhorn@sun.ac.za
Department of Logistics, Stellenbosch University, Stellenbosch, Western Cape, South Africa
Eirinakis, Pavlos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-12
peir@aueb.gr
Management Science & Technology, Athens University of
Economics & Business, ATHENS, Greece
Eisenriegler, Sepp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-33
sepp.eisenriegler@rusz.at
R.U.S.Z. GmbH Lutzowgasse 12-14; 1140 Vienna, Austria,
Vienna, Austria
Ejov, Vladimir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-39
vladimir.ejov@flinders.edu.au
School of Computer Science, Engineering and Mathematics,
Flinders University, Bedford Park, SA, Australia
AUTHOR INDEX
El Ouardighi, Fouad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-25
elouardighi@essec.fr
Operations Management, ESSEC Business School, Cergy
Pontoise, France
Elgindy, Tarek . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-43
tarek.elgindy@csiro.au
Mathematics, Informatics and Statistics, CSIRO, Melbourne,
Victoria, Australia
Elhafsi, Mohsen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-40
mohsen.elhafsi@ucr.edu
School of Business Administration, University of California,
Riverside, CA, United States
Elhallaoui, Issmail . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-43
issmail.elhallaoui@gerad.ca
Math., Polytechnique, Montreal, Qué., Canada
Eliassi-Rad, Tina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-25
tina@eliassi.org
Rutgers University, Piscataway, New Jersey, United States
Ekenberg, Love . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-31
lovek@dsv.su.se
Dept. of Computer and Systems Sciences, Stockholm University, Kista, -, Sweden
Eliiyi, Uğur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-25
eliiyi@gmail.com
Department of Transport Planning, Izmir Metropolitan Municipality ESHOT General Directorate, Izmir, Turkey
Ekerhovd, Nils-Arne . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-36
nilsarne.ekerhovd@snf.no
SNF - Centre for Applied Research at NHH, Norwegian
School of Economics (NHH), Norway
Ellison, David . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-12
david@ellison.net
Mathematics, RMIT, Paris, France
Ekici, Ali . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-27
aekici@uh.edu
Industrial Engineering, University of Houston, Houston, TX,
United States
Ekici, Ali . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-02, TB-02
ali.ekici@ozyegin.edu.tr
Industrial Engineering, Ozyegin University, Istanbul, Turkey
Ekim, Tinaz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-11, MB-12
tinaz.ekim@boun.edu.tr
Istanbul, Bebek, Turkey
Ekinci, Yeliz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-41
ekinciyeliz@yahoo.com
Industrial Engineering, Dogus University, Istanbul, Turkey
Ekiz, Idil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-15
idilekiz@windowslive.com
Arel University, Istanbul, Turkey
Ekmen, Pelin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-23
ekmen.pelin@gmail.com
Bosphorus University, Turkey
Ekstrom, Thomas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-34
thomas.ekstrom@foi.se
Division of Defence Analysis, FOI, Swedish Defence Research Agency, Stockholm, Sweden
EL Haj Ben Ali, Safae . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-03
anasafae@gmail.com
Estadistica E.i.o., Universidad de Sevilla, Sevilla, Spain
El Hallaoui, Issmail . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-02
ih@crt.umontreal.ca
Math et Génie industriel, POLY and GERAD, MTL, QC,
Canada
Elmaghraby, Wedad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-15
welmaghr@rhsmith.umd.edu
R.H. Smith School of Business, University of Maryland, College Park, MD, United States
Elsayed, Elsayed . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-28, TA-42
elsayed@rci.rutgers.edu
Rutgers University, United States
Elshaikh, Abdalla . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-45
ae201@kent.ac.uk
Kent Business School, University of Kent, Canterbury, Kent,
United Kingdom
ElSheikh, Ahmed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-20
Ahmed.ElSheikh@pet.hw.ac.uk
Institute of Petroleum Engineering, Heriot-Watt University,
Edinburgh, Select State, United Kingdom
Emblemsvag, Jan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-23
jan.emblemsvag@vard.com
Vard Group As, Alesund, Norway
Emde, Simon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-13
simon.emde@uni-jena.de
Operations Management, Friedrich-Schiller-Universität Jena,
Jena, Germany
Emel, Erdal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-17
erdal@uludag.edu.tr
Industrial Engineering Department, Uludag University,
Bursa, Turkey
Emel, Gül Gökay . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-27, HA-44
ggokay@uludag.edu.tr
Business Administration, Uludag University, Bursa, Turkey
Emelichev, Vladimir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-19
emelichev@tut.by
321
AUTHOR INDEX
IFORS 2014 - Barcelona
Belarus State University, Minsk, Belarus
Industrial Engineering, Gazi University, Ankara, Turkey
Emer, Deniz Esin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-40
eesin@metu.edu.tr
Industrial Engineering, Middle East Technical University,
Ankara, Turkey
Errico, Fausto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-41
fausto.errico@cirrelt.ca
École de Technologie Supérieure and CIRRELT, Montreal,
Canada
Emrouznejad, Ali . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-32
a.emrouznejad@aston.ac.uk
Aston Business School, Aston University, Birmingham,
United Kingdom
Ertiningsih, Dwi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-19
dwiertiningsihd@math.leidenuniv.nl
Leiden University, Leiden, Zuid Holland, Netherlands
Eneya, Levis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-41
leneya@cc.ac.mw
Mathematical Sciences, University of Malawi-Chancellor
College, Zomba, South-Eastern Region, Malawi
Engau, Alexander . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-18, HD-29
aengau@alumni.clemson.edu
Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO, United States
Epstein, Leonardo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-19
lepstein@uandes.cl
School of Business and Economics, Universidad de los Andes, Santiago, Santiago, Chile
Erdem, Sabri . . . . . . . . . . TB-04, HB-27, FB-40, ME-42, HD-43
sabri.erdem@deu.edu.tr
Business Administration, Dokuz Eylul University Faculty of
Business, IZMIR, Turkey
Erdin Gundogdu, Ceren . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-42
ceren_erdin@yahoo.com
Business Administration, Yildiz Technical Univercity, Istanbul, Turkey
Eren Akyol, Derya . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-15, TE-27
derya.eren@deu.edu.tr
Department of Industrial Engineering, Dokuz Eylul University, Izmir, Turkey
Erginel, Nihal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-14
nerginel@anadolu.edu.tr
Industrial Engineering Department, Anadolu University,
Turkey
Ergun, Hakan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-10
hakan.ergun@esat.kuleuven.be
KU Leuven, Belgium
Ergun, Serap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-30
serapbakioglu@sdu.edu.tr
Technical Education Faculty, Suleyman Demirel University,
Turkey
Eriksson, E Anders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-08
e.anders.eriksson@foi.se
Defence Aanlysis, FOI, Stockholm, Sweden
Eriksson, Ola . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-36
Ljusk.Ola.Eriksson@slu.se
Department of Forest Resource Management, Swedish University of Agricultural Sciences, Umea, Sweden
Ernst, Andreas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-43
Andreas.Ernst@csiro.au
Mathematical and Information Sciences, CSIRO, Clayton
South, Vic, Australia
Erol, Serpil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-27
serpiler@gazi.edu.tr
322
Ertugrul, Irfan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-21
iertugrul@pau.edu.tr
Faculty of Business and Economic Sciences, Pamukkale University, Denizli, Turkey
Ertunc, Ela . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-04
elaertunc@selcuk.edu.tr
Geomatic Engineering, University of Selcuk, Konya, Turkey
Ervural, Bilal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-45
bilalervural@gmail.com
Istanbul Technical University, Turkey
Erzin, Adil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-39
adilerzin@math.nsc.ru
Discrete Optimization in Operations Research, Sobolev Institute of Mathematics, Novosibirsk, Russian Federation
Escudero, Laureano Fernando HB-03, FA-08, HB-11, HE-28,
MB-45
laureano.escudero@urjc.es
Dept. de Estadística e Investigación Operativa, Universidad
Rey Juan Carlos, Mostoles (Madrid), Spain
Esmaili Najafabadi, Elham . . . . . . . . . . . . . . . . . . . . . . . . . . HE-27
esmaili.elham@gmail.com
Industrial Engineering Department, Payame Noor University,
Najaf Abad, Isfahan, Iran, Islamic Republic Of
Espejo, Inmaculada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-03
inmaculada.espejo@uca.es
Statistics and operations research, University of Cadiz, Puerto
Real, Cádiz, Spain
Espinosa, Rafael Salvador . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-08
rata_del_mal@yahoo.com.mx
Universidad de Guadalajara, Zapopan, Jalisco, Mexico
Espinosa-Aranda, Jose Luis . . . . . . . . . . . . . . . . . . . . . . . . . TE-21
JoseL.Espinosa@uclm.es
UCLM, Spain
Espinoza Garcia, Juan Carlos. . . . . . . . . . . . . . . . . . . . . . . MA-12
b00319981@essec.edu
Operations Management, ESSEC Business School, Cergy
Pontoise, France
Espinoza, Daniel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-29
daespino@dii.uchile.cl
Industrial Engineering, Universidad de Chile, Santiago, RM,
Chile
Espitia Rueda, Alvaro Raul . . . . . . . . . . . . . . . . . . . . . . . . . . TE-02
ar.espitia325@uniandes.edu.co
Universidad de los Andes, Bogota, Colombia
Espuña, Antonio . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-13, TD-41
antonio.espuna@upc.edu
Departamento de Ingenieria Quimica, Universitat Politècnica
de Catalunya, Barcelona, Spain
IFORS 2014 - Barcelona
Estrada, Miquel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-06
miquel.estrada@upc.edu
CENIT Centre for Innovation in Transport, Barcelona, Spain
AUTHOR INDEX
ana.l.fadista@ctt.pt
CTT, Faro, Portugal
Estrócio, João Paulo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-18
joao.estrocio@cesp.com.br
CESP - Cia. Energética de São Paulo, Campinas, São Paulo,
Brazil
Fagerholt, Kjetil . . . . . . . . . . . . . . HA-05, HD-05, TB-05, ME-35
kjetil.fagerholt@iot.ntnu.no
Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology,
Trondheim, Norway
Etlinger, Karl . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-32
karl.etlinger@boku.ac.at
Institute of production and logistics, University of Natural
Resources and Life Sciences, Vienna, Austria
Faias, Jose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-34
jfaias@clsbe.lisboa.ucp.pt
UCP, Catolica Lisbon School of Business and Economics,
Lisbon, Portugal
Etukudo, Idorenyin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-36
nseobongidorenyin@gmail.com
Mathematics/Statistics & Computer Science, University of
Calabar, Calabar, Cross River, Nigeria
Falagara Sigala, Ioanna . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-31
ioanna.falagara.sigala@wu.ac.at
Vienna University of Economics and Business, Vienna, Austria
Euler, Reinhardt . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-12, MD-12
reinhardt.euler@univ-brest.fr
Informatique, Université de Brest, Brest, France
Falbo, Paolo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-08
falbo@eco.unibs.it
Department of Economics and Management, University of
Brescia, Brescia Bs, Italy
Evans, Antony . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-03
antony.evans@ucl.ac.uk
UCL Energy Institute, University College London, London,
United Kingdom
Everett, Jim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-29
jim.everett@uwa.edu.au
Centre for Exploration Targeting, University of Western Australia, Nedlands, WA, Australia
Evtushenko, Yuri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-18
evt@ccas.ru
Applied problems of optimization, Computer Center of Russian Academi of Sciences, Moscow, Russian Federation
Ewbank, Henrique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-02
henrique.ewbank@coppead.ufrj.br
COPPEAD Graduate Business School, Brazil
Expósito Izquierdo, Christopher . . . . . . . . . . . . . . . . . . . . . TD-40
cexposit@ull.es
Estadística, I.O. y Computación, University of La Laguna,
Spain
Eyvindson, Kyle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-36
kyle.eyvindson@helsinki.fi
Department of Forest Sciences, University of Helsinki,
Helsinki, Finland
Faccio, Maurizio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-13
maurizio.faccio@unipd.it
Department
of
Innovation
in
Mechanics
and
Management(DIMEG-Padova), University of Padova, Italy
Fack, Veerle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-33
veerle.fack@ugent.be
Applied Mathematics and Computer Science, Ghent University, Ghent, Belgium
Faco’, Joao Lauro D. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-39
jldfaco@ufrj.br
Dept. of Computer Science, Universidade Federal do Rio de
Janeiro, Rio de Janeiro, RJ, Brazil
Fadaei, Salman . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-43
salman.fadaei@in.tum.de
Informatics, TU München, Garching, Germany
Fadísta, Ana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-14
Fampa, Marcia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-11
fampa@cos.ufrj.br
Universidade Federal do Rio de Janeiro, Rio de Janeiro,
Brazil
Fan, Yang-Hua . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-26
sky31240@gmail.com
Department of International Business, National Dong Hwa
University, Shou-feng, Haulien, Taiwan
Fan, Yueyue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-20
yyfan@ucdavis.edu
Civil and Environmental Engineering, University of California, Davis, Davis, CA, United States
Fang, Shu-Cherng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-17
fang@ncsu.edu
Industrial and Systems Engineering, North Carolina State
University, Raleigh, NC, United States
Fang, Yong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-30
yfang@amss.ac.cn
Institute of Systems Science, Academy of Mathematics and
Systems Science, Chinese Academy of Sciences, Beijing,
China
Fanzeres, Bruno . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-10
bsantos@ele.puc-rio.br
Electrical Engineering, Pontifical Catholic University of Rio
de Janeiro, Rio de Janeiro, RJ, Brazil
Faria, Luerbio. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-12
luerbio@cos.ufrj.br
UERJ, Rio de Janeiro, RJ, Brazil
Farias, Ricardo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-23
rfarias@gmail.com
PESC, Coppe - Ufrj, Rio de Janeiro, Rio de Janeiro, Brazil
Farré, Mercè . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-21
farre@mat.uab.cat
Mathematics, Unversitat Autònoma de Barcelona, Bellaterra,
CATALONIA, Spain
Farrell, Niall . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-10
Niall.Farrell@esri.ie
ESRI, Dublin, Ireland
323
AUTHOR INDEX
IFORS 2014 - Barcelona
Fasano, Giorgio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-21
giorgio.fasano@thalesaleniaspace.com
Space Infrastructures & Transportation, Thales Alenia Space
Italia, Turin, Italy
Fasano, Giovanni . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-25
fasano@unive.it
Department of Management, University Ca’Foscari of
Venice, Venice, Italy
Fathi, Masood. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-41
fathi.masood@gmail.com
Organziación Industrial, TECNUN Universidad de Navarra,
San Sebastian, Guipuzcoa, Spain
Fathi, Masood . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-08
mfathi@tecnun.es
Industrial Management, Tecnun (university of Navarra), San
Sebastian, Guipuzcua, Spain
Fattahi, Ali . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-28
afattahi@ku.edu.tr
Industrial Engineering, Koc University, Istanbul, Istanbul,
Turkey
Faulin, Francisco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-41
ffaulin@pamplona.uned.es
Mathematics, UNED - Pamplona Local Center, Pamplona,
Navarre, Spain
Faulin, Javier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-41, TB-41
javier.faulin@unavarra.es
Dept. Statistics and Operations Research, Public University
of Navarre, Pamplona, Navarra, Spain
Feick, Christian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-33
christian.feick@ipoint-systems.de
iPoint-systems gmbh, Reutlingen, Germany
Feinberg, Eugene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-19
eugene.feinberg@sunysb.edu
Department of Applied Mathematics, Stony Brook University, Stony Brook, NY, United States
Felletti, Daniele . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-08
daniele.felletti@tiscali.it
Metodi Quantitativi per le Scienze Economiche e Aziendali,
Università di Milano-Bicocca, Milano, Italy
Fendek, Michal. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-15
fendek@euba.sk
Department of Operations Research and Econometrics, University of Economics in Bratislava, Bratislava, Slovakia, Slovakia
Fendekova, Eleonora . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-15
nfendek@euba.sk
Department of Business Economics, University of Economics Bratislava, Bratislava, Slovakia
Feng, Xuehao . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-04
fengxuehao@snu.ac.kr
Industrial Engineering, Seoul National University, Seoul, Korea, Republic Of
Feng, Youyi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-37
yyfeng@se.cuhk.edu
Chinese University of Hong Kong, Hong Kong
Fenollosa, M. Loreto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-36
maferi0@esp.upv.es
Economía y Ciencias Sociales, Universitat Politecnica de Va-
324
lencia, Valencia, Valencia, Spain
Fenrich, Grzegorz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-13
grzegorz.fenrich@cs.put.poznan.pl
Institute of Computing Science, Poznan University of Technology, Poznan, Poland
Ferdinand, Friska Natalia . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-37
freezk_83@yahoo.com
Department of Industrial Engineering, Pusan National University, Busan, Korea, Republic Of
Fernandez, Elena . . . . . HA-02, FA-03, MA-06, HA-31, HE-31,
HA-40, TE-44
e.fernandez@upc.edu
Statistics and Operations Research, Technical University of
Catalonia, Barcelona, Spain
Fernandez, Jose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-18, HD-45
josefdez@um.es
Estadistica e Investigacion Operativa, Universidad de Murcia, Espinardo - Murcia, Spain
Fernandez, Pascual . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-18
pfdez@um.es
Statistics and Operations Research, University of Murcia
(Spain), Spain
Fernández Cuesta, Eirik . . . . . . . . . . . . . . . . . . . . . HA-05, ME-35
eirik.cuesta@iot.ntnu.no
Norwegian University of Science and Technology, Norway
Ferrari, Hernan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-45
hferrari@unq.edu.ar
Universidad Nacional de Quilmes, Bernal, Argentina
Ferreira, Ângela . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-14
apf@ipb.pt
School of Technology and Management, Polytechnic Institute of Bragança, Bragança, Portugal
Ferreira, AnaSofia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-34
d2012166@isegi.unl.pt
ISEGI, Universidade Nova de Lisboa, Lisboa, Portugal
Ferreira, Brígida da Costa . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-39
brigida@ua.pt
Ipoc-fg, Epe, Coimbra, Portugal
Ferreira, Enrique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-13
enferrei@ucu.edu.uy
Electrical Engineering, Univ. Catolica del Uruguay, Montevideo, Uruguay
Ferreira, José Augusto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-37
ferreira@mat.uc.pt
University of Coimbra, Coimbra, Portugal
Ferreira, Liliana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-36
liliana.ferreira@ipleiria.pt
Departamento de Matemática, Instituto Politécnico de Leiria
- ESTG, Leiria, Leiria, Portugal
Ferreira, Tiago . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-41
tiago@deinfo.ufrpe.br
Statistics and Informatics, UFRPE, Recife, Pernambuco,
Brazil
Ferrer, Albert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-41
alberto.ferrer@upc.edu
Dpt. of Applied Mathematics I, Technological University of
Catalonia (UPC), Barcelona, Catalunya, Spain
IFORS 2014 - Barcelona
AUTHOR INDEX
Ferrer, José María . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-37
jmferrer@ucm.es
Universidad Complutense de Madrid, Spain
Fikar, Christian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-39
christian.fikar@boku.ac.at
Institute of Production and Logistics, University of Natural
Resources and Life Sciences, Vienna, Vienna, Austria
Ferrer, Juan-Carlos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-15
jferrer@ing.puc.cl
Ingenieria Industrial y de Sistemas, P. Universidad Catolica
de Chile, Santiago, Chile
Filatovas, Ernestas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-18
ernest.filatov@gmail.com
Institute of Mathematics and Informatics, Vilnius University,
Vilnius, Lithuania
Ferrer-Savall, Jordi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-41
jordi.ferrer-savall@upc.edu
School of Agricultural Engineering of Barcelona, The Technical University of Catalonia, Castelldefels, Catalonia, Spain
Fildes, Robert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-21
R.Fildes@lancaster.ac.uk
Management Science, Lancaster University, Lancaster,
United Kingdom
Fesel, Nilgun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-43
feselnilgun@gmail.com
Industrial Engineering, Middle East Technical University,
Ankara, Turkey
Filippi, Carlo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-36
carlo.filippi@unibs.it
Economics and Management, University of Brescia, Brescia,
BS, Italy
Fiala, Petr . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-27
pfiala@vse.cz
Dept. of Econometrics, University of Economics Prague,
Prague 3, Czech Republic
Finardi, Erlon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-26
erlon.finardi@ufsc.br
Universidade Federal de Santa Catarina, Brazil
Fiand, Frederik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-01
f.fiand@tu-braunschweig.de
Institute for Mathematical Optimization, Technical University Braunschweig, Braunschweig, Germany
Fichtinger, Johannes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-33
jfichtin@wu.ac.at
Department of Information Systems and Operations, WU Vienna, Wien, Austria
Fichtner, Wolf . . . . . . . . . . . . . . . . . . . . . . . HB-07, MA-08, HB-09
wolf.fichtner@wiwi.uni-karlsruhe.de
Chair of Energy Economics, KIT, Karlsruhe, Germany
Fidan, Mehmet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-32
mfidan@anadolu.edu.tr
Faculty of Engineering, Anadolu University, Eskisehir,
Turkey
Fiestras-Janeiro, Ma Gloria . . . . . . . . . . . . . . . . . . . . . . . . . . TA-22
fiestras@uvigo.es
Universidade de Vigo, Vigo, Spain
Fink, Andreas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-12
andreas.fink@hsu-hamburg.de
Chair of Information Systems, Helmut-Schmidt-University,
Hamburg, Germany
Fiorotto, Diego . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-41
diego_fiorotto@hotmail.com
DCCE, UNESP, São José do Rio Preto, São Paulo, Brazil
Fischer, Andreas . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-14, HA-26
Andreas.Fischer@tu-dresden.de
Department of Mathematics, Technische Universität Dresden, Dresden, Germany
Fischer, Frank . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-26
frank.fischer@mathematik.uni-kassel.de
Mathematics and Natural Sciences, University of Kassel,
Kassel, Germany
Fischer, Kathrin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-10
kathrin.fischer@tu-harburg.de
Institute for Operations Research and Information Systems,
Hamburg University of Technology (TUHH), Hamburg, Germany
Figueira, Gonçalo . . . . . . . . . . . . . . . . . . . . . . . . . . MB-04, MA-41
goncalo.figueira@fe.up.pt
Industrial Engineering and Management, Faculty of Engineering of Porto University, Porto, Portugal
Fischetti, Matteo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-11
fisch@dei.unipd.it
DEI, University of Padua, Padova, Italy, Italy
Figueira, José Rui . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-18
figueira@ist.utl.pt
Instituto Superior Tecnico, Technical University of Lisbon,
Lisbon, Portugal
Fishman, Dmytro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-44
dmytrofishman@gmail.com
Mathematics and Computer Science, University of Tartu, Estonia
Figueira, José Rui . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-32
figueira@tecnico.ulisboa.pt
Instituto Superior Técnico, Lisboa, Portugal
Fisset, Benjamin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-40
benjamin.fisset@inria.fr
INRIA, Villeneuve d Ascq, – Please Select (only U.S. / Can /
Aus), France
Figueroa, Nicolas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-25
meleos@gmail.com
Department of Economics, Pontificia Universidad Católica
de Chile, Santiago, Chile
Figueroa-García, Juan Carlos . . . . . . . . . . . . . . . . . . . . . . . HD-07
filthed@gmail.com
Engineering, Universidad Nacional de Colombia, Bogotá,
Cundinamarca, Colombia
Fitzpatrick, Trevor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-40
t.fitzpatrick@soton.ac.uk
School of Management, University of Southampton,
Southampton, United Kingdom
Fleiner, Tamas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-12
fleiner@cs.bme.hu
Department of Computer Science and Information Theory,
Budapest University of Technology and Economics, Bu-
325
AUTHOR INDEX
IFORS 2014 - Barcelona
dapest, Hungary
PESC/COPPE, Universidade Federal do Rio de Janeiro, Rio
de Janeiro, RJ, Brazil
Fleischer, Alex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-44
afleischer@fr.ibm.com
Ilog Optimization Technical Sales, IBM Software Group,
Gentilly, France
Francas, David . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-24
dfr@camelot-mc.com
Camelot Management Consultants, Mannheim, Germany
Fliedner, Thomas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-31
thomas.fliedner@tum.de
TUM School of Management, Technische Universitaet
Muenchen, Muenchen, Germany
Franco, Carlos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-02
cafranco@ucatolica.edu.co
Ingenieria Industrial, Universidad Católica de Colombia, Bogotá, Colombia
Fliege, Joerg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-03
J.Fliege@soton.ac.uk
University of Southampton, United Kingdom
Franco, L. Alberto . . . . . . . . . . . . . . . . . . MA-23, MB-23, HA-38
L.A.Franco@lboro.ac.uk
School of Business and Economics, Loughborough University, Loughborough, United Kingdom
Flisberg, Patrik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-36
pafli@mweb.co.za
The Forestry Research Institute of Sweden, Uppsala, Sweden
Flores, Hector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-37, TE-43
hector.flores@asu.edu
Industrial Engineering, Arizona State University, Tempe, AZ,
United States
Florian, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-04
mike@crt.umontreal.ca
CIRRELT, University of Montreal, Montreal, QC, Canada
Flynn, Damian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-38
FLYNN.DAMIAN@GMAIL.COM
Systems Centre, University of Bristol, Bristol, United Kingdom
Fodstad, Marte . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-29
marte.fodstad@sintef.no
SINTEF Energy Research, Trondheim, Norway
Fonollosa, Javier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-10
javier.fonollosa@upc.edu
Teoria del Senyal i Comunicacions, Universitat Politècnica
de Catalunya, Barcelona, Spain
Forsgren, Malin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-01
malin@sics.se
SICS - Swedish Institute of Computer Science, Kista, Sweden
Fortemps, Philippe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-24
Philippe.Fortemps@umons.ac.be
University of Mons, Mons, Belgium
Fortz, Bernard . . . . . . . . . . . . . . . MA-15, HA-31, HB-31, FB-41
bfortz@euro-online.org
Département d’Informatique, Université Libre de Bruxelles,
Bruxelles, Belgium
Fountoulakis, Kimon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-14
K.Fountoulakis@sms.ed.ac.uk
School of Mathematics, University of Edinburgh, United
Kingdom
Fourer, Robert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-21
4er@ampl.com
AMPL Optimization Inc., Evanston, IL, United States
Fox, Edward . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-19
efox@mail.cox.smu.edu
Marketing, Southern Methodist University, Dallas, Texas,
United States
França, Felipe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-41
felipe@cos.ufrj.br
326
François, Véronique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-02
veronique.francois@ulg.ac.be
HEC Management School of the University of Liège, Liège,
Belgium
Frangioni, Antonio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-26
frangio@di.unipi.it
Dipartimento di Informatica, Universita’ di Pisa, Pisa, Italy
Franke, Susanne . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-26, FA-36
susanne.franke@math.tu-freiberg.de
TU Bergakademie Freiberg, Germany
Franz, Axel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-03
franz@bwl.uni-mannheim.de
Center for Doctoral Studies in Business, Graduate School
of Economics & Social Sciences, University of Mannheim,
Mannheim, Germany
Freire, Fausto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-31
faustomc@ci.uc.pt
Mechanical Eng, University of Coimbra, Coimbra, Portugal
Freixas, Josep . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-27
josep.freixas@upc.edu
Applied Mathematics 3, Technical University of Catalonia,
Manresa, Spain
Frelin, Jan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-33
jan.frelin@foi.se
Defence Analysis, FOI, Stockholm, Sweden
Fresard, Marjolaine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-36
marjofresard@gmail.com
UMR AMURE, University of Brest, Quimper, France
Fricker, Ron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-30
rdfricker@nps.edu
Operations Research, Naval Postgraduate School, Monterey,
CA, United States
Fridheim, Havard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-33
havard.fridheim@ffi.no
Analysis Division, Norwegian Defence Research Establishment, Kjeller, Norway
Friedman, Lea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-29
leaf@bgu.ac.il
Industrial Engineering and Management, Ben Gurion University and Sapir College, Beer Sheva, Israel
Friedow, Isabel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-21
isabel.friedow@tu-dresden.de
Institute of Numerical Mathmatics, Dresden University of
Technology, Dresden, Germany
IFORS 2014 - Barcelona
Fries, Carlos Ernani . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-14
carlos.fries@ufsc.br
Department of Production and Systems Engineering, Federal
University of Santa Catarina, Florianopolis, Santa Catarina,
Brazil
Frini, Anissa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-31
anissa_frini@uqar.ca
Unité départementale des sciences de la gestion, Université
du Québec à Rimouski, Lévis, Québec, Canada
Fritze, Christian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-43
christian.fritze@uni-bielefeld.de
Chair for Quantitative Accounting & Financial Reporting,
University of Bielefeld, Bielefeld, Germany
Fröhling, Magnus . . . . . . . . . . . . . . . . . . . . . . . . . . MA-38, MD-38
magnus.froehling@kit.edu
Institute for Industrial Production (IIP), Karlsruhe Institute of
Technology (KIT), Karlsruhe, Germany
Froix, Anthony . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-43
anthony.froix@simon.rochester.edu
University of Rochester, Rochester, NY, United States
Fu, Jing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-35
fu.j.aa@m.titech.ac.jp
Social Engineering, Tokyo Institute of Technology, Tokyo,
Tokyo-to, Japan
Fu, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-35
mfu@umd.edu
Smith School of Business, University of Maryland, College
Park, MD, United States
Fu, Xin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-43
xfu@xmu.edu.cn
Management Science, School of Management, Xiamen University, China
Fuduli, Antonio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-26
antonio.fuduli@unical.it
Dipartimento di Matematica e Informatica, Universita’ della
Calabria, Rende, Italy
Fuentes Rojas, Ever Angel . . . . . . . . . . . . . . . . . . . . . . . . . . ME-42
ever.fuentes@gmail.com
Programa de Ingeniería Industrial, Universidad Libre, BOGOTA, Colombia
Fuentes, Claudio. . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-23, HE-25
claudio.fuentes@udp.cl
Psicologia, Universidad Diego Portales, Santiago, Region
Metropolitana, Chile
Fuentes, Manuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-01
manuelfuentesglez@gmail.com
Polytechnic University of Madrid, Madrid, Spain
Fügener, Andreas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-06
andreas.fuegener@wiwi.uni-augsburg.de
Universität Augsburg, Germany
Fügenschuh, Armin . . . . . . . . . . . . . . . . . . . . . . . . . TD-33, MD-43
fuegenschuh@hsu-hh.de
Mechanical Engineering, Helmut Schmidt University, Hamburg, Germany
Fujisawa, Katsuki . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-09
katsuki.fujisawa@gmail.com
Kyushu University, Japan
AUTHOR INDEX
Fukasawa, Ricardo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-02
rfukasaw@math.uwaterloo.ca
Combinatorics and Optimization, University of Waterloo,
Waterloo, Ontario, Canada
Funes, Mariana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-42
mfunes@eco.unc.edu.ar
Facultad de Ciencias Económicas - Universidad Nacional de
Córdoba, Córdoba, Argentina
Fung, Joey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-12
joey.fung@uts.edu.au
School of Mathematical Sciences, University of Technology,
Sydney, Australia
Furman, Kevin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-29
kevin.c.furman@exxonmobil.com
ExxonMobil Upstream Research Company, ExxonMobil,
Houston, TX, United States
Fürst, Christine . . . . . . . . . . . . . . MD-32, MA-35, FA-36, HB-36
cfuerst@uni-bonn.de
Ecology and Natural Resources Management, Center for Development Research (ZEF), Bonn, NRW, Germany
Furtado Teixeira, Alex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-28
alex.teixeira@petrobras.com.br
Cenpes, Petrobras, Rio de Janeiro, Rio de Janeiro, Brazil
Furtado, Maria Gabriela . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-05
gabisfurtado@gmail.com
Departamento de Eng. de Producao, Universidade Federal de
Sao Carlos, Sao Carlos, Sao Paulo, Brazil
G. Hernandez-Diaz, Alfredo . . . . . . . . . . . . . . . . . . . . . . . . . TB-37
agarher@upo.es
Department of Economica, Quantitative Methods and E.H.,
Pablo de Olavide University, Seville, Spain
G. Pardo, Eduardo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-37
eduardo.pardo@urjc.es
Computer Science, Universidad Rey Juan Carlos, Mostoles,
– Please Select (only U.S. / Can / Aus), Spain
G.-Tóth, Boglárka . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-21, HD-45
bog@math.bme.hu
Department of Differental Equations, Budapest University of
Technology and Economics, Hungary
Gabay, Michaël . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-21
michael.gabay@g-scop.grenoble-inp.fr
Laboratoire G-SCOP, Grenoble, France
Gabriel, Steven . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-07
sgabriel@umd.edu
Civil & Env. Engin./ Applied Math and Scientific Computation Program, University of Maryland, College Park, MD,
United States
Gadegaard, Sune Lauth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-19
sunegadegaard@gmail.com
Department of Economics and Business, Aarhus University,
Aarhus V, Denmark, Denmark
Gaidamaka, Yuliya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-31
ygaidamaka@sci.pfu.edu.ru
Telecommunication Systems Department, Peoples’ Friendship University of Russia, Moscow, Russian Federation
Gaivoronski, Alexei . . . . . . . . . . . . . . . . . . . . . . . . . . TA-05, FA-43
alexei.gaivoronski@iot.ntnu.no
327
AUTHOR INDEX
IFORS 2014 - Barcelona
Industrial Economics and Technology Management, Norwegian University of Science and Technology, Trondheim,
Norway
Galariotis, Emilios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-29
egalariotis@audencia.com
Finance, Audencia Nantes School of Management, Nantes,
France
Gaoua, Yacine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-08
ygaoua@laas.fr
LAAS-CNRS, Toulouse, France
Garín, María Araceli . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-45
mariaaraceli.garin@ehu.es
Applied Economy III, UPV/EHU, Bilbao, Bizkaia, Spain
Galé, Carmen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-11
cgale@unizar.es
Métodos Estadísticos, Universidad de Zaragoza, Zaragoza,
Spain
Garbs, Matthias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-08
matthias.garbs@wiwi.uni-goettingen.de
Chair of Production and Logistics, University of Göttingen,
Göttingen, Germany
Galiana, Francisco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-36
fgaliana@agf.upv.es
Universitat Politècnica de València (UPV), Valencia, Spain
Garbuzova-Schlifter, Maria . . . . . . . . . . . . . . . . . . . . . . . . . HE-34
mgarbuzova@eonerc.rwth-aachen.de
Institute for Future Energy Consumer Needs and Behavior
(FCN), RWTH Aachen, Aachen, Germany
Gallego de Andrade, Luiz Augusto . . . . . . . . . . . . . . . . . . MB-20
luiz.andrade@tevec.com.br
Graduate Program in Logistics Systems Engineering, University of Sao Paulo, Sao Paulo, Brazil
Gallego Salguero, Áurea . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-36
augalsal@cgf.upv.es
Cartographic Engineering, Geodesy and Photogrammetry,
Universitat Politecnica de Valencia, Valencia, Spain
Gallego, Micael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-45
Micael.Gallego@urjc.es
Ciencias de la Computación, Universidad Rey Juan Carlos,
Móstoles, Madrid, Spain
Galnaityte, Aiste . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-14
aiste.galnaityte@laei.lt
Lithuanian Institute of Agrarian Economics, Lithuania
Gamache, Michel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-06
michel.gamache@polymtl.ca
Mathematics and Industrial Engineering, École Polytechnique de Montréal, Montréal, Quebec, Canada
Gamberi, Mauro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-13
mauro.gamberi@unipd.it
Department of Management and Engineering, University of
Padova, Vicenza, Italy
Gamrath, Gerald . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-39
gamrath@zib.de
Zuse-Institute Berlin, Berlin, Germany
Gams, Matjaz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-42
matjaz.gams@ijs.si
Jozef Stefan Institute, Ljubljana, Slovenia
Gandibleux, Xavier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-29
xavier.gandibleux@univ-nantes.fr
Lina - Umr Cnrs 6241, The University of Nantes, Nantes,
France
Ganguly, Subhamoy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-10
subhamoy.ganguly@iimu.ac.in
Indian Institute of Management Udaipur, India
Gao, Jianjun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-29
jianjun.gao@sjtu.edu.cn
Automation, Shanghai Jiao Tong University, Shanghai, China
Gao, Yi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-03
ygao@swin.edu.au
Department of Aviation, Swinburne University of Technology, Hawthorn, Victoria, Australia
328
García Alvarado, Marthy Stívaliz . . . . . . . . . . . . . . . . . . . ME-40
marthy-stivaliz.garcia-alvarado.1@ens.etsmtl.ca
Departement of Automated Manufacturing Engineering,
École De Technologie Supérieure, Montreal, Quebec, Canada
García Quiles, Sergio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-03
sergio.garcia-quiles@ed.ac.uk
School of Mathematics, University of Edinburgh, Edinburgh,
United Kingdom
García-Bertrand, Raquel . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-07
Raquel.Garcia@uclm.es
Electrical Engineering, University of Castilla-La Mancha,
Ciudad Real, Ciudad Real, Spain
García-González, Javier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-10
javiergg@iit.upcomillas.es
Instituto de Investigación Tecnológica, U. Pontificia Comillas, Madri, Spain
García-Jurado, Ignacio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-22
igjurado@udc.es
Department of Mathematics, Coruna University, Coruna,
Spain
García-Nové, Eva M. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-03
eva.garcian@umh.es
University Miguel Hernández, Elche, Spain
García-Sánchez, Álvaro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-13
alvaro.garcia@upm.es
Ingeniería de Organización, Administración de Empresas
y Estadística, Universidad Politécnica de Madrid, Madrid,
Spain
García-Segovia, Purificación . . . . . . . . . . . . . . . . . . . . . . . . . TE-36
pugarse@tal.upv.es
Tecnología de Alimentos, Universitat Politecnica de Valencia, Valencia, Valencia, Spain
García-Villoria, Alberto. . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-13
alberto.garcia-villoria@upc.edu
Universitat Politècnica de Catalunya, Spain
Garcia Lopez, Juan Manuel . . . . . . . . . . . . . . . . . . FB-10, TB-44
jm.garcia@es.ibm.com
Client Solutions Professional, International Business Machines, S.A., Spain, IBM Decision Optimization Software,
Madrid, Spain
Garcia, Rita . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-31
rita.garcia@dem.uc.pt
ADAI-LAETA, University of Coimbra, Coimbra, Portugal
IFORS 2014 - Barcelona
Garcia-Alvarez-Coque, José María . . . . . . . . . . . . . . . . . . TE-36
jmgarcia@upvnet.upv.es
Economics and Social Sciences, Universitat Politècnica de
València, Valencia, Valencia, Spain
Garcia-Bernabeu, Ana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-38
angarber@esp.upv.es
Economia y Ciencias Sociales, Universitat Politècnica de
València, Alcoy, Spain
Garcia-Gonzalo, Jordi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-36
Jordigarcia@isa.utl.pt
Forest Research Centre, Instituto Superior de Agronomia,
Lisbon, Portugal
Garcia-Gutierrez, Javier . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-37
jgarciagtz@yahoo.com.mx
Transportation Engineering, UAEMex, Toluca, Mexico,
Mexico
Garcia-Rodenas, Ricardo . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-21
ricardo.garcia@uclm.es
Escuela Superior de Informatica, Universidad de Castilla La
Mancha, Ciudad Real, Ciudad Real, Spain
Gardeux, Vincent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-40
gardeux.vincent@gmail.com
Bio5, The University of Arizona, Tucson, AZ, United States
Gardner, Steven . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-18
steven.gardner@sas.com
Operations Research R&D, SAS Institute, Inc., Cary, NC,
United States
Garg, Naman . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-22
namangarg29@gmail.com
Indian Institute of Technology (IIT), Delhi, Noida, Uttar
Pradesh, India
Garrett, Daniel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-24
dfgarrett@gmail.com
Toulouse School of Economics, France
Garrison, Gary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-06
gary.garrison@belmont.edu
College of Business Administration, Belmont University,
Nashville, TN, United States
Garroppo, Rosario G. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-11
r.garroppo@iet.unipi.it
Dip. di Ingegneria dell’Informazione, Universita di Pisa,
Pisa, Italy
Garzon Rozo, Betty Johanna . . . . . . . . . . . . . . . . . . . . . . . . TE-34
s1154454@sms.ed.ac.uk
Business School Management Science, University of Edinburgh, Edinburgh, United Kingdom
Gaspar, Miguel B. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-35
mbgaspar@ipma.pt
Instituto Português do Mar e da Atmosfera I.P./IPMA, Olhão,
Portugal
Gastélum Chavira, Diego Alonso . . . . . . . . . . . . . . . . . . . . ME-29
diego.gastelum@udo.mx
Universidad de Occidente, Culiacán, Sinaloa, Mexico
Gaubert, Stephane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-24
stephane.gaubert@inria.fr
CMAP, INRIA Saclay, palaiseau, France
AUTHOR INDEX
Gaudioso, Manlio . . . . . . . . . . . . . HA-26, HD-26, HE-26, TE-26
gaudioso@dimes.unical.it
DIMES, Università della Calabria, Rende, Italy
Gauthier, Jean-Bertrand . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-11
jean-bertrand.gauthier@hec.ca
GERAD & HEC Montreal, Laval, Québec, Canada
Gavalec, Martin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-26
martin.gavalec@uhk.cz
Department of Information Technologies FIM, University of
Hradec Kralove, Hradec Kralove, Czech Republic
Gavanelli, Marco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-43
marco.gavanelli@unife.it
EnDiF - Engineering Department, Università di Ferrara, Ferrara, Italy
Gavious, Arieh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-22
ariehg@bgu.ac.il
Department of Industrial Engineering and Management, Faculty of Engineering Sciences, Ben-Gurion University„ BeerSheva, Israel
Gavirneni, Nagesh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-04
nagesh@cornell.edu
Johnson School of Business, Cornell University, Ithaca, New
York, United States
Gavranovic, Haris . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-28
haris.gavranovic@gmail.com
BAO lab, Sarajevo, Bosnia And Herzegovina
Gay, Jean-Christophe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-03
jean-christophe.gay@dauphine.fr
University Paris Dauphine, Paris, France
Gómez Esteban, Pablo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-23
pablo.gomez.esteban@urjc.es
Statistics and Operational Research, Rey Juan Carlos University, Mostoles (Madrid), Spain
Górecka, Dorota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-37
dgorecka@umk.pl
Department of Econometrics and Statistics, Nicolaus Copernicus University in Toruń, Faculty of Economic Sciences and
Management, Toruń, Poland
Gaytán, Juan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-37
juangaytan08@gmail.com
Postgraduate Studies, Engineering School, Universidad
Autónoma del Estado de México, Toluca, México, Mexico
Ge, Qiao . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-04
qiao.ge@ivt.baug.ethz.ch
ETH, Zurich, Zurich, Switzerland
Geiger, Martin Josef . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-28
m.j.geiger@hsu-hh.de
Logistics Management Department, Helmut-SchmidtUniversity, Hamburg, Germany
Gel, Esma. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-22
esma.gel@asu.edu
School of Computing, Informatics and Decision Systems
Engineering, Arizona State University, Tempe, AZ, United
States
Gelareh, Shahin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-33
shahin.gelareh@gmail.com
Lagis- Cnrs, Polytech’Lille, Villeneuve d’Ascq, France
329
AUTHOR INDEX
IFORS 2014 - Barcelona
Gelau, Tobias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-44
t.gelau@4flow.de
4flow AG, Germany
Geldermann, Jutta . . . . . . . . . . . . . . . . . . HA-08, MB-31, ME-31
geldermann@wiwi.uni-goettingen.de
Chair of Production and Logistics, Universität Göttingen,
Göttingen, Germany
ongerek@anadolu.edu.tr
Electrical and Electronics Engineering, Anadolu University,
Eskisehir, Turkey
Gergin, Zeynep . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-30
z.gergin@iku.edu.tr
Industrial Engineering Department, Istanbul Kultur University, Istanbul, Bakirkoy, Turkey
Gelmini, Alberto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-09
alberto.gelmini@rse-web.it
Power System Development, RSE SpA, Milano, Italy
Gerogiannis, Vassilis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-26
gerogian@teilar.gr
Department of Business Administration, Technological Education Institute of Thessaly, Greece, Larissa, Greece
Genç, Aşır . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-39
agenc@selcuk.edu.tr
Statistic, Selcuk University, Konya, Turkey
Geroliminis, Nikolas . . . . . . . . . . . . . . . . . HA-04, HB-04, ME-06
nikolas.geroliminis@epfl.ch
ENAC, EPFL, Lausanne, Switzerland
Gencer, Busra . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-15
bugencer@ku.edu.tr
Graduate School of Sciences and Engineering, Koc University, Turkey
Gerstl, Enrique (Tzvi) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-13
enrique.gerstl@mail.huji.ac.il
School of Business Administration, The Hebrew University,
Jerusalem, Israel
Gençer, Hüseyin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-05
e.huseyin.gencer@gmail.com
Yasar University, Turkey
Gestrelius, Sara . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-01
sarag@sics.se
SICS, KISTA, Sweden
Gendreau, Michel . . . . . . . . . . . . . . . . . . . . HB-02, HB-20, HE-41
michel.gendreau@cirrelt.ca
MAGI and CIRRELT, École Polytechnique, Montreal, Quebec, Canada
Gevezes, Theodoros . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-34
theogev@gen.auth.gr
Faculty of Engineering, Aristotle University of Thessaloniki,
Thessaloniki, Greece
Gendron, Bernard . . . . . . . . . . . . . . . . . . MD-11, HD-26, MB-36
gendron@iro.umontreal.ca
DIRO/CIRRELT, Université de Montréal, Montréal, Québec,
Canada
Ghaddar, Bissan . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-16, MD-16
bghaddar@ie.ibm.com
IBM Research, Dublin, Ireland
Genest, Blaise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-24
bgenest@irisa.fr
Cnrs, Irisa, RENNES, France
Ghaderi, Mohammad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-42
mohammad.ghaderi@esade.edu
Information Systems Management, ESADE Business School,
Sant Cugat del Valles, Catalonia, Spain
Genovese, Andrea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-44
a.genovese@sheffield.ac.uk
Management School - Logistics and Supply Chain Research
Centre, University of Sheffield, Sheffield, United Kingdom
Ghahraman, Abaghan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-10
abaghan@gmail.com
Business Department, Universitat Autonoma de Barcelona,
Barcelona, Spain
Gentile, Claudio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-10
gentile@iasi.cnr.it
IASI-CNR, Roma, Italy
Ghahroodi, Sajjad Rahimi . . . . . . . . . . . . . . . . . . . . . . . . . . HD-37
sghahroodi@ku.edu.tr
Koc University, Istanbul, Turkey
Gentile, Guido . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-41
guido.gentile@uniroma1.it
Dipartimento di Ingegneria Civile Edile e Ambientale, University of Rome "La Sapienza’, Università degli Studi di
Roma, Roma, Italy
Ghandehari, Mahsa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-19
ghandehary@yahoo.com
Management, University of Isfahan, Isfahan, Iran, Islamic
Republic Of
Georgiou, Andreas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-23
acg@uom.edu.gr
Department of Business Administration, University of Macedonia, Thessaloniki, Greece
Ger, Metin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-07
ger.metin@gmail.com
Civil Engineering, Istanbul Aydin University, istanbul,
Turkey
Gerasimova, Ilmira . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-30
tarot_gera@mail.ru
Ufa State Aviation Technical University, Ufa, Russian Federation
Gerek, Omer Nezih . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-32
330
Gharbi, Ali . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-13
ali.gharbi@etsmtl.ca
Automated Prduction, Ecole de Technologie Superieure,
Montreal, Quebec, Canada
Gheyssens, Jonathan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-08
jgheyssens@gmail.com
NADEL, ETH Zürich, Zürich, Switzerland
Ghoniem, Ahmed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-19
aghoniem@isenberg.umass.edu
Operations & Information Management, University of Massachusetts Amherst, USA, USA, United States
Ghossoub, Mario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-29
m.ghossoub@imperial.ac.uk
Finance - Business School, Imperial College London, Lon-
IFORS 2014 - Barcelona
don, United Kingdom
Giallombardo, Giovanni . . . . . . . . . . . . . . . . . . . . . HD-26, TE-26
giallo@dimes.unical.it
DIMES, University of Calabria, Rende, Italy
Gianessi, Paolo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-11
paolo.gianessi@lipn.univ-paris13.fr
LIPN, University Paris 13, Villetaneuse, France
Gianfreda, Angelica . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-09
agianfreda@london.edu
Management Science and Operations, London Business
School, London, United Kingdom
AUTHOR INDEX
Gnecco, Giorgio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-16, HD-31
giorgio.gnecco@imtlucca.it
IMT - Institute for Advanced Studies, Lucca, Lucca, Italy
Göb, Rainer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-21
goeb@mathematik.uni-wuerzburg.de
Statistics, University of Wuerzburg, Wuerzburg, Germany
Gobbato, Luca . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-45
luca.gobbato@polito.it
Department of Control and Computer Engineering, Politecnico di Torino, Torino, Italy
Giarola, Sara. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-38
s.giarola10@imperial.ac.uk
Imperial College London, United Kingdom
Godoi, Adilson Preto de . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-10
adilsongodoi@hotmail.com
Programa de Pós Graduação em Engenharia Elétrica, UnespUniv. Estadual Paulista, Bauru, São Paulo, Brazil
Gibson, Andy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-08
Andrew.gibson@manchester.ac.uk
Electrical, Manchester university, Ma nchester, United Kingdom
Goel, Gagan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-22
gagangoel@google.com
Google Research, New York, New York, New York, United
States
Gijswijt, Dion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-09
dion.gijswijt@gmail.com
EWI, TU Delft, Delft, Netherlands
Goel, Vikas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-29
goelvikas@gmail.com
ExxonMobil, Houston, TX, United States
Gila Arrondo, Aranzazu . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-18
agarrondo@um.es
Statistics and Operation Research, University of Murcia, Espinardo, Murcia, Spain
Goerigk, Marc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-01
goerigk@mathematik.uni-kl.de
Technische Universität Kaiserslautern, Kaiserslautern, Germany
Gimbert, Hugo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-24
hugo.gimbert@labri.fr
CNRS, LaBRI, Bordeaux, France
Goes, Anderson Roges Teixeira . . . . . . . . . . . . . . . . . . . . . MA-08
artgoes@ufpr.br
Federal University of Parana, Curitiba, Paraná, Brazil
Giner, Salvador . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-36
SALVADOR.GINER-ROSA@roquette.com
Purchasing department, Roquette Laisa España, BenifaióValencia, Spain
Goff, Katherine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-19
kgoff@ryerson.ca
Department of Mechanical and Industrial Engineering, Ryerson University, Toronto, Ontario, Canada
Ginestar, Concepción . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-36
cginesta@upvnet.upv.es
Universidad Politécnica de Valencia., Valencia, Spain
Gogi, Anastasia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-23
a.gogi@lboro.ac.uk
School of Business and Economics, Loughborough University, Cambridge, United Kingdom
Ginzo Villamayor, María José . . . . . . . . . . . . . . . . . . . . . . . TE-21
mariajose.ginzo@usc.es
Universidad de Santiago de Compostela, Spain
Giovannelli, Antonio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-34
a.giovannelli@loccioni.com
Research@energy, Loccioni Group, Angeli di Rosora, Italy
Glass, Celia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-31
c.a.glass@city.ac.uk
Cass Business School, City University, London, United Kingdom
Gleixner, Ambros . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-39
gleixner@zib.de
Optimization, Zuse Institute Berlin (ZIB), Berlin, Germany
Glover, Fred . . . . . . . . . . MB-11, HB-40, HD-40, TD-40, TE-40
fredwglover@yahoo.com
ECEE, University of Colorado, Boulder, Clorado, United
States
Glowinski, Roland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-29
roland@math.uh.edu
Department of Mathematics, University of Houston, Houston, United States
Goh, Mark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-43
tligohkh@nus.edu.sg
The Logistics Institute–Asia/Pacific, National University of
Singapore, Singapore, Singapore
Gökçen, Hadi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-39
hgokcen@gazi.edu.tr
Industrial Engineering, Gazi University, Ankara, Maltepe,
Turkey
Golany, Boaz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-22
golany@ie.technion.ac.il
Industrial Engineering & Management, Technion - Israel Institute of Technology, Haifa, Israel
Goldberg, Noam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-17
noam.goldberg@biu.ac.il
Bar-Ilan University, Israel
Goldengorin, Boris . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-18
Goldengorin@gmail.com
LATNA - Laboratory of Algorithms and Technologies for
Networks Analysis and Department of Applied Mathematics
and Informatics, Nizhny Novgorod branch of The National
Research University Higher School of Economics, Nizhny
331
AUTHOR INDEX
IFORS 2014 - Barcelona
Novgorod, Russian Federation
Golesorkhi, Sougand . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-41
S.Golesorkhi@mmu.ac.uk
Centre for International Business and Innovation, Manchester
Metropolitan University, Manchester, United Kingdom
Golubtsov, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-36
pgolubtsov@gmail.com
Moscow State University, Moscow, Russian Federation
Gomes Júnior, Silvio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-14
silviofgj@gmail.com
Coordenação de Engenharia de Produção, UEZO-Fundação
Centro Universitário Estadual da Zona Oeste, Rio de Janeiro,
Rio de Janeiro, Brazil
Gomes, A. Miguel . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-21, FB-27
agomes@fe.up.pt
INESC TEC, Faculdade de Engenharia, Universidade do
Porto, Porto, Portugal
Gomes, Alvaro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-09
agomes@deec.uc.pt
Dep Eng Electrotecnica e Computadores, Univ. Coimbra,
Coimbra, Portugal
Gomes, Christina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-45
christina-gomes@uol.com.br
Linguistics, Universidade Federal do Rio de Janeiro, Petrópolis, Rio de Janeiro, Brazil
Gomes, Gastão . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-45
gastao@im.ufrj.br
Métodos Estatísticos, Universidade Federal do Rio de
Janeiro, Rio de Janeiro, Rio de Janeiro, Brazil
Gomes, Luiz F. Autran M. . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-34
autran@ibmecrj.br
Management, Ibmec/RJ, Rio de Janeiro, RJ, Brazil
Gomez Padilla, Alejandra . . . . . . . . . . . . . . . . . . . HB-27, MD-40
alejandra.gomez@cucei.udg.mx
Industrial Engineering, University of Guadalajara, Guadalajara, Jalisco, Mexico
Gomez Ravetti, Martin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-13
martin@dcc.ufmg.br
Computer Science, Federal University of Minas Gerais, Belo
Horizonte, Brazil
Gomez San Roman, Tomas . . . . . . . . . . . . . . . . . . . . . . . . . MB-10
tomas.gomez@iit.upcomillas.es
Institute for Research in Technology - IIT, Universidad Pontificia Comillas, ICAI School of Engineering, Madrid, Spain
Gomez, Arthur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-40
atgomezbr@gmail.com
University of Vale do Rio dos Sinos, Porto Alegre, rs, Brazil
Gomez, Elena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-41
elenags@cta.uva.es
Systems Engineering and Automatic Control, University of
Valladolid, Valladolid, Spain
Gomez, Susana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-29
susanag@unam.mx
Instituto de Matematicas Aplicadas y Sistemas, Universidad
Nacional A. de Mexico, Mexico, Mexico
Gomis, Oriol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-10
ogomis@irec.cat
332
Universitat Politecnica de Catalunya, Barcelona, Spain
Gomis, Oriol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-10
oriol.gomis@citcea.upc.edu
Electrical Engineering, CITCEA-UPC, Barcelona, Spain
Goncalves, Gilles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-19
goncalves.gilles@gmail.com
Lgi2a, Ea 3926, Faculté des Sciences Appliquées, Bethune,
France, France
Gonçalves, José Fernando . . . . . . . . . . . . . . . . . . . HA-21, HE-21
jfgoncal@fep.up.pt
LIAAD, INESC TEC, Faculdade de Economia do Porto, Universidade do Porto, Porto, Portugal
Goncalves, Jose Mauricio Brasil . . . . . . . . . . . . . . . . . . . . . HE-34
josemauriciobrasil@gmail.com
Centro Tecnológico - Escola de Engenharia, UFF - Universidade Federal Fluminense, Niteroi, RJ, Brazil
Gonçalves, Max Leandro Nobre . . . . . . . . . . . . . . . . . . . . . HD-14
maxlng@ufg.br
Mathematic, Federal university of Goiás, Goiania, Goiás,
Brazil
Gonçalves, Rogério dos Reis . . . . . . . . . . . . . . . . . . . . . . . . . TD-10
rogerio@unemat-net.br
Universidade do Estado de Mato Grosso, Sinop, Mato
Grosso, Brazil
Gondzio, Jacek . . . . . . . . . . . . . . . . . . . . . . HA-14, TD-17, HB-26
j.gondzio@ed.ac.uk
School of Mathematics, University of Edinburgh, Edinburgh,
United Kingdom
Gong, Bing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-40
gongbing1112@gmail.com
Department of Industrial Engineering„ Universidad Politécnica de Madrid, Madrid, Spain
Gong, Yeming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-19
gong@em-lyon.com
Emlyon Business School, Lyon, France
Gonzalez, Diana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-14
diagon@etsii.upv.es
Universitat Politècnica de València, Spain
Gonzalez, Sergio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-41
sgonzalezmarti@uoc.edu
Open University of Catalonia, Barcelona, Spain
Gonzalez-Araya, Marcela . . . . . . . . . . . . . . . . . . . ME-14, HD-36
mgonzalez@utalca.cl
Departamento de Modelación y Gestión Industrial, Universidad de Talca, Curicó, Región del Maule, Chile
Gonzalez-Brevis, Pablo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-26
P.Gonzalez-Brevis@sms.ed.ac.uk
School of Mathematics, University of Edinburgh, United
Kingdom
Gonzalez-Velarde, Jose Luis . . . . . . . . . . . . . . . . . . . . . . . . . TB-37
gonzalez.velarde@itesm.mx
Manufacturing Systems, Monterrey Tech, Monterrey, N.L.,
Mexico
González Rueda, Ángel Manuel . . . . . . . . . . . . . . . . . . . . . . TE-21
angelmanuel.gonzalez@usc.es
Estadística e Investigación Operativa, Universidad de Santiago de Compostela, Santiago de Compostela, Spain
IFORS 2014 - Barcelona
González Vayá, Marina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-20
vayam@ethz.ch
Power Systems Laboratory, ETH Zurich, Zurich, Switzerland
González, Rafael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-41
rgonzalezm@repsol.com
Advanced Control, Petronor, Repsol, Muskiz, Spain
González-Császár, Eduardo . . . . . . . . . . . . . . . . . . . . . . . . . TE-19
e.gonzalez@ieee.org
Analysis, Portofino Consultores, Santiago, Chile
AUTHOR INDEX
legouveia@fc.ul.pt
DEIO - Departamento de Estatística e Investigação Operacional, Universidade de Lisboa - Faculdade de Ciências,
Lisboa, Portugal
Goverde, Rob . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-01
r.m.p.goverde@tudelft.nl
Transport and Planning, Delft University of Technology,
Delft, Netherlands
Govindaraj, Suresh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-19
sureshg@business.rutgers.edu
Rutgers, Newark, United States
González-Díaz, Julio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-21
julio.gonzalez@usc.es
Estadística e Investigación Operativa, Universidad de Santiago de Compostela, Santiago de Compostela, Spain
Goyal, Vineet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-20
vgoyal@ieor.columbia.edu
Columbia University, New York, NY, United States
González-Diéguez, Francisco José . . . . . . . . . . . . . . . . . . . . TE-21
franciscojose.gonzalez@usc.es
Matemática Aplicada, Universidad de Santiago de Compostela, Santiago de Compostela, Spain
Goycoolea, Marcos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-29
mgoycool@gmail.com
School of Business, Universidad Adolfo Ibanez, Santiago,
Chile
Goossens, Dries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-35
Dries.Goossens@ugent.be
Management Information science and Operations Management, Ghent University, Gent, Belgium
Gozun, Brian Canlas . . . . . . . . . . . . . . . . . . . . . . . . MB-04, TB-40
bcgozun@gmail.com
De La Salle University Manila, Manila, Philippines
Gorelkina, Olga . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-24
ogorelkina@gmail.com
Research on Collective Goods, Max Planck Institute, Bonn,
Germany
Gören, Merve . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-43
merve.goren@boun.edu.tr
Industrial Engineering, Boğaziçi University, İstanbul, Turkey,
Turkey
Gorgone, Enrico . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-26, HB-31
egorgone@ulb.ac.be
Département d’Informatique, Université Libre de Bruxelles,
Bruxelles, Belgium
Gori, Marco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-16
marcoxgori@gmail.com
University of Siena, Siena, Italy
Gortázar, Francisco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-37
francisco.gortazar@urjc.es
Computer Science, Universidad Rey Juan Carlos, Móstoles,
Madrid, Spain
Goslawski, Marek . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-12
marek.goslawski@put.poznan.pl
Poznan University of Technology, Poznan, Poland
Goto, Hiroyuki . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-30
goto-h@hosei.ac.jp
Department of Industrial & System Engineering, Hosei University, Koganei, Tokyo, Japan
Gotzamani, Katerina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-23
kgotza@uom.gr
Business Administration, University of Macedonia, Thessaloniki, Greece
Goulart, Paul . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-20
pgoulart@control.ee.ethz.ch
ETH Zurich, Automatic Control Laboratory, Zurich, Switzerland
Gouveia, Luís. . . . . . . . . . . . . . . . HB-02, MB-02, MD-11, HA-31
Graham, Colin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-22
cagraham@cuhk.edu.hk
The Chinese University of Hong Kong, Hong Kong, Hong
Kong
Granlund, Luke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-11
granlund@pa.msu.edu
Michigan State University, East Lansing, United States
Grantz, Volker . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-03
Volker.Grantz@frequentis.com
Frequentis, Vienna, Austria
Grasas, Alex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-41
alex.grasas@upf.edu
Economics and Business, Universitat Pompeu Fabra,
Barcelona, Spain
Grasman, Scott . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-41
grasman@umich.edu
Industrial and Systems Engineering, Rochester Institute of
Technology, Rochester, MI, United States
Gratton, Serge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-14, TB-18
serge.gratton@enseeiht.fr
ENSEEIHT, Toulouse, France
Graveney, Mike . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-14
mike@mjgraveney.wanadoo.co.uk
Warwick University, Warwick, United Kingdom
Gravier, Sylvain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-12
sylvain.gravier@ujf-grenoble.fr
Institut Fourier, Saint Martin D’hères, France
Greasley, Andrew. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-38
a.greasley@aston.ac.uk
Operation Information Management, Aston University, Birmingham, United Kingdom
Greco, Salvatore . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-24, MB-24
salgreco@unict.it
Deapartment of Economics and Quantitative Methods, University of Catania, Catania, Italy
333
AUTHOR INDEX
IFORS 2014 - Barcelona
Greenstein, Gil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-42
gilgr@hit.ac.il
Faculty of Management of Technology, Holon Institute of
Technology, Holon, Israel
Gregorio, Rodrigo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-25
rgregori@alumnos.inf.utfsm.cl
Departamento de Informática, Universidad Técnica Federico
Santa María, Valparaíso, Valapraíso, Chile
Greistorfer, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-04, HB-40
peter.greistorfer@kfunigraz.ac.at
Produktion und Logistik, Karl-Franzens-Universität Graz,
Graz, Austria
Greiving, Stefan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-40
stefan.greiving@tu-dortmund.de
TU Dortmund, Dortmund, Germany
Grether, Dominik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-04
grether@vsp.tu-berlin.de
TU Berlin, Berlin, Germany
Gribkovskaia, Irina . . . . . . . . . . . . . . . . . MA-05, MB-05, MD-05
irina.gribkovskaia@himolde.no
Faculty of Economics, Informatics and Social Sciences,
Molde University College - Specialized University in Logistics, Molde, Norway
Grieco, Antonio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-13
antonio.grieco@unisalento.it
Dip.to di Ingegneria dell Innovazione, Università del Salento,
Lecce, Italy
Griffin, Joshua . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-18, TB-25
Joshua.Griffin@sas.com
SAS Institute, United States
Grigoroudis, Evangelos . . . . . . . . . . . . . . . TA-29, TE-29, MD-38
vangelis@ergasya.tuc.gr
Department of Production Engineering & Management,
Technical University of Crete, Chania, Greece
Grimaud, Frédéric . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-13
grimaud@emse.fr
IE & Computer science, Ecole des Mines de Saint Etienne,
Saint Etienne, France
Grippa, Pasquale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-27
Pasquale.Grippa@aau.at
Networked and Embedded Systems, Alpen-Adria Universität
Klagenfurt, Klagenfurt, Carinthia, Austria
Grippo, Luigi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-25
grippo@dis.uniroma1.it
DIS, Univ.LaSapienza Roma, Roma, Italy
Gritzmann, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-25, TB-45
gritzman@ma.tum.de
Mathematics, TU München, Munich, Germany
Groß, Martin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-11
gross@math.tu-berlin.de
Mathematics, Technische Universität Berlin, Germany
Großmann, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-01
peter.grossmann@tu-dresden.de
Faculty of Transportation and Traffic Sciences, TU Dresden,
Dresden, Saxony, Germany
Gronalt, Manfred . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-32, MD-36
Manfred.Gronalt@boku.ac.at
334
Institute of Production and Logistics, University of Natural
Resources and Applied Life Sciences, Vienna, Austria
Grossmann, Ignacio . . . . . . . . . . . . . . . . . . . . . . . . . HB-29, HD-29
grossmann@cmu.edu
Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA, United States
Grunow, Martin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-08
martin.grunow@tum.de
TUM School of Management, Technische Universität
München, München, Germany
Guajardo, Mario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-22
Mario.Guajardo@nhh.no
Business and Management Science, NHH Norwegian School
of Economics, Bergen, Norway
Guan, Lei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-27
guanlei@bit.edu.cn
Department of Management Science and Logistics, Beijing
Institute of Technology, Beijing, China
Gubarev, Fedor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-18, TE-18
fedor.gubarev@datadvance.net
Datadvance, Moscow, Russian Federation
Gudelj, Anita . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-02, HD-05
anita@pfst.hr
Faculty of Maritime Studies, University of Split, Split, Croatia
Guenther, Hans-Otto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-33
hans-otto.guenther@hotmail.de
Industrial Engineering, Seoul National University, Seoul, Korea, Republic Of
Guerra, Manuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-24
mguerra@iseg.utl.pt
Mathematics, ISEG - University of Lisbon, Lisboa, Portugal
Guerra-Vázquez, Francisco . . . . . . . . . . . . . . . . . . . . . . . . . FB-26
francisco.guerra@udlap.mx
Actuaria y Matematicas, Fundación Universidad de las Americas Puebla, San Andres Cholula, Puebla, Mexico
Guerrero, Victoria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-10
victoria.gmestre@gmail.com
Engineering Projects, University of Castilla - La Mancha,
Socuéllamos, Ciudad Real, Spain
Guerriero, Francesca . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-45
francesca.guerriero@unical.it
D.I.M.E.G.: Mechanical, Energy and Management Engineering, University of Calabria, Rende, Italy
Guerrin, Francois . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-07
francois.guerrin@cirad.fr
UPR Recyclage & Risque, Inra & Cirad, Montpellier Cedex
5, France
Guezzen, Amine Hakim . . . . . . . . . . . . . . . . . . . . . HE-35, MB-44
amine.guezzen@yahoo.fr
Faculty of Technology, Universy of Tlemcen, Tlemcen, Algeria
Guignard-Spielberg, Monique . . . . . . . . . . . . . . . . . . . . . . . HB-11
guignard_monique@yahoo.fr
OPIM, University of Pennsylvania, Philadelphia, PA, United
States
Guillen Gonsalbez, Gonzalo . . . . . . . . . . . . . . . . . . . . . . . . . TD-41
IFORS 2014 - Barcelona
gonzalo.guillen@urv.cat
Enginyeria Química, Universitat Rovira i Virgili, Tarragona,
Catalonia, Spain
Guimarães, Luis . . . . . MB-04, FA-06, MA-19, MA-41, MD-41
guimaraes.luis@fe.up.pt
INESC TEC, Faculadade de Engenharia, Universidade do
Porto, Portugal
Guimaraes, Renato . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-03
renato.guimaraes@icn-groupe.fr
Operations Management, ICN Business School, Nancy,
France
Guimarans, Daniel . . . . . . . . . . . . . FB-25, HE-33, TD-41, TE-41
daniel.guimarans@nicta.com.au
Optimisation Research Group, NICTA, Eveleigh, New South
Wales, Australia
Gujarathi, Saurabh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-11
saurabh.gujarathi@gmail.com
Michigan State University, East Lansing, United States
Gül, Sait . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-27
saitgul@halic.edu.tr
Halic University, Turkey
Guler, Kemal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-41
kemal.guler@hp.com
Decision Technologies, Hewlett-Packard Labs, Palo Alto, Ca
Gullhav, Anders N. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-31
anders.gullhav@iot.ntnu.no
Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology,
Trondheim, Trondheim, Norway
Gullu, Refik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-39
refik.gullu@boun.edu.tr
Industrial Engineering Department, Bogazici University, Istanbul, Turkey
Gümüşoğlu, Şevkinaz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-43
sevkinaz.gumusoglu@yasar.edu.tr
Yaşar University Vocational School, izmir, Turkey
Gumus, Mehmet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-32
mehmet.gumus@mcgill.ca
Desautels Faculty of Management, McGill University, Montreal, Quebec, Canada
Günay, Melike . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-10
m.gunay@iku.edu.tr
Computer Engineering, İstanbul Kültür Universit, Turkey
Gundegjerde, Christian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-05
christian.gundegjerde@creuna.no
Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology,
Trondheim, Norway
Gunes, Evrim Didem . . . . . . . . . . . . . . . . . . . . . . . . HE-15, MB-39
egunes@ku.edu.tr
Operations and Information Systems, Koc University, Istanbul, Turkey
Guney, Evren. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-15
evrenguney@arel.edu.tr
Arel University, Istanbul, Turkey
Güngör, Kıymet Özge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-18
kiymetozgegungor@gmail.com
AUTHOR INDEX
Industrial Engineering, Faculty of Engineering, Eskişehir,
Turkey
Gunluk, Oktay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-11
gunluk@us.ibm.com
Math. Sciences, IBM Research – USA, NY, United States
Gunn, Eldon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-36
eldon.gunn@dal.ca
Industrial Engineering, Dalhousie University, Halifax, Nova
Scotia, Canada
Gunnec, Dilek . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-15
dilek.gunnec@ozyegin.edu.tr
Industrial Engineering, Ozyegin University, Istanbul, Turkey
Gunnerud, Vidar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-28
vidargu@ntnu.no
Trondheim, Norway
Günther, Christian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-18
Christian.Guenther5@student.uni-halle.de
Martin-Luther-Universität Halle-Wittenberg, Germany
Günther, Markus . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-44, MD-44
markus.guenther@uni-bielefeld.de
Department of Business Administration and Economics,
Bielefeld University, Bielefeld, Germany
Guo, Jing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-29
jg3222@columbia.edu
Industrial Engineering and Operations Research, Columbia
University in the City of New York, New York, NY, United
States
Guo, Pengfei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-22
pengfei.guo@polyu.edu.hk
Faculty of Business, Hong Kong Polytechnic University,
Hong Kong
Guo, Tiande . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-16
tdguo@ucas.ac.cn
School of Mathematical Sciences, University of Chinese
Academy of Sciences, Beijing, China
Gupta, Sudheer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-19
sudheerg@sfu.ca
Faculty of Business, Simon Fraser University, Vancouver,
BC, Canada
Gupta, Umesh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-34
umesh@maths.iitkgp.ernet.in
Demartment of Mathematics, Indian Institute of Technology
Kharagpur, Kharagpur, West Bengal, India
Guragac, Burak . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-32
burak.guragac@ozu.edu.tr
Ozyegin University, Istanbul, Turkey
Gürel, Sinan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-42
gsinan@metu.edu.tr
Department of Industrial Engineering, Middle East Technical
University, Ankara, Turkey
Güreli, Suzan. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-43
suzangureli@hotmail.com
Industrial Engineering Department, Istanbul Kültür University, Istanbul, Turkey
Gurgur, Cigdem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-39
gurgurc@ipfw.edu
Management, Purdue University, Fort Wayne, IN, United
335
AUTHOR INDEX
IFORS 2014 - Barcelona
States
Gurrieri, Massimo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-24
Massimo.Gurrieri@umons.ac.be
University of Mons, Mons, Belgium
Gurski, Frank . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-39
frank.gurski@hhu.de
Institute of Computer Science, University of Düsseldorf,
Düsseldorf, Germany
Gutiérrez, Gloria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-41
gloria@autom.uva.es
Systems Engineering and Automatic Control, University of
Valladolid, Valladolid, Spain
Hagen, Martine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-05
marthage@stud.ntnu.no
Norwegian University of Science and Technology, Trondheim, Please Select, Norway
Haghani, Ali . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-04, HD-04
haghani@umd.edu
Civil and Environmental Engineering, University of Maryland at College Park, College Park, Maryland, United States
Haghighat Sefat, Morteza . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-20
Morteza.Haghighat@pet.hw.ac.uk
Institute of Petroleum Engineering, Heriot Watt University,
Edinburgh, Select State, United Kingdom
Gutierrez, Sandra . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-40
sandra.gutierrez@epn.edu.ec
Matemática, Escuela Politecnica Nacional, Quito, Pichincha,
Ecuador
Hahn, Gerd J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-24
hahn@bwl.uni-mannheim.de
CAMELOT Management Consultants Endowed Assistant
Professorship for Supply Chain Management, University of
Mannheim, Mannheim, Germany
Gutjahr, Walter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-31
walter.gutjahr@univie.ac.at
Department of Statistics and Decision Support Systems, University of Vienna, Vienna, Vienna, Austria
Hahn, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-11
hahn@seas.upenn.edu
Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, United States
Gwiggner, Claus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-40
claus.gwiggner@uni-hamburg.de
Operations Research, University of Hamburg, Hamburg, Germany
Hain, Vladimir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-44
vladimirhain@gmail.com
Institute of History and Theory of Architecture and Monument Restoration, Slovak university of technology, Faculty of
architecture, Bratislava, Slovakia, Slovakia
Ha, Albert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-37
imayha@ust.hk
Information Systems, Business Statistics and Operations
Management, Hong Kong University of Science and Technology, Hong Kong, Hong Kong
Ha, Byung-Hyun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-13
byunghyun.ha@gmail.com
Dept. of Industrial Engineering, Pusan National University,
Korea, Republic Of
Hajian, Mozafar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-27
mozafar.hajian@uk.ibm.com
IBM, United Kingdom
Hakanen, Jussi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-18
jussi.hakanen@jyu.fi
Dept. of Mathematical Information Technology, University
of Jyvaskyla, University of Jyvaskyla, Finland
Haanpaa, Tomi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-18
haanpaa.tomi@gmail.com
Primapower / Finn-Power, Finland
Halfoune, Nadia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-16
n_halfoune2011@yahoo.fr
Computer Science Department„ A/Mira University of Béjaia,
Bejaia, Algeria
Habenicht, Walter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-19
walter.habenicht@uni-hohenheim.de
Business Administration, University of Hohenheim,
Stuttgart, Germany
Halim, Ronald . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-04
r.a.halim@tudelft.nl
Transport and Logistics, Delft University of Technology,
Delft, Zuid Holland, Netherlands
Hablal, Houria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-16
hablalhouria@yahoo.fr
Technology, University of Bejaja, Albania
Hallak, Nadav . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-38
nadav_hallak@outlook.com
Faculty of Industrial Engineering and Management, Technion
- Israel Institute of Technology, Israel
Haddad, Jack . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-04
jh@technion.ac.il
Technion Israel Institute of Tech, Haifa, Israel
Hadi-Vencheh, Abdollah. . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-02
abdh12345@yahoo.com
Isfahan, Iran, Islamic Republic Of
Hagemann, Johannes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-13
johannes.hagemann@mbtech-group.com
MBtech Group GmbH & Co. KGaA, Sindelfingen, Germany
Hagemann, Simon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-20
s_hagemann@web.de
Chair for Energy Economics, University of Duisburg Essen,
Germany
336
Halme, Merja . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-14, HB-18
merja.halme@aalto.fi
Information and Service Economy, Aalto School of Economics, Aalto, Finland
Halulu, Sila . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-21, HB-43
s.halulu@iku.edu.tr
Industrial Engineering, Istanbul Kultur University, Istanbul,
Turkey
Halvorsen, Ina Blomseth . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-05
halvorsen.ina@bcg.com
Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology,
Trondheim, Norway
IFORS 2014 - Barcelona
Halvorsen-Weare, Elin E. . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-05
Elin.Halvorsen-Weare@sintef.no
Department of Applied Mathematics, Sintef Ict, Oslo, Norway
Hamacher, Silvio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-29
hamacher@puc-rio.br
PUC-Rio, Rio de Janeiro, Brazil
Hamedi, Masoud . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-04
masoud@umd.edu
Civil & Environmental Engineering Department, University
of Maryland, College Park, MD, United States
Hamid, Mona . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-25
M.hamid-2@sms.ed.ac.uk
Business School, Edinburgh University, Edinburgh, Scotland,
United Kingdom
Hamouda, Abdelmagid S. . . . . . . . . . . . . . . . . . . . . ME-21, TA-42
hamouda@qu.edu.qa
Mechanical and Industrial Engineering, Qatar University,
Doha, Qa, Qatar
Hamouda, Essia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-40
essia@cs.ucr.edu
School of Business Administration, University of California,
Riverside, CA, United States
AUTHOR INDEX
ban Planning and Land-Use Planning, Trenčín, Slovakia
Handl, Julia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-02
julia.handl@mbs.ac.uk
Manchester Business School, University of Manchester,
Manchester, United Kingdom
Hanemann, Philipp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-07
philipp.hanemann@uni-leipzig.de
Institute for Infrastructure and Resources Managemen, Universität Leipzig, Leipzig, Saxony, Germany
Hanke, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-27
Michael.Hanke@uni.li
Institute for Financial Services, University of Liechtenstein,
Vaduz, Liechtenstein
Hansen, Ole . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-44
o.hansen@4flow.de
4flow AG, Germany
Hanzalek, Zdenek . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-08
hanzalek@fel.cvut.cz
CTU Prague, Prague, Czech Republic
Hao, Jin-Kao . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-40
hao@info.univ-angers.fr
LERIA, Université d’Angers, Angers, France
Hampel, David . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-09
DHampel@seznam.cz
Mendel University in Brno, Brno, Czech Republic
Harabor, Daniel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-25, HE-33
dharabor@gmail.com
NICTA, Sydney, Australia, Australia
Hamzadayi, Alper . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-12
alper.hamzadayi@deu.edu.tr
Dokuz Eylul University, Turkey
Harada, Mutsumi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-35
t03004@sakura.juntendo.ac.jp
Juntendo University, Japan
Han, Congying . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-16
hancy@ucas.ac.cn
School of Mathematical Sciences, University of Chinese
Academy of Sciences, Beijing, China
Harbering, Jonas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-01
jo.harbering@math.uni-goettingen.de
Institute for Numerical and Applied Mathematics, University
of Goettingen, Goettingen, Lower Saxony, Germany
Han, Deren . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-38
handeren@njnu.edu.cn
School of Mathematical Sciences, Nanjing Normal University, Nanjing, Jiangsu, China
Hariche, Kamal. . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-23, ME-29
hariche_kamal@yahoo.fr
Commercial science, Bejaia University, Bejaia, Algeria
Han, Sangwoo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-42
swhan@snu.ac.kr
Seoul National Univ., Korea, Republic Of
Han, Xin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-13
hanxin.mail@gmail.com
School of Software, Dalian University of Technology, Dalian,
Liaoning Province, China
Hanafi, Saïd . . . . . . . . . . . . . . . . . . . . . . . . . . MB-11, TA-28, TE-40
said.hanafi@univ-valenciennes.fr
Istv2, Lamih-siade, University of Valenciennes, Valenciennes, France
Hanalioglu, Tagi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-39
taghi.khaniyev@boun.edu.tr
Bogazici University, Istanbul, Turkey
Hanany, Eran . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-22
hananye@post.tau.ac.il
Tel Aviv University, Ramat Aviv, Israel
Hanáček, Tomás . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-27
hanacek.tomas@gmail.com
PhD. Student, Faculty of architecture, STU, Institute of Ur-
Harison, Elad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-40
eladha@shenkar.ac.il
Industrial Engineering and Management, Shenkar College of
Engineering and Design, Ramat Gan, Israel
Haro, Noemi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-14
nharo@colson.edu.mx
El Colegio de Sonora, Hermo, Mexico
Harper, Paul . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-09, FB-13
harper@cardiff.ac.uk
School of Mathematics, Cardiff University, Cardiff, Wales,
United Kingdom
Harris, Shannon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-06
sharris@katz.pitt.edu
Katz Graduate School of Business, Pittsburgh, PA, United
States
Harrison, Norma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-32
Norma.Harrison@mgsm.edu.au
Macquarie Graduate School of Management, Macquarie University, Sydney, NSW, Australia
Hart, Diane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-38
d.hart@mmu.ac.uk
337
AUTHOR INDEX
IFORS 2014 - Barcelona
Business School, Manchester Metropolitan University,
Manchester, United Kingdom
Hartikainen, Markus . . . . . . . . . . . . . . . . . . . . . . . MD-18, ME-18
markus.e.hartikainen@jyu.fi
Department of Mathematical Information Technology, University of Jyväskylä, University of Jyvaskyla, Finland
Hartl, Richard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-42
richard.hartl@univie.ac.at
Business Admin, University of Vienna, Vienna, Austria
Hartono, Budi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-33
boed@gadjahmada.edu
Mechanical and Industrial Engineering, Universitas Gadjah
Mada, Indonesia
Has, Adela. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-19
adela.kapetanovic@gmail.com
Faculty of Economics in Osijek, University of Osijek, Osijek,
Croatia
Hasannasab, Maryam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-44
maryam.hasannasab@khu.ac.ir
Department of Mathematics and Computer Science,
Kharazmi University, Tehran, Iran, Islamic Republic Of
Hasgul, Servet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-13
shasgul@ogu.edu.tr
Industrial Engineering, Eskisehir Osmangazi University, Eskisehir, Turkey
Hashimoto, Hideki . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-21, TE-40
hasimoto@nagoya-u.jp
Nagoya University, Nagoya, Japan
Hasle, Geir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-25
geir.hasle@sintef.no
Applied Mathematics, Sintef Ict, Oslo, Norway
Hasuike, Takashi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-26
thasuike@ist.osaka-u.ac.jp
Graduate School of Information Science and Technology,
Osaka University, Suita, Osaka, Japan
He, Qie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-02, MA-45
qhe@umn.edu
Industrial and Systems Engineering, University of Minnesota,
Minneapolis, MN, United States
He, Xuedong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-29
xh2140@columbia.edu
Industrial Engineering and Operations Research, Columbia
University, New York, United States
Hearne, John . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-36
john.hearne@rmit.edu.au
Mathematical and Geospatial Sciences, RMIT University,
Melbourne, Victoria, Australia
Heathcote, Andrew . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-15
Andrew.Heathcote@newcastle.edu.au
University of Newcastle, Callaghan, NSW, Australia
Heching, Aliza R. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-13
ahechi@us.ibm.com
IBM TJ Watson Research Center, NewYork, NY, United
States
Hedman, Kory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-07
Kory.Hedman@asu.edu
Electrical Engineering, Arizona State University, Tempe, AZ,
United States
Heese, Sebastian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-22
sebastian.heese@ebs.edu
EBS University, Germany
Heffels, Tobias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-08
tobias.heffels@kit.edu
KIT-IIP, Germany
Heide-Jørgensen, Ditte . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-20
dihj@math.ku.dk
Department of Mathematical Sciences, University of Copenhagen, København NV, Denmark
Haubenberger-Hahn, Rita . . . . . . . . . . . . . . . . . . . . . . . . . . ME-33
Rita.Haubenberger-Hahn@era-gmbh.at
ERA Elektro Recycling Austria GmbH, Vienna, Austria
Heidgen, Jan-Gerrit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-43
heidgen@vwl.uni-freiburg.de
BWL Seminar I, Finanzwesen, Rechnungswesen und Controlling, Albert-Luwdwigs-Universität Freiburg, Freiburg,
Germany
Hauer, Walter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-33
walter.hauer@tbhauer.at
Technisches Büro HAUER Umweltwirtschaft GmbH, Korneuburg, Austria
Hein, Fanny . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-41
Hein@europa-uni.de
Chair for Supply Chain Management, European University
Viadrina Frankfurt(Oder), Frankfurt(Oder), Germany
Haviv, Moshe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-22
haviv@mscc.huji.ac.il
Department of Statistics, Hebrew University of Jerusalem,
Jerusalem, Israel
Hein, Nelson . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-25, HB-34
hein@furb.br
Mathematics, FURB, Blumenau, Santa Catarina, Brazil
Hayek, Naila . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-25
naila.hayek@u-paris2.fr
Economics, University Paris 2, Paris, France
Hämäläinen, Raimo P. . . . . . . . . . . . . . . . . . . . . . . MA-23, MD-23
raimo.hamalainen@aalto.fi
Systems Analysis Laboratory, Aalto University ,School fo
Science, AALTO, Finland
Hayya, Jack . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-06
jch@psu.edu
Supply Chains & Information Systems, Penn State University, University Park, PA, United States
338
Heipcke, Susanne . . . . . . . . . . . . . . . . . . . . MB-21, HA-23, TB-28
susanneheipcke@fico.com
Xpress Optimization, FICO, Marseille, France
Hekimoğlu, Haluk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-04
haluk_heki@hotmail.com
Business Administration, Social Sciences, Istanbul, Turkey
Helber, Stefan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-06
stefan.helber@prod.uni-hannover.de
Inst. f. Produktionswirtschaft, Leibniz Universität Hannover,
Hannover, Germany
Helgesen, Per Ivar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-07
IFORS 2014 - Barcelona
per.ivar.helgesen@enova.no
Industrial Economics and Technology Management, NTNU,
Trondheim, Norway
Hellemo, Lars . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-45
lars.hellemo@sintef.no
SINTEF, Trondheim, Norway
Helmberg, Christoph . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-26
helmberg@mathematik.tu-chemnitz.de
Fakultät für Mathematik, Technische Universität Chemnitz,
Chemnitz, Germany
Hemmati, Ahmad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-05
ahmad.hemmati@iot.ntnu.no
Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology,
Trondheim, Norway
Hemmecke, Raymond . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-28
hemmecke@tum.de
TU München, Germany
Hemmelmayr, Vera . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-33
vera.hemmelmayr@wu.ac.at
Vienna University of Economics and Business (WU), Vienna,
Austria
Hennum, Alf Christian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-33
achennum@gmail.com
FFI, KJELLER, Norway
Henrion, Didier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-16
henrion@laas.fr
LAAS-CNRS, University of Toulouse, Toulouse, France
Henriques, Carla . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-44
coliv@inescc.pt
INESC Coimbra and ISCAC Coimbra, Coimbra, Portugal
Herczeg, Gábor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-08
gahe@man.dtu.dk
Department of Management Engineering, Technical University of Denmark, Lyngby, Denmark
Heredia, F.-Javier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-10
f.javier.heredia@upc.edu
Statistics and Operations Research, Universitat Politècnica
de Catalunya - BarcelonaTech, Barcelona, Catalunya, Spain
Hernandez, German Jairo . . . . . . . . . . . . . . . . . . . . . . . . . . HD-07
gjhernandezp@gmail.com
Engineering, Universidad Nacional de Colombia, Colombia
Hernandez, German . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-07
jhonpetrucci2000@yahoo.es
Universidad Nacional de Colombia, Colombia
Herrera, Milton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-04
milton-herrera@upc.edu.co
Universidad Piloto de Colombia, Colombia
Herrigel-Wiedersheim, Sabrina . . . . . . . . . . . . . . . . . . . . . . TB-01
sabrina.herrigel@ivt.baug.ethz.ch
Institute for Transport Planning and Systems, ETH Zurich,
Zurich, Switzerland
Herrmann, Frank . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-35
Frank.Herrmann@HS-Regensburg.de
Innovation and Competence Centre for Production Logistics
and Factory Planning, Technical University of Applied Sciences Regensburg, Regensburg, Germany
AUTHOR INDEX
Herrmann, Jeffrey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-42
jwh2@isr.umd.edu
Department of Mechanical Engineering, University of Maryland, College Park, MD, United States
Herrmann, Ricardo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-13
ricardo.herrmann@br.ibm.com
IBM Research, Brazil
Herrmannsdoerfer, Maja . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-44
m.herrmannsdoerfer@4flow.de
4flow AG, Germany
Herskovits, Jose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-38
jose@optimize.ufrj.br
COPPE/UFRJ- Federal University of Rio de Janeiro, Brazil
Hertz, Alain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-06
alain.hertz@gerad.ca
Ecole Polytechnique, Montreal, Canada
Hesamzadeh, Mohammad Reza . . . . . . . . . . . . . . . . . . . . . TB-07
mrhesamzadeh@ee.kth.se
Electric Power Systems, KTH Royal Institute of Technology,
Stockholm, Sweden
Heshmati, Sam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-11
sam.heshmati@gmail.com
INESC TEC, Faculty of Engineering, University of Porto,
Portugal
Hesse, Martina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-08
Martina.Hesse@wiwi.uni-goettingen.de
Chair of Production and Lgistics, Georg-August-Universität
Göttingen, Göttingen, Germany
Heyns, Andries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-11
andriesheyns@gmail.com
Department of Logistics, Stellenbosch University, Matieland,
Western Cape, South Africa
Hezarkhani, Behzad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-22
b.hezarkhani@tue.nl
Department of Industrial Engineering, Eindhoven University
of Technology, Eindhoven, Netherlands
Hezer, Seda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-13
sedahezer@selcuk.edu.tr
Industrial Engineering, Selcuk University, Konya, Turkey
Hibiki, Norio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-30
hibiki@ae.keio.ac.jp
Administration Engineering, Keio University, Yokohama,
Japan
Hicks, Illya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-39
ivhicks@rice.edu
Computational and Applied Mathematics, Rice University,
Houston, TX, United States
Hidalgo, Ieda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-18
iedahidalgo@gmail.com
Energy, Unicamp - University of Campinas, Campinas, São
Paulo, Brazil
Hiermann, Gerhard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-42
Gerhard.Hiermann.fl@ait.ac.at
Mobility Department - Dynamic Transportation Systems,
AIT Austrian Institute of Technology, Vienna, Vienna, Austria
339
AUTHOR INDEX
IFORS 2014 - Barcelona
Hildmann, Marcus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-34
hildmann@eeh.ee.ethz.ch
Information Technology and Electrical Engineering, ETH
Zurich, Zürich, Switzerland
Hillege, Hans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-39
j.l.hillege@tcc.umcg.nl
Department of Cardiology/Epidemiology, University Medical Centre Groningen, Groningen, Netherlands
Hiller, Benjamin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-28
hiller@zib.de
Optimization, Zuse Institute Berlin, Berlin, Germany
Hindle, Giles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-38
giles.hindle@hull.ac.uk
Mangement Systems, Hull University Business School, Hull,
United Kingdom
Hinojosa, Miguel A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-37
mahinram@upo.es
Universidad Pablo de Olavide, Seville, Spain
Hinojosa, Yolanda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-03
yhinojos@us.es
Economía Aplicada I, Universidad de Sevilla, Sevilla, Spain
Hippmann, Patrick . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-23
patrick.hippmann@univie.ac.at
Department of Business, Economics, and Statistics, University of Vienna, Vienna, Austria
Hirano, Shinya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-30
s.hirano.0331@gmail.com
Okasan Asset Management, Chuo-ku, Japan
Hirotsu, Nobuyoshi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-35
nhirotsu@hotmail.com
Juntendo University, Inzai, Chiba, Japan
Hirsch, Patrick . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-39
patrick.hirsch@boku.ac.at
Institute of Production and Logistics, University of Natural
Resources and Life Sciences, Vienna, Wien, Austria
Hjaila, Kefah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-13
kefah.hjaila@upc.edu
Departamento de Ingeniería Quimíca, Universitat Politècnica
de Catalunya(UPC), Barcelona, Barcelona, Spain
Ho, Ying-Chin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-04
ho@cc.ncu.edu.tw
Institute of Industrial Management, National Central University, Chung-Li, Taoyuan, Taiwan
Hoşgör, Tuğçe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-11
tugcehosgor@gmail.com
Industrial Engineering Department, İstanbul Kültür University, İstanbul, Turkey
Hobbesland, Kirsti . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-05
Kirsti.hobbesland@iot.ntnu.no
Norwegian University of Science and Technology, Trondheim, Norway
Hoberg, Kai . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-19
Kai.Hoberg@the-klu.org
Supply Chain and Operations Strategy, Kühne Logistics University, Hamburg, Germany
Hobson, Philip A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-38
p.hobson@qut.edu.au
340
Centre for Tropical Crops and Biocommodities, Queensland
University of Technology, Brisbane, Australia
Hochbaum, Dorit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-25
hochbaum@ieor.berkeley.edu
IE&OR department, UC Berkeley, Berkeley, CA, United
States
Hocke, Sina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-44
sina.hocke@tuhh.de
Institute of Management Control and Accounting, Hamburg
University of Technology, Germany
Hoechstoetter, Markus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-38
markus.hoechstoetter@kit.edu
Statistics, Kit - Econ, Karlsruhe, Baden-Wuerttemberg, Germany
Hoffman, Karla . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-21, TA-44
khoffman@gmu.edu
Department of Systems Engineering and Operations Research, George Mason University, Fairfax, Virginia, United
States
Hohzaki, Ryusuke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-33
hozaki@cc.nda.ac.jp
Department of Computer Science, National Defense
Academy, Yokosuka, Kanagawa, Japan
Holeček, Pavel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-26, TD-26
pavel.holecek@upol.cz
Department of Mathematical Analysis and Applications of
Mathematics, Palacky University in Olomouc, Olomouc,
Czech Republic
Holguin-Veras, Jose . . . . . . . . . . . . . . . . . . MB-06, TB-32, HB-44
jhv@rpi.edu
Rensselaer Polytechnic Institute, United States
Holland, Christopher . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-42
chris.holland@mbs.ac.uk
Strategy and Information Systems, Manchester Business
School, Manchester, United Kingdom
Holmberg, Kaj . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-02
kaj.holmberg@liu.se
Optimization, Mathematics, Linkoping University, Sweden
Homberger, Jörg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-12
joerg.homberger@hft-stuttgart.de
Stuttgart, Germany
Hong, I-Hsuan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-08
ihong@ntu.edu.tw
Industrial Engineering, National Taiwan University, Taipei,
Taiwan
Hong, JaeYeol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-34
hongpremigo@gmail.com
Korea university, Korea, Republic Of
Hong, QIU . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-10
qh1365@163.com
School of Business Administration, Southwestern University
of Finance and Economics, Chengdu, China
Hong, Qiu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-02
qh1365@163.com
The school of Statistics, Southwestern University of Finance
and Economics, Chengdu, Sichuan, China
Hong, Soon-Heum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-01
IFORS 2014 - Barcelona
AUTHOR INDEX
shong@krri.re.kr
Korea Railway Research Institute, Gyeonggi-do, Korea, Republic Of
ahosseini@sabanciuniv.edu
Industrial Engineering Department, Sabanci University, Istanbul, Tuzla, Turkey
Hong, Xing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-31
xhong@gwmail.gwu.edu
Engineering Management & Systems Engineering, The
George Washington University, United States
Hosseinzadeh Lotfi, Farhad . . . . . . . . . . . . . . . . . . HD-10, TE-14
Farhad@hosseinzadeh.ir
Islamic Azad University, Science and research branch,
Tehran, Iran, Islamic Republic Of
Hong, Young-Chae . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-06
hongyc@umich.edu
University of Michigan, Ann Arbor, United States
Hotta, Keisuke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-09
khotta@shonan.bunkyo.ac.jp
Faculty of Information and Communication, Bunkyo University, Chigasaki, Kanagawa, Japan
Honma, Yudai . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-03
yudai@iis.u-tokyo.ac.jp
Institute of Industrial Science, The University of Tokyo,
Meguro-ku, Tokyo, Japan
Hoogendoorn, Serge . . . . . . . . . . . . . . . . . . . . . . . . . HB-04, TD-04
s.p.hoogendoorn@tudelft.nl
Transport & Planning, Delft University of Technology, Delft,
Netherlands
Hougaard, Jens Leth . . . . . . . . . . . . . . . . . . . . . . . . . HA-10, TE-14
jlh@foi.ku.dk
Institute of Food and Resource Economics, University of
Copenhagen, Copenhagen, Denmark
Houmb, Siv Hilde . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-31
sivhoumb@securenok.com
Secure-NOK AS, Houston, TX, Norway
Hoogeveen, Han . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-11
j.a.hoogeveen@uu.nl
Department of Information and Computer Science, Utrecht
University, Utrecht, Netherlands
Howard, Anna . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-44
howarda2@lsbu.ac.uk
Faculty of Business, London South Bank University, United
Kingdom
Hooker, John N. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-13
john@hooker.tepper.cmu.edu
Tepper School of Business, Carnegie Mellon University,
Pittsburgh, PA, United States
Hoyos, Carlos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-40
carlos.hoyos@colmayor.edu.co
Facultad de Arquitectura e Ingenieria, Institucion Universitaria Colegio Mayor de Antioquia, Medellin, Antioquia,
Colombia
Hooshmand Khaligh, Farnaz . . . . . . . . . . . . . . . . . . . . . . . . FB-36
farnaz.hooshmand.khaligh@gmail.com
Amirkabir University of Technology, Tehran, Iran, Islamic
Republic Of
Hordijk, Raymundo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-33
rr.hordijk@nlda.nl
Faculty of Military Sciences, Netherlands Defence Academy,
Den Helder, Netherlands
Horiyama, Takashi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-09
horiyama@al.ics.saitama-u.ac.jp
Information Technology Center, Saitama University, Saitama,
Saitama, Japan
Hörmann, Wolfgang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-34
hormannw@boun.edu.tr
Industrial Engineering, Bogazici University, Turkey
Horvat, Ana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-26
horvat@fon.bg.ac.rs
Faculty of Organizational Sciences, Serbia
Horvát, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-23
peter.horvat@savba.sk
Economic Modelling and Analyses, Institute of Economic
Research Slovak Academy of Sciences, Bratislava, Slovakia
Hosoya, Yuhki . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-25
hosoya@kanto-gakuin.ac.jp
Graduate school of economics, Kanto-Gakuin University,
Yokohama, Kanagawa, Japan
Hosseinalifam, Morad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-15
morad.hosseinalifam@polymtl.ca
Departement de mathématiques et génie industriel, École
Polytechnique, Montréal, QC, Canada
Hosseini, Seyed Ahmad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-43
Hrusovsky, Martin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-33
martin.hrusovsky@wu.ac.at
Department of Information Systems and Operations, WU Vienna University of Economics and Business, Vienna, Austria
Hsu, Chao-Che . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-37
hsuchao@mail.tku.edu.tw
Department of Transportation Management, Tamkang University, New Taipei city, Taiwan
Hsu, Yu-Hsuan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-02
lesly66@gmail.com
Graduate Institute of Logistics Management, National Dong
Hwa University, Hualien, Taiwan, Taiwan
Hsueh, Che-Fu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-44
cfhsueh@uch.edu.tw
Marketing and Distribution Management, Chien Hsin University of Science and Technology, Taoyuan, Taiwan
HU, Rong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-21
hoorong@nuaa.edu.cn
Department of Air Transportation, Nanjing University of
Aeronautics and Astronautics, Nanjing, Jiangsu, China
Hu, Xudong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-06
xdhu@amss.ac.cn
Academy of Mathematics and Systems Science, Chinese
Academy of Sciences, Beijing, China
Hu, Yannan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-21
yannanhu@nagoya-u.jp
Nagoya University, Nagoya, Japan
Hu, Yuhai . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-20
yuh212@lehigh.edu
Industrial & Systems Engineering, Lehigh University, Bethlehem, PA, United States
341
AUTHOR INDEX
IFORS 2014 - Barcelona
Huang, Cheng-kui . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-34
bmahck@ccu.edu.tw
Department of Business Administration, National Chung
Cheng University, Min-Hsiung, Chia-Yi, Taiwan
Huang, Jincai . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-18, ME-44
zhiyongma88@sohu.com
National University of Defense Technology, Science and
Technology on Information Systems Engineering Laboratory, changsha, China
kate.hughes@hughes-scm.com
MGSM, Macquarie Graduate School of Management, Kensington, NSW, Australia
Huguet, Marie-José . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-22
huguet@laas.fr
LAAS-CNRS, Toulouse, France
Hui, Yer Van . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-22, HD-35
msyervan@cityu.edu.hk
City University of Hong Kong, Hong Kong, Hong Kong
Huang, Kwei-Long . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-39
craighuang@ntu.edu.tw
Institute of Industrial Engineering, National Taiwan University, Taiwan
Huisman, Bob . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-01
b.huisman@tudelft.nl
Algorithmics Group, Delft University of Technology, Delft,
Netherlands
Huang, Li-Hao . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-19
j07110324@gmail.com
National Chin-Yi University of Technology, Taichung, Taiwan
Huisman, Dennis . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-01, TA-01
huisman@ese.eur.nl
Econometric Institute, Erasmus University, Rotterdam,
Netherlands
Huang, Tingliang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-22
t.huang@ucl.ac.uk
Department of Management Science and Innovation, University College London, London, Select State, United Kingdom
Huka, Maria Anna . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-36
maria.huka@boku.ac.at
Department of Economics and Social Science, Institute of
Production and Logistics, University of Natural Resources
and Life Sciences, Vienna, Vienna, Austria
Huang, Wei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-28
huang@ma.tum.de
Mathematics, Technische Universität München, Garching b.
Munich, Bavaria, Germany
Huang, Xiaoxia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-21
hxiaoxia@manage.ustb.edu.cn
University of Science and Technology Beijing, China
Huang, Yi-Chuan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-27
jeanhuang77@yahoo.com.tw
Graduate School of Operation and Management, Kao Yuan
University, Taiwan
Humpola, Jesco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-28
humpola@zib.de
Optimization, Zuse Institute Berlin, Berlin, Berlin, Germany
Hung, Meng-Chan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-37
vivi_mon100@yahoo.com.tw
Department of Industrial Engineering and Management, National Chiao Tung University, Hsinchu, Taiwan
Hungerländer, Philipp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-35
philipp.hungerlaender@uni-klu.ac.at
Mathematics, University of Klagenfurt, Austria
Huang, Yuan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-40
yuan.huang@soton.ac.uk
University of Southampton, Southampton, United Kingdom
Huppmann, Daniel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-07
dhuppmann@diw.de
DIW Berlin, Berlin, Germany
Huangfu, Qi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-21
qihuangfu@fico.com
FICO, Birmingham, United Kingdom
Hurink, Johann . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-06
j.l.hurink@utwente.nl
Department of Applied Mathematics, University of Twente,
Enschede, Netherlands
Huber, Sandra . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-28
sandra-huber@hsu-hh.de
Logistics Management Department, Helmut-SchmidtUniversity, University of the Federal Armed Forces, Hamburg, Germany
Hubin, Aliaksandr . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-05
aliaksandr.hubin@stud.himolde.no
Faculty of Economics, Informatics and Social Sciences,
Molde University College-Specialized University in Logistics, Molde, Norway, Norway
Hübner, Alexander . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-19
alexander.huebner@ku-eichstaett.de
Operations Management, Catholic University EichstaettIngolstadt, Ingolstadt, Germany
Huddleston, Jeanne . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-06
Huddleston.Jeanne@mayo.edu
Center for Science of Healthcare Delivery, Mayo Clinic,
Rochester, MN, United States
Hughes, Kate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-31
342
Hurtado, Rafael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-27
rghurtadoh@unal.edu.co
Physics, Universidad Nacional de Colombia, Bogota, Cundinamarca, Colombia
Hutzinger, Clemens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-24
clemens.hutzinger@univie.ac.at
Chair of Organization and Planning, Vienna University, Vienna, Austria
Hvattum, Lars Magnus . . . . . . . . . . . . . . . HA-05, TA-05, TD-40
lars.m.hvattum@iot.ntnu.no
Dept of Industrial Economics and Technology Management,
Norwegian University of Science and Technology, Trondheim, Norway
Hwang, Ill Hoe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-42
majesty4u@kaist.ac.kr
KAIST, Daejeon, Korea, Republic Of
Hwang, Wook Yeon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-42
wookyeonhwang@gmail.com
IFORS 2014 - Barcelona
Qatar University, Qatar
Hwang, Woonam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-22
whwang@london.edu
London Business School, London, United Kingdom
Hyndman, Rob . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-18
Rob.Hyndman@monash.edu
Econometrics & Business Statistics, Monash University,
Clayton, Victoria, Australia
Iakovou, Eleftherios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-35
eiakovou@auth.gr
Mechanical Engineering, Aristotle University of Thessaloniki, Thessaloniki, Greece
Iancu, Dan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-18
daniancu@stanford.edu
Stanford Graduate School of Business, Stanford, United
States
Iassinovskaia, Galina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-19
galina.iassinovskaia@uclouvain-mons.be
UCL-Mons, Mons, Belgium
Ide, Jonas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-18
j.ide@math.uni-goettingen.de
Fakultät für Mathematik, Georg-August-Universität Göttingen, Germany
Idris, Husni . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-03
husni.idris@engilitycorp.com
Engility Corporation, Billerica, MA, United States
Ignacio Junior, Edmundo . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-14
eijunior@gmail.com
State University of Campinas, LIMEIRA, Sao Paulo, Brazil
Ignatius, Joshua . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-43
joshua_ignatius@hotmail.com
School of Mathematical Sciences, Universiti Sains Malaysia,
Minden, Penang, Malaysia
Igualada, Lucia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-10, ME-10
ligualada@irec.cat
Energy Economics Group, Electrical Engineering Research
Area, Intitut de Recerca en Energia de Catalunya, Sant Adria
de Besos, Spain
Iida, Yoichi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-37
iida@rs.suwa.tus.ac.jp
Department of Business Administration and Information,
Tokyo University of Science, Suwa, Chino, Nagano, Japan
Ikegami, Atsuko . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-09, TB-39
atsuko@st.seikei.ac.jp
Faculty of Science and Technology, Seikei University, Tokyo,
Japan
Ilijas, Tomi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-42
tomi.ilijas@arctur.si
Arctur d.o.o., Nova Gorica, Slovenia
Imahori, Shinji . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-21, HD-21
imahori@na.cse.nagoya-u.ac.jp
Department of Computational Science and Engineering,
Nagoya University, Nagoya, Japan
Imai, Haruo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-08
imai@kier.kyoto-u.ac.jp
KIER, Kyoto University, Kyoto, Japan
AUTHOR INDEX
Immers, Ben . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-25
ben.immers@gmail.com
Delft University of Technology, Delft, Zuid Holland, Netherlands
Imoh, Kingsley . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-44
kngslyikpe@yahoo.com
Economics, Akwa Ibom State university, Uyo, Akwa Ibom,
Nigeria
Inan, Umut H. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-27
umutinan@halic.edu.tr
Industrial Engineering, Haliç University, Turkey
Inceoglu, Gonca . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-14
inceoglugonca@gmail.com
Education Faculty - Department of Primary Education - Program in Primary School Mathematic Teaching, Anadolu University, Eskisehir, Turkey
Inceoglu, Mehmet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-45
inceoglum@gmail.com
Architecture, Anadolu University, Eskisehir, Turkey
Inghels, Dirk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-42
dirk.inghels@uantwerpen.be
ITMMA, Hasselt, Belgium
Ingolfsson, Armann . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-19
Armann.Ingolfsson@UAlberta.Ca
School of Business, University of Alberta, Edmonton, Alberta, Canada
Inkaya, Tulin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-16
tinkaya@uludag.edu.tr
Industrial Engineering Department, Uludag University,
Turkey
Inkoom, Justice Nana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-36
j.inkoom@uni-bonn.de
Ecology and Natural Resource Management, Centre for Development Studies, University of Bonn, Germany, Bonn,
North Rhine-Westphalia, Germany
Innorta, Mario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-09
mario.innorta@fastwebnet.it
University of Bergamo, Bergamo, Italy
Inui, Hitoshi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-30
h.inui.08@gmail.com
Shibaura Institute Of Technology, Tokyo, Japan
Inzunza, Andres . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-10
arinzunza@gmail.com
Pontificia Universidad Catolica de Chile, Santiago, Chile
Iofina, Galina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-16
giofina@mail.ru
Moscow Institute of Physics and Technology, Russian Federation
Ionescu, Lucian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-03
Lucian.Ionescu@fu-berlin.de
Department of Information Systems, Freie Universität Berlin,
Berlin, Germany
Iori, Manuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-21, FA-25
manuel.iori@unimore.it
DISMI, University of Modena and Reggio Emilia, Reggio
Emilia, Italy
Ioslovich, Ilya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-04, MB-25
343
AUTHOR INDEX
IFORS 2014 - Barcelona
agrilya@tx.technion.ac.il
The Technion - Israel Instiute of Technology, Haifa, Israel
Ipsilandis, Pandelis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-26
ipsil@teilar.gr
Project Management, Technological Education Institute of
Larissa, Larissa, Greece
Iranzo, Jose A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-11
joseani@unizar.es
Metodos Estadisticos, Universidad de Zaragoza, Zaragoza,
Spain
Irawan, Chandra . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-45
ca259@kent.ac.uk
Kent Business School, University of Kent, Canterbury, –
Please Select (only U.S. / Can / Aus), United Kingdom
Iris, Cagatay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-05
cagai@transport.dtu.dk
Technical University of Denmark, Lyngby, Denmark
Irzhavski, Pavel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-12
irzhavski@bsu.by
Department of Discrete Mathematics and Algorithmics, Faculty of Applied Mathematics and Computer Science, Belarusian State University, Minsk, Belarus
Isebor, Obiajulu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-28
oisebor@alumni.stanford.edu
BP, Houston, TX, United States
Ishaq, Shamaila . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-42
dinaishaq@yahoo.com
Warwick Business School, University of Warwick, Coventry,
United Kingdom
Ishizaka, Alessio . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-15, MB-37
alessio.ishizaka@port.ac.uk
Portsmouth Business School, University of Portsmouth,
Portsmouth, Hampshire, United Kingdom
Issaadi, Hayat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-39
issaadihayat@yahoo.fr
Mathematics, USTHB University, Alger, Alger, Algeria
Iusem, Alfredo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-26
iusp@impa.br
IMPA, Rio de Janeiro, RJ, Brazil
Ivanisevic, Ivo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-25
ivo.ivanisevic@gmail.com
Trovicor d.o.o., Trovicor, Split, Croatia
Ivkin, Nikita . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-16
ivkinnikita@gmail.com
Faculty of Management and Applied Mathematics, Moscow
Institute of Physics and Technology (State University), Dolgoprudny, Moscow Region, Russian Federation
Ivorra, Benjamin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-29
ivorra@mat.ucm.es
Matematica Aplicada, Universidad Complutense de Madrid,
Madrid, Spain, Spain
İçmen, Banu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-21
bicmen@anadolu.edu.tr
Industrial Engineering, Anadolu University, Turkey
Iyengar, Garud . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-20, HD-20
garud@ieor.columbia.edu
Industrial Eng. and Operations Research Dept., Columbia
University, New York, NY, United States
İlhan, Doğan Aybars . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-11
aybrs90@windowslive.com
Industrial Engineering Department, Istanbul Kültür University, Istanbul, Turkey
J Muñoz, Jose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-14
j.munoz@upc.edu
Applied Mathematics III, Universitat Politecnica de
Catalunya, Barcelona, Barcelona, Spain
J. W. James, Ross . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-19
ross.james@canterbury.ac.nz
Department of Management, University of Canterbury,
Christchurch, New Zealand
Jabarnejad, Masood . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-09
masood@auburn.edu
Industrial and Systems Engineering, Auburn University,
Auburn, Alabama, United States
Jablonsky, Josef . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-30
jablon@vse.cz
Dept. of Econometrics, University of Economics Prague,
Prague 3, Czech Republic
Jachnik, Arkadiusz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-24
arkadiusz.jachnik@cs.put.poznan.pl
Institute of Computing Science, Poznan University of Technology, Poznan, Poland
Jacquillat, Alexandre . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-35
alexjacq@mit.edu
Engineering Systems Division, MIT, Cambridge, MA, United
States
Jadbabaie, Ali . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-06
jadbabai@seas.upenn.edu
Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA, United States
Jafari, Nahid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-43
nahid.jafariasbagh@rmit.edu.au
Mathematical and Geospatial Sciences, RMIT University,
Melbourne, Victoria, Australia
Jakowczyk, Marta . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-08
marta.jakowczyk@gmail.com
School of Mechanical, Aerospace and Civil Engineering,
University of Manchester, Manchester, United Kingdom
Jalil, Muhammad Naiman . . . . . . . . . . . . . . . . . . . ME-04, TD-08
muhammad.jalil@lums.edu.pk
Lahore University of Management Sciences, Pakistan
Iwamoto, Seiichi . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-09, MD-09
iwamotodp@kyudai.jp
Economics, Kyushu University, Fukuoka, Japan
Jammernegg, Werner . . . . . . . . . . . . . . . . . . . . . . . MA-33, MB-33
werner.jammernegg@wu.ac.at
Department of Information Systems and Operations, WU Vienna University of Economics and Business, Wien, Austria
Iwasawa, Hiroki . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-21
h-iwasawa@na.cse.nagoya-u.ac.jp
Nagoya University, Nagoya, Japan
Jandova, Vera . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-26
vera.jandova01@upol.cz
Dept. of Mathematical Analysis and Applications of Mathe-
344
IFORS 2014 - Barcelona
matics, Palacky University in Olomouc, Faculty of Science,
Olomouc, Czech Republic
Janela, João . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-02
jjanela@iseg.utl.pt
CEMAPRE and ISEG/ULisboa, Lisboa, Portugal
Jang, Young . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-42
yjang@kaist.ac.kr
Industrial and Systems Engineering, KAIST, Daejeon, Korea,
Republic Of
Janova, Jitka . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-09
janova@mendelu.cz
Department of Statistics and Operation Analysis, Mendel
University of Agriculture and Forestry in Brno, Brno, Czech
Republic
Jans, Raf . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-41, MB-41
raf.jans@hec.ca
Department of Logistics and Operations Management, HEC
Montreal, Montreal, Quebec, Canada
Janssen, René . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-33
rhp.janssen@nlda.nl
Faculty of Military Sciences, Netherlands Defence Academy,
Den Helder, Netherlands
Jaoua, Mehdi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-06
mehdi.jaoau@polymtl.ca
Mathématiques et génie industriel, École Polytechnique de
Montréal, Montréal, Québec, Canada
Jaśkowski, Wojciech . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-28
wjaskowski@cs.put.poznan.pl
Institute of Computing Science, Poznan University of Technology, Poznan, Poland
Jaramillo, Patricia . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-23, FA-27
gpjarami@unal.edu.co
Medellin, Antioquia, Colombia
Jayaswal, Sachin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-03
sachin@iimahd.ernet.in
Production & Quantitative Methods, Indian Institute of Management Ahmedabad, Ahmedabad, Gujarat, India
Jedrzejowicz, Piotr . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-12
pj@am.gdynia.pl
Information Systems, Gdynia Maritime University, Gdynia,
Poland
Jena, Sanjay Dominik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-36
sanjay.jena@cirrelt.ca
CIRRELT, Université de Montréal, Canada
Jensen, Rune. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-05
rmj@itu.dk
IT-University of Copenhagen, Denmark
Jensson, Pall . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-19
pallj@ru.is
School of Science and Engineering, Reykjavik University,
Reykjavik, Iceland
Jeon, Jinwoo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-23
jlostuniverse@hanmail.net
Safety Research office, Koera Transportation Safety Authority, Ansan-si, Gyeonggi-do, Korea, Republic Of
Jeong, Hyo-Tae . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-42
htjeong@gwnu.ac.kr
AUTHOR INDEX
Advanced Metal and Materials Engineering, GangneungWonju National University, Gangneung, Gangwon, Korea,
Republic Of
Jeong, Myong K . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-42
mjeong@rci.rutgers.edu
Industrial & Systems Eng, Rutgers University, United States
Ji, Hyunwoong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-42
hyunwoong.ji@gmail.com
Seoul National University, Korea, Republic Of
Jiménez-Martín, Antonio . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-31
antonio.jimenez@upm.es
Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid (UPM), Boadilla del Monte, Madrid, Spain
Jiménez-Martínez, Marcos . . . . . . . . . . . . . . . . . . . . . . . . . . HB-36
mjimene1@uni-bonn.de
Center for Development Research (ZEF), Universität Bonn,
Bonn, Nordrhein-Westfalen, Germany
Jiménez-Parra, Beatriz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-08
bjimenez@unex.es
Organización de Empresas, Universidad de Extremadura,
Badajoz, Spain
Jimenez, Xavi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-17
xavi.jimenez@upc.edu
Universitat Politècnica de Catalunya, Barcelona, Spain
Jimenez-Cordero, M. Asuncion . . . . . . . . . . . . . . . . . . . . . . TE-21
asuncionjc@us.es
University of Seville, Seville, Spain
Jimenez-Lopez, Mariano . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-26
mariano.jimenez@ehu.es
Economía Aplicada I, University of the Basque Country, San
Sebastian, Spain
Jin, Qingwei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-17
qingweijin@zju.edu.cn
Management Science and Engineering, Zhejiang University,
Hangzhou, Zhejiang, China
Joannopoulos, Émilie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-36
emilie.joannopoulos@usherbrooke.ca
Université de Sherbrooke, Sherbrooke, Canada
Jochem, Patrick . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-07, MA-08
jochem@kit.edu
Chair of Energy Economics (IIP), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Johari, Ramesh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-06
ramesh.johari@gmail.com
Stanford University, Stanford, United States
Johnsen, Trond A. V. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-05
trond.johnsen@marintek.sintef.no
MARINTEK, SINTEF, Trondheim, Norway
Johnson, Franklin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-25
franklin.johnson@upla.cl
Computación E Informatica, Universidad de playa ancha,
Valparaiso, Chile
Joki, Kaisa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-26
kjjoki@utu.fi
Department of Mathematics and Statistics, University of
Turku, Finland
345
AUTHOR INDEX
IFORS 2014 - Barcelona
Joormann, Imke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-39
joormann@mathematik.tu-darmstadt.de
Research Group Optimization, Dept. of Mathematics, Technical University Darmstadt, Germany
Jorge, Pedro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-37
pedromrjuc2009@gmail.com
Apartado 3008, Department of Mathematics, Coimbra, Portugal
Jornada, Daniel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-18
danieljornada@gmail.com
Industrial Engineering, Texas A&M University, United States
Joswig, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-24
joswig@math.tu-berlin.de
Institut für Mathematik, TU Berlin, Berlin, Germany
Joudrier, Hugo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-28
hugo.joudrier@gmail.com
G-SCOP, Grenoble, France
Joueiai, Mahtab . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-04
m.joueiai@tudelft.nl
Traffic and transport, TU Delft, Delft, Netherlands
Jouini, Oualid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-10
oualid.jouini@ecp.fr
Laboratoire Genie Industriel, Ecole Centrale Paris, ChatenayMalabry, France
Jourdan, Laetitia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-40
laetitia.jourdan@lifl.fr
LIFL/INRIA/Université Lille 1, Villeneuve d Ascq, France
Jourquin, Bart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-06
bart.jourquin@uclouvain.be
Louvain School of Management, Université Catholique de
Louvain, Mons, Belgium
Jovanović, Mlad̄an . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-32
mladjan@rcub.bg.ac.rs
Laboratory for Multimedia Communications, Faculty of Organisational Sciences, University of Belgrade, Belgrade, Serbia
Joyce-Moniz, Martim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-31
martim.moniz@ulb.ac.be
Départment d’Informatique, Université Libre de Bruxelles,
Belgium
Jozefowiez, Nicolas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-02
nicolas.jozefowiez@laas.fr
LAAS-CNRS, Toulouse, France
Jozefowska, Joanna . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-12
jjozefowska@cs.put.poznan.pl
Institute of Computing Science, Poznañ University of Technology, Poznañ, Wielkopolska, Poland
Juan, Angel A. . . . . . . . . . . . . . . . . . . . . . . . . TA-41, TB-41, TE-41
ajuanp@gmail.com
Computer Science, Fundació per a la Universitat Oberta de
Catalunya, Barcelona, Spain
Juenger, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-11
mjuenger@informatik.uni-koeln.de
Institut fuer Informatik, Universitaet zu Koeln, Koeln, Germany
Juhas, Pavol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-11
pjuhas@bnl.gov
346
Brookhaven National Laboratory, Upton, New York, United
States
Jun, Chi-Hyuck . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-42
chjun@postech.ac.kr
Industrial & Management Engineering, POSTECH, Pohang,
Korea, Republic Of
Justus, Nicolas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-04
nicolasjustus@gmx.de
TU Darmstadt, Darmstadt, Germany
Jutz, Simon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-41
simon.jutz@uibk.ac.at
Information Systems, Production and Logistics Management,
University of Innsbruck, Innsbruck, Austria
Kabakulak, Banu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-31
banu.kabakulak@boun.edu.tr
Industrial Engineering Department, Bogazici University,
Turkey
Kabyl, Kamal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-12
k_kabyle2000@yahoo.fr
Laboratory of Modeling and Optimization of Systems
LAMOS, Technology Department, University of Bejaia, Algeria, Bejaia, Algeria
Kaczmarczyk, Waldemar . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-14
waldek@agh.edu.pl
Department of Operations Research & Information Technology, AGH University of Science & Technology, Krakow,
Poland
Kadzinski, Milosz . . . . . . . . . . . . . . . . . . . MA-24, MB-24, MD-24
milosz.kadzinski@cs.put.poznan.pl
Institute of Computing Science, Poznan University of Technology, Poznan, Poland
Kahraman, Cengiz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-33
kahramanc@itu.edu.tr
Industrial Engineering, Istanbul Technical University, Istanbul, Turkey
Kahya, Uğur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-14
ukahya26@gmail.com
Anadolu University, Turkey
Kajiji, Nina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-30
nina@nkd-group.com
Computer Science and Statistics, University of Rhode Island,
and The NKD Group, Inc., Kingston, RI, United States
Kakeneno, Joe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-27
joekakeneno@yahoo.co.uk
Management Systems, Tanzania Ports Authority, Dar es
Salaam, N/A, Tanzania, United Republic Of
Kalafatoglu, Yasemin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-03
ykalafatoglu@gmail.com
Industrial Engineering, Bogazici University, Istanbul, Turkey
Kalamara, Katerina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-03
k.kalamara@gmail.com
Edinburgh Airport, Edinburgh, United Kingdom
Kalcsics, Jörg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-02, HE-03
kalcsics@kit.edu
Institute of Operations Research, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Kalinowski, Thomas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-31
IFORS 2014 - Barcelona
thomas.kalinowski@newcastle.edu.au
University of Newcastle, Australia
Kaliszewski, Ignacy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-18
ignacy.kaliszewski@ibspan.waw.pl
Systems Research Institute, Warszawa, Poland
Kallabis, Thomas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-07
thomas.kallabis@uni-due.de
Chair for Management Science and Energy Economics, University Duisburg-Essen, Essen, Germany
AUTHOR INDEX
Germany
Kano, Minoru . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-35
kano@sakura.juntendo.ac.jp
Juntendo University, Japan
Kao, Shih-Chou . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-27
t80132@cc.kyu.edu.tw
Graduate School of Operation and Management, Kao Yuan
University, Kaohsiung city, Taiwan
Kallio, Markku . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-14
markku.kallio@aalto.fi
Aalto University School of Business, Aalto, Finland
Kaparis, Konstantinos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-39
k.kaparis@lancs.ac.uk
Managemenst Science, Lancaster University, United Kingdom
Kaluzny, Bohdan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-33
Bohdan.Kaluzny@drdc-rddc.gc.ca
Defence Research and Development Canada, Canada
Kapočien, Silvija . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-45
silvija@sportorumai.lt
Kaunas University of Technology, Kaunas, Lithuania
Kalvø, Øyvind Iversen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-07
oyvindkalvo@gmail.com
NTNU, Trondheim, Norway
Kappmeier, Jan-Philipp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-11
jan-philipp.kappmeier@tu-dortmund.de
Combinatorial Optimization & Graph Algorithms, Technische Universität Berlin, Germany
Kamisli Ozturk, Zehra . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-18
zkamisli@anadolu.edu.tr
Industrial Engineering Department, Anadolu University, Eskisehir, Turkey
Kammerdiner, Alla . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-33
alla@nmsu.edu
Industrial Engineering, New Mexico State University, Las
Cruces, New Mexico, United States
Kamvysi, Konstantina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-23
nakam@uom.gr
Business Excellence Laboratory, Department of Business Administration, University of Macedonia, Thessaloniki, Greece
Kandakoglu, Ahmet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-33
akandakoglu@hvkk.tsk.tr
Scientific Decision Support Department, Turkish Air Force
Command, Ankara, Turkey
Kanellopoulos, Argyris . . . . . . . . . . . . . . . . . . . . . . HB-08, MB-18
argyris.kanellopoulos@gmail.com
Operations Research and Logistics, Wageningen University,
Wageningen, Gelderland, Netherlands
Kang, Chao-Chung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-14
cckang@pu.edu.tw
Department of Business Administration and Graduate Institute of Management, Providence University, Shalu, Taichung,
Taiwan
Kang, He-Yau . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-19, MD-37
kanghy@ncut.edu.tw
Department of Industrial Engineering and Management, National Chin-Yi University of Technology, Taichung, Taiwan
Kapucugil-Ikiz, Aysun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-27
aysun.kapucugil@deu.edu.tr
Business Administration, Dokuz Eylul University, Izmir,
Turkey
Kara, Yakup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-13
ykara@selcuk.edu.tr
Industrial Engineering, Selcuk University, Konya, Turkey
Karabak, Fahriye . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-04
fahriye.karabak@ozu.edu.tr
Industrial Engineering, Ozyegin University, Istanbul, Turkey
Karadayı, Saliha . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-22
karadayis@itu.edu.tr
Industrial Engineering, İstanbul Technical University, İstanbul, Turkey
Karaer, Ozgen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-37
okaraer@metu.edu.tr
Industrial Engineering, Middle East Technical University,
Ankara, Turkey
Karagiannis, Giannis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-10
karagian@uom.gr
Economics, University of Macedonia, Thessaloniki, Greece
Karahasanovic, Amela . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-03
Amela.Karahasanovic@sintef.no
Sintef Ict, Oslo, Norway
Karalashvili, Liana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-09
liana.qaralashvili@yahoo.com
Mathematics, University of Georgia, Tbilisi, Georgia
Kangas, Annika . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-36
annika.kangas@helsinki.fi
Department of Forest Resources Management, University of
Helsinki, Helsinki, Finland
Karalkova, Anastasiya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-05
anastasiya.karalkova@himolde.no
Molde University College- Spescialized University in Logistics, Norway
Kanioura, Athina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-23
athina.kanioura@accenture.com
Accenture, Athens, Greece
Karaoğlu, Onur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-12
okaraoglu@yahoo.com
Mathematics, Selçuk University, Konya, Turkey
Kannegiesser, Matthias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-33
mkannegiesser@yahoo.com
Production Management, TU Berlin, Berlin, Deutschland,
Karapetyan, Daniel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-33
daniel.karapetyan@gmail.com
Computer Science, University of Nottingham, Nottingham,
347
AUTHOR INDEX
IFORS 2014 - Barcelona
United Kingdom
Karathanasopoulos, Andreas . . . . . . . . . . . . . . . . . . . . . . . MD-26
andreas.kara@hotmail.com
University of East London, London, United Kingdom
Karimi, Sahar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-42
saharkarimi@hotmail.com
Edge Hill University, Ormskirk, Lancashire, – Please Select
(only U.S. / Can / Aus), United Kingdom
Karlsson, Thorlakur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-19
THORLAKUR@ru.is
School of Business, Reykjavik University, Reykjavik, Iceland
Karmitsa, Napsu . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-26, TE-26
napsu@karmitsa.fi
Department of Mathematics and Statistics, University of
Turku, Turku, Finland
Karrer, Arno . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-44
arno.karrer@aau.at
Controlling and Strategic Management, University of Klagenfurt, Klagenfurt, Austria
Karsten, Christian Vad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-05
chrkr@dtu.dk
DTU Management Engineering, The Technical University of
Denmark, Denmark
Karsu, Ozlem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-24
ozlemkarsu@yahoo.co.uk
Management, London School of Economics, LONDON,
United Kingdom
Kartak, Vadim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-21
kvmail@mail.ru
Bashkir State Pedagogical University M. Akmullah „ Ufa,
Russian Federation
Kasaei Roodsari, Maziar . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-32
mroodsari@ku.edu.tr
Industrial Engineering, Koc University, Istanbul, Turkey
Kasimbeyli, Nergiz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-18
nkasimbeyli@anadolu.edu.tr
Industrial Engineering, Anadolu University, Eskisehir,
Turkey
Kasimbeyli, Refail . . . . . HD-02, TE-02, HD-14, HD-18, FB-21,
HE-26
rkasimbeyli@anadolu.edu.tr
Industrial Engineering, Anadolu University, Eskisehir,
Turkey
Kasirzadeh, Atoosa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-03
atoosa.kasirzadeh@polymtl.ca
GERAD, Montreal, Quebec, Canada
Kassa, Rabah . . . . . . . . . . . . . . . . . . . . . . . TD-16, MB-23, ME-29
rabah_kassa2002@yahoo.fr
mathematique, Universite Bejaia algerie, bejaia, Algeria
Kassay, Gabor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-26
kassay@math.ubbcluj.ro
Mathematics, Babes-Bolyai University, Cluj, Romania
Kasyanov, Pavlo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-19
kasyanov@i.ua
National Technical University of Ukraine, Kyiv, Ukraine
Katagiri, Hideki . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-26
348
katagiri-h@hiroshima-u.ac.jp
Hiroshima University, Japan
Katehakis, Michael . . . . . . . . . . . . . . . . . . . . . . . . . HA-19, MB-19
mnk@rutgers.edu
Rutgers, Piscataway, NJ, United States
Katrutsa, Alexandr . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-16
amkatrutsa@yandex.ru
Moscow Institute of Physics and Technology, Russian Federation
Kawano, Hiroyuki . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-16
kawano@nanzan-u.ac.jp
Department of Systems Design and Engineering, Nanzan
University, Seto, Aichi, Japan
Kawas, Ban . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-43
bkawas@us.ibm.com
IBM Research, United States
Kawasaki, Hidefumi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-35
kawasaki@math.kyushu-u.ac.jp
Faculty of Mathematics, Kyushu University, Fukuoka, Japan
Kaya, Anil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-16
anll.k@hotmail.com
Izmir University of Economics, Izmir, Turkey
Kaya, Onur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-37
okaya@ku.edu.tr
INDR, Koc University, Istanbul, Turkey
Kaya, Tekiner . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-13
tekinerkaya@hotmail.com
Business Administration, Ankara University, Ankara,
Ankara, Turkey
Kayacı Çodur, Merve . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-07
mkayaci@atauni.edu.tr
Industrial Engineering, Ataturk University, Erzurum, Turkey
Kayakutlu, Gulgun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-29
gkayakutlu@gmail.com
Industrial Engineering, Istanbul Technical University, Istanbul, Turkey
Køber, Petter Kristian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-33
pkk@ffi.no
Dept. of Analysis, FFI (Norwegian Defence Research Establishment), Norway
Kayguluoglu, Cem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-27
kayguluoglucem@hotmail.com
Business Adminstration, Uludag University, Bursa, Turkey
Kayis, Enis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-39
enis.kayis@ozyegin.edu.tr
Industrial Engineering, Ozyegin University, Istanbul, International, Turkey
Kärkkäinen, Leena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-36
leena.karkkainen@metla.fi
Finnish Forest Research Institute, Joensuu, Finland
Kazaz, Burak . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-19, TE-24
bkazaz@syr.edu
Syracuse University, Syracuse, United States
Ke, Ginger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-32
gke@mun.ca
Faculty of Business Administration, Memorial University of
IFORS 2014 - Barcelona
Newfoundland, St. John’s, NL, Canada
Kedad-Sidhoum, Safia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-12
safia.kedad-sidhoum@lip6.fr
Lip6 - Upmc, Paris, France
Kedmati, Jamaleddin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-36
j-khedmati@razi.tums.ac.ir
Pharmacoeconomics & Pharmaceutical Administration,
TUMS, Tehran, Tehran, Iran, Islamic Republic Of
Keeling, Kellie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-35
Kellie.Keeling@du.edu
Business Information & Analytics, University of Denver,
Denver, CO, United States
Kegelart, Tanguy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-19
tanguy.kegelart@uclouvain.be
Louvain School of Management, Université catholique de
Louvain, Belgium
Kei, Kutu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-37
kutukei1980@gmail.com
Applied Imformation Technology, The Kyoto College of
Graduate School for Informatics, Kyoto, Kyoto, Japan
Keleş, Büşra . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-35
busrakeles88@gmail.com
Industrial Engineering, TOBB University of Economics and
Technology, Ankara, Turkey
Kellner, Kai . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-16
kellner@math.uni-frankfurt.de
Goethe University Frankfurt, Frankfurt am Main, Germany
AUTHOR INDEX
Kersting, Jan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-08
jan.kersting@isi.fraunhofer.de
Energy Policy and Energy Markets, Fraunhofer Institute for
Systems and Innovation Research ISI, Karlsruhe, Germany
Kesavan, Saravanan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-19
skesavan@unc.edu
UNC Kenan-Flagler, Chapel Hill, North Carolina, United
States
Keshvari, Abolfazl . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-18
abolfazl.keshvari@aalto.fi
Aalto University School of Business, Finland
Keskin, Burak . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-35
burakkeskiin@gmail.com
Business Administration, Cankiri Karatekin University,
Cankiri, Turkey
Keskin, Neslihan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-24
neslihankeskin91@gmail.com
Industrial Engineering, Istanbul Kültür University, Istanbul,
Turkey, Turkey
Kettinger, William . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-31
Bill.kettinger@memphis.edu
Management information systems, University of Memphis,
Memphis, TN, United States
Keviczky, Tamas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-20
t.keviczky@tudelft.nl
Delft Center for Systems and Control, Delft University of
Technology, Delft, Netherlands
Kemahlioglu-Ziya, Eda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-22
ekemahl@ncsu.edu
North Carolina State University, Raleigh, United States
Kezić, Danko . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-02, HD-05
danko@pfst.hr
Department of Maritime electronics and informatics, Faculty
of Maritime Studies, University of Split, Split, Croatia
Kendi, Salima . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-31
salima_kendi@yahoo.fr
Operational Research, University of Bejaia, Bejaia, Bejaia,
Algeria
Khader, Ahamad Tajudin . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-23
tajudin@cs.usm.my
School of Computer Sciences, Universiti Sains Malaysia,
Georgetown, Penang, Malaysia
Kenne, Jean-Pierre . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-13
Jean-Pierre.Kenne@etsmtl.ca
University of Quebec, École de Technologie Supérieure,
Montréal, Quebec, Canada
Khairani, Nerli . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-17
knerli@yahoo.com
Mathematics, University Negeri Medan/Grad. School of
Math. USU, Medan, Indonesia
Kennedy, Chris. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-06
christopher.kennedy@utoronto.ca
Civil Engineering, University of Toronto, Toronto, Ontario,
Canada
Khalifa, Khalifa Nasser . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-42
alkhalifa@qu.edu.qa
Qatar University, Qatar
Kent, Gerhard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-40
10065237@nwu.ac.za
North-West University, South Africa
Keramydas, Christos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-35
chkeramy@auth.gr
Mechanical Engineering, Aristotle University of Thessaloniki, Thessaloniki, Greece
Kerkhove, Louis-Philippe . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-12
louisphilippe.kerkhove@ugent.be
Faculty of Economics and Business Administration, Ghent
University, Gent, Belgium
Kersten, Gregory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-23
gregory@jmsb.concordia.ca
Concordia University, Ottawa, Ontario, Canada
Khalil, Wissam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-33
khalil_wissam@hotmail.com
Artois, Lens, France
Khalili, Azam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-19
azamkhalili84@yahoo.com
University of Isfahan, Isfahan, Iran, Islamic Republic Of
Khamooshi, Homayoun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-14
hkh@gwu.edu
Decision Sciences, George Washington Uinversity, Washington, DC, United States
Khan, Raza . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-02
razakhan2004@gmail.com
Manchester Business School, University of Manchester,
Stockport, United Kingdom
Khanh, Phan Quoc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-37
349
AUTHOR INDEX
IFORS 2014 - Barcelona
pqkhanh@hcmiu.edu.vn
Mathematics, International University of Hochiminh City,
Hochiminh City, Viet Nam
Kharbeche, Mohamed . . . . . . . . . . . . . . . . . . . . . . ME-19, ME-21
mkharbec@qu.edu.qa
Mechanical and Industrial Engineering, Qatar University,
Doha, Qatar, Qatar
Kheiri, Ahmed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-28, HE-33
axk@cs.nott.ac.uk
School of Computer Science, ASAP group, University of
Nottingham, Nottingham, United Kingdom
Khominich, Dmitry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-18
dmitry.khominich@datadvance.net
Datadvance, Moscow, Russian Federation
Khritankov, Anton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-16
anton.khritankov@acm.org
MIPT, Russian Federation
Khusnullin, Nail . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-01
nhusnullin@gmail.com
Ics Ras, Russian Federation
Ki, Youngmin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-25
trigun@postech.ac.kr
Industrial & Management Engineering, POSTECH, Korea,
Republic Of
Kidd, Martin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-01, HE-17
martin.kidd@unibo.it
Department of Electrical, Electronic, and Information Engineering, University of Bologna, Bologna, Italy
Kieckhäfer, Karsten. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-08
k.kieckhaefer@tu-braunschweig.de
Institute of Automotive Management and Industrial Production, Technische Universität Braunschweig, Braunschweig,
Germany
Kijima, Shuji . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-09
kijima@inf.kyushu-u.ac.jp
Department of Informatics, Graduate School of ISEE,
Kyushu University, Fukuoka, Japan
Kilianova, Sona . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-24
sona.kilianova@fmph.uniba.sk
Department of Applied Mathematics and Statistics, Comenius University, Bratislava, Slovakia
Kilic, Kemal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-26
kkilic@sabanciuniv.edu
Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul
Kilic, Onur A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-13
onuralp@hacettepe.edu.tr
Department of Management, Hacettepe University, Turkey
Kilic, Sezgin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-30
s.kilic@hho.edu.tr
Industrial Engineering, Turkish Air Force Academy, Istanbul,
Turkey
Kim, Byung-In . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-25
bkim@postech.ac.kr
Industrial and Management Engineering, Pohang University
of Science and Technology (POSTECH), Korea, Republic Of
Kim, Changhee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-27
350
heeslife@snu.ac.kr
Operations Management, College of Business Administration, Seoul National University, Seoul, Gwanakgu, Korea,
Republic Of
Kim, Chulhan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-13
chulhan.kim@simlab.kaist.ac.kr
Industrial and Systems Engineering, KAIST, Daejeon, Korea,
Republic Of
Kim, Deok-Hwan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-40
thekan0723@gmail.com
Quality Management Office, Korea Institute of Energy Research, Daejeon, Korea, Korea, Republic Of
Kim, Dohyun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-16
ftgog@kisti.re.kr
Korea Institute of Science and Technology Information,
Seoul, Korea, Republic Of
Kim, Dongwook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-04
blizzard@snu.ac.kr
Industrial Engineering, Seoul National University, Korea,
Republic Of
Kim, Hyewon. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-19
gjch305@naver.com
Graduate School of Economics, Osaka University, Toyonaka,
Japan
Kim, Hyun Jung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-44
suntie31@snu.ac.kr
College of Business Administration, Seoul National University, Seoul, Korea, Republic Of
Kim, Jae Ho . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-20
jaek@princeton.edu
Princeton University, Princeton, NJ, United States
Kim, Jinho . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-42
jhkim04@gmail.com
Rutgers University, United States
Kim, Jooyoung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-04
trafficplan@naver.com
Transportation, University of Seoul, Seoul, Seoul, Korea, Republic Of
Kim, Jun Seok . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-16
bliths@gmail.com
School of Industrial Management Engineering, Korea University, Korea, Republic Of
Kim, Jun-Seong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-42
soulloan@postech.ac.kr
Industrial and management engineering, POSTECH, Pohang,
Gyeongbuk, Korea, Democratic People’s Republic Of
Kim, Kap Hwan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-37
kapkim@pusan.ac.kr
Industrial Engineering, Pusan National University, Busan,
Korea, Republic Of
Kim, Kwang-Jae . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-23
kjk@postech.ac.kr
POSTECH, Korea, Republic Of
Kim, Minjun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-23
minjun@postech.ac.kr
POSTECH, Korea, Republic Of
Kim, Sang Won . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-35
IFORS 2014 - Barcelona
poms123@naver.com
College of Business Administration, University of Ulsan, Ulsan, Korea, Republic Of
Kim, Seong-Jun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-42
sjkim@gwnu.ac.kr
Industrial Eng., Gangneung-Wonju National University,
Gangneung, KW, Korea, Republic Of
Kim, Seoung Bum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-42
sbkim1@korea.ac.kr
Industrial Management Engineering, Korea University,
Seoul, Korea, Republic Of
Kim, Solyi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-32
solyi1129@cbnu.ac.kr
Management Information Systems, Chungbuk National University, Cheongju, Chungbuk, Korea, Republic Of
Kim, Soo Wook . . . . . . . . . . . . . . . . . . . . . . TB-09, MA-27, HD-44
kimsoo2@snu.ac.kr
College of Business Administration, Seoul National University, Seoul, Korea, Republic Of
AUTHOR INDEX
Kischka, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-33
P.Kischka@wiwi.uni-jena.de
Statistics, University Jena, Jena, Germany
Kisialiou, Yauheni . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-05
Yauheni.Kisialiou@himolde.no
Molde University College - Specialized University in Logistics, Norway
Kiszova, Zuzana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-26
kiszova@opf.slu.cz
Department of mathematical methods in economics, Silesian
university in Opava, School of business administration in
Karvina, Karvina, Czech Republic
Kitaeva, Anna . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-13
kit1157@yandex.ru
Tomsk Polytechnic University, Russian Federation
Kitagawa, Tatsuya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-35
t.k.returnace@gmail.com
GE Japan Corporation, Minato-ku, Tokyo, Japan
Kim, Sung-Shick . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-16, TE-32
sungskim@korea.ac.kr
Division of Information Management, Korea University,
seoul, Korea, Korea, Republic Of
Kitagawa, Tomohiro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-27
em52001@nda.ac.jp
Graduate School of Science and Engineering, National Defense Academy Japan, Japan
Kim, Tae-Sung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-32
kimts@cbnu.ac.kr
Management Information Systems, Chungbuk National University, Chongju, Chungbuk, Korea, Republic Of
Kivunike, Florence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-31
florence@dsv.su.se
Computer and Systems Sciences, Stockholm university,
Kista, Sweden
Kim, Woo-Sik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-42
wskim@kogas.re.kr
Korea Gas Corporation R&D Center, Ansan, Korea, Republic
Of
Kılıç, Gökhan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-30
gk.klc89@gmail.com
Industrial Engineering, Istanbul Kültür University, Turkey
Kimms, Alf . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-22
alf.kimms@uni-due.de
Mercator School of Management, University of DuisburgEssen, Duisburg, Germany
Kimura, Sakuo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-19
skimura@res.kutc.kansai-u.ac.jp
Takatsuki Campus Office, Kansai University, Takatsuki,
Japan
Kimura, Yutaka . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-09, MD-09
yutaka@akita-pu.ac.jp
Systems Science and Technology, Akita Prefectural University, Yuri-honjo, Akita, Japan
Kinoshita, Eizo. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-29
kinoshit@urban.meijo-u.ac.jp
Urban Science Department, Meijo University, Kani, Gifu,
Japan
Kirchhoff, Fabian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-01
kirchhoff@math.tu-clausthal.de
Clausthal University of Technology, Germany
Kirschstein, Thomas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-29
thomas.kirschstein@wiwi.uni-halle.de
Chair of Production & Logistics, Martin-Luther-University
Halle-Wittenberg, Halle/Saale, – Bitte auswählen (nur für
USA / Kan. / Aus.), Germany
Kirshner, Sam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-27
skirshner@business.queensu.ca
School of Business, Queen’s University, Canada
Kınacı, İsmail . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-43
ikinaci@selcuk.edu.tr
Statistics, Selçuk University, Konya, Turkey
Kjenstad, Dag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-03
dag.kjenstad@sintef.no
SINTEF, Oslo, Norway
Klabjan, Diego . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-41, HA-45
d-klabjan@northwestern.edu
Industrial Engineering and Management Sciences, Northwestern University, Evanston, IL, United States
Klamroth, Kathrin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-18
klamroth@math.uni-wuppertal.de
Department of Mathematics and Informatics, University of
Wuppertal, Wuppertal, Germany
Klein, Sulamita . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-12
sula@cos.ufrj.br
COPPE-PESC, Universidade Federal do Rio de Janeiro, Rio
de Janeiro, RJ, Brazil
Kleinmuntz, Don . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-23, HD-23
don@kleinmuntzassociates.com
Kleinmuntz Associates, Chicago, IL, United States
Klibi, Walid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-41
walid.klibi@kedgebs.com
Operations Management and Information Systems Department, Kedge Bs / Cirrelt, Bordeaux, France
Klier, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-06
michael.klier@tu-dresden.de
351
AUTHOR INDEX
IFORS 2014 - Barcelona
Institute for Transport and Economics, TU Dresden, Dresden,
Germany
Kliewer, Natalia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-03
natalia.kliewer@fu-berlin.de
Information Systems, Freie Universitaet Berlin, Berlin, Germany
Kljajic Borstnar, Mirjana . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-42
mirjana.kljajic@fov.uni-mb.si
Laboratory for Decision Processes and Knowledge-based
systems, University of Maribor, Faculty of Organizational
Sciences, Maribor, Slovenia, Slovenia
Klose, Andreas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-19
aklose@imf.au.dk
Department of Mathematics, Aarhus University, Aarhus,
Denmark
Knight, Vincent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-09
Knightva@cf.ac.uk
School of Mathematics, Cardiff University, Cardiff, United
Kingdom
Knippenberg, Willem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-33
willem.knip@gmail.com
OR, Royal Netherlands Naval Collage, Den Haag, Netherlands
Knutti, Reto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-08
reto.knutti@env.ethz.ch
Institute for Atmospheric and Climate Science, ETH Zurich,
Zurich, Switzerland
Ko, Chang Seong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-37
csko@star.kyungsung.ac.kr
Kyungsung University, Busan, Korea, Republic Of
Ko, Hong Seung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-27, MB-37
h_ko@kcg.ac.jp
Web Business Technology, The Kyoto College of Graduate
Studies for Informatics, Kyoto, Japan
Koberstein, Achim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-04
koberstein@wiwi.uni-frankfurt.de
Business Administration, Goethe-University of Frankfurt,
Frankfurt am Main, Germany
Köbis, Elisabeth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-18
koebis@math.fau.de
Department of Mathematics, University of ErlangenNuremberg, Erlangen, Bavaria, Germany
Koc, Ali . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-20, MA-43
akoc@us.ibm.com
Business Analytics and Mathematical Sciences, IBM TJ Watson Research Center, Yorktown Heights, NY, United States
Kocas, Cenk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-10
kocas@sabanciuniv.edu
School of Management, Sabanci University, Istanbul, Turkey
Koch, Thorsten . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-28, HA-39
koch@zib.de
Optimization, Zuze Institue Berlin, Berlin, Germany
Management, Bar-Ilan University, Israel
Koh, Shiegheun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-13
sgkoh@pknu.ac.kr
Systems Management and Engineering, Pukyong National
University, Busan, Korea, Republic Of
Koide, Noriaki . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-38
noriaki-koide@ist.osaka-u.ac.jp
Department of Information and Physical Sciences, Graduate
School of Information Science and Technology, Osaka University, Suita, Osaka, Japan
Koide, Takeshi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-10, HD-19
koide@konan-u.ac.jp
Konan University, Kobe, Japan
Kojic, Vedran . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-32
vkojic@efzg.hr
of Mathematics, Faculty of Economics and Business, Zagreb,
Croatia
Kojima, Kentaro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-32
kojima@ise.aoyama.ac.jp
Industrial and Systems Engineering, Aoyama Gakuin University, Japan
Kok, Gurhan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-20, TD-22
gurhan.kok@duke.edu
Duke University, Durham, NC, United States
Koksal, Gulser . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-43
koksal@metu.edu.tr
Industrial Engineering, Middle East Technical University,
Ankara, Turkey
Koksalan, Murat . . . . . . . . . . . . . . . . . . . . . FA-18, HB-18, HE-18
koksalan@metu.edu.tr
Industrial Engineering, METU, Turkey
Kolomvos, George . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-42
George.Kolomvos@gmail.com
Industrial Engineering and Optimization, Kathikas Institute
of Research & Technology, Cyprus
Koltai, Tamás . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-32
koltai@mvt.bme.hu
Management and Corporate Economics, Budapest University
of Technology and Economics, Budapest, Hungary
Komosko, Larisa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-12
lucent.92@mail.ru
The Higher School of Economics, Nizhny Novgorod, Russian Federation
Konczak, Aneta . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-32
aneta.konczak@put.poznan.pl
Division of Construction Technology and Management, Poznan University of Technology, Poznan, Poland
Kong, Lingchen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-38
konglchen@126.com
Department of Applied Mathematics, Beijing Jiaotong University, Beijing, China
Kochenberger, Gary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-40
gary.kochenberger@ucdenver.edu
University of Colorado Boulder, Boulder, United States
Kong, Qingxia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-16
qingxia.kong@gmail.com
School of Business, Universidad Adolfo Ibanez, Santiago,
Chile
Kogan, Konstantin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-25
kogank@biu.ac.il
Kontic, Branko . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-42
branko.kontic@ijs.si
352
IFORS 2014 - Barcelona
Environmental Sciences, Jozef Stefan Institute, Ljubljana,
Slovenia
Kontic, Davor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-42
davor.kontic@ijs.si
Environmental Sciences, Jozef Stefan Institute, Ljubljana,
Slovenia
Kontovas, Christos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-05
kontova@transport.dtu.dk
DTU Transport, Technical University of Denmark, Kgs. Lyngby, Denmark
Koo, Hongmi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-32
hongmi.koo@gmail.com
Center for Development Research (ZEF), University of Bonn,
Korea, Republic Of
Koo, Hyeng-Keun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-30
hkoo@ajou.ac.kr
Department of Financial Engineering, Ajou University, Suwon, Korea, Republic Of
Koole, Ger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-10, FA-13
ger.koole@vu.nl
Mathematics, VU University Amsterdam, Amsterdam,
Netherlands
Kopfer, Herbert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-42
kopfer@uni-bremen.de
Department of Business Studies & Economics, Chair of Logistics, University of Bremen, Bremen, Germany
Korad, Akshay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-07
akorad@mainex1.asu.edu
Arizona State University, Tempe, AZ, United States
Korelič, Igor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-42
igor.korelic@result.si
Result d.o.o., Ljubljana, Slovenia
Korenblit, Mark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-41
korenblit@hit.ac.il
Holon Institute of Technology, Holon, Israel
Korhonen, Pekka . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-18
pekka.korhonen@aalto.fi
Information and Service Economy, Aalto University School
of Business, Helsinki, Finland
Koronakos, Gregory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-10
gkoron@unipi.gr
Informatics, University of Piraeus, Piraeus, Greece
Korotkov, Vladimir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-19
wladko@tut.by
Department of Mathematics and Statistics, University of
Turku, Turku, Finland
Korzilius, Hubert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-23
h.korzilius@fm.ru.nl
Institute for Management Research, Radboud University Nijmegen, Netherlands
Koschker, Susanne . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-07
susanne.koschker@tu-dresden.de
Chair of Energy Economics, Technische Universität Dresden,
Dresden, Germany
Koshizuka, Takeshi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-06
koshizuk@nanzan-u.ac.jp
Sciences and Engineering, Nanzan University, Seto, Aichi,
AUTHOR INDEX
Japan
Kostarelou, Eftychia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-14
ekostarelou@yahoo.gr
Mechanical Engineering, University of Thessaly, Volos,
Greece
Kostic, Bojan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-41
bojan.kostic@uniroma1.it
Department of Civil, Constructional and Environmental Engineering, Sapienza University of Rome, Rome, Italy
Kostina, Ekaterina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-07
kostina@mathematik.uni-marburg.de
Department of Mathematics and Computer Science, University of Marburg, Marburg, Germany
Kostoglou, Vassilis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-40
vkostogl@it.teithe.gr
Department of Informatics, Alexander TEI of Thessaloniki,
Thessaloniki, Greece
Kotiadis, Kathy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-23
kathy.kotiadis@associate.wbs.ac.uk
Warwick Business School, University of Warwick, Coventry,
United Kingdom
Koussis, Nicos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-43
nicos.koussis@gmail.com
Frederick University, Cyprus
Koutsopoulos, Haris . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-01
haris@MIT.EDU
Department of Civil and Environmental Engineering, MIT
logo Massachusetts Institute of Technology, Cambridge, MA,
United States
Kouvela, Anastasia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-12
a.kouvela@lse.ac.uk
Management Science Group, London School of Economics
and Political Science, London, United Kingdom
Kovacevic Vujcic, Vera . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-17
verakov@fon.bg.ac.rs
Laboratory for Operational Research, Faculty of Organizational Sciences, University of Belgrade, Belgrade, Serbia,
Serbia
Kovacevic, Raimund . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-09
raimund.kovacevic@univie.ac.at
Department of Statistics and Operations Research, University
Vienna, Wien, Wien, Austria
Kovacs, Annamaria . . . . . . . . . . . . . . . . . . . . . . . . . HD-22, HE-22
panni@cs.uni-frankfurt.de
Goethe University Frankfurt, Germany
Kovalev, Sergey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-13
smkovalev@yahoo.com
Institut Fayol, École Nationale Supérieure des Mines de
Saint-Étienne, Saint-Étienne, France
Kozanidis, George . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-14, HE-37
gkoz@mie.uth.gr
Mechanical Engineering, University of Thessaly, Volos,
Magnisia, Greece
Kozeletskyi, Igor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-22
igor.kozeletskyi@uni-due.de
Mercator School of Management, University of DuisburgEssen, Duisburg, Germany
353
AUTHOR INDEX
IFORS 2014 - Barcelona
Kozlovskaia, Nadezhda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-40
kknn@yandex.ru
SPbSU, St Petersburg, Russian Federation
ramesh@cs.sfu.ca
School of Computing Science, Simon Fraser University,
Burnaby, British Columbia, Canada
Kpondjo, Nadia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-14
nadia.kpondjo@ifpen.fr
Economie, Electricite de France R&D/IFPEN/EconomiX,
Villejuif, France
Kroenke, Adriana . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-25, HB-34
didlen@terra.com.br
PPGMNE/Mathematics, UFPR/FURB, Blumenau, Santa
Catarina, Brazil
Kraft, Volker . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-08, MB-21
volker.kraft@jmp.com
JMP Devision, SAS Institute, Heidelberg, Germany
Krogh Boomsma, Trine . . . . . . . . . . . . . . . . . . . . . . MB-10, FB-20
trine@math.ku.dk
Department of Mathematical Sciences, University of Copenhagen, København Ø, Denmark
Krahmer, Felix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-25
f.krahmer@math.uni-goettingen.de
Institute for Numerical and Applied Mathematics, University
of Göttingen, Göttingen, Germany
Krarup, Jakob . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-28
krarup@diku.dk
Dept. of Computer Science, University of Copenhagen,
Birkeroed, Denmark
Krass, Dmitry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-03
krass@rotman.utoronto.ca
Rotman School of Mgmt, University of Toronto, Toronto,
Ontario, Canada
Kratica, Jozef . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-17
jkratica@mi.sanu.ac.rs
Mathematical Institute, Serbian Academy of Sciences and
Arts, Belgrade, Serbia
Krause, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-09
michael.krause@tu-clausthal.de
Clausthal University of Technology, Clausthal-Zellerfeld,
Germany
Kreikebaum, Frank . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-20
frankkreikebaum@yahoo.com
Smart Wire Grid Inc., Oakland, United States
Kreinovich, Vladik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-43
vladik@utep.edu
Computer Science, University of Texas at El Paso, El Paso,
Texas, United States
Kress, Moshe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-32
mkress@nps.edu
Operations Research, Naval Postgraduate School, Monterey,
CA, United States
Krokhmal, Pavlo . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-14, HD-20
krokhmal@engineering.uiowa.edu
Mechanical and Industrial Engineering, University of Iowa,
Iowa city, IA, United States
Kroon, Leo . . . . . . . . . . . . . . . . . . HA-01, HE-01, MD-01, ME-01
lkroon@rsm.nl
Rotterdam School of Management, Erasmus University Rotterdam, Rotterdam, Netherlands
Krüger, Gustavo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-15
gustavokruger.professor@hotmail.com
Accountant, Universidade Federal Do Rio Grande Do Sul UFRGS, Guaiba, Rio Grande do Sul, Brazil
Kruger, Hennie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-16, TB-40
Hennie.Kruger@nwu.ac.za
School of Computer, Statistical and Mathematical Sciences,
North-West University, Potchefstroom, South Africa
Krushinsky, Dmitry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-02
d.krushinsky@gmail.com
Operations, Planning, Accounting and Control, Eindhoven
University of Technology, Eindhoven, Netherlands
Krygsman, Stephan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-02
skrygsman@sun.ac.za
Department of Logistics, Stellenbosch University, Stellenbosch, South Africa
Krylatov, Alexander . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-04
partizan-sasha@yandex.ru
Saint-Petersburg state university, Russian Federation
Kuş, Coşkun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-43
coskun@selcuk.edu.tr
Statistics, Selçuk University, Konya, Turkey
Kressner, Alexander . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-06
kressner@uni-hohenheim.de
Procurement and Production, University of Hohenheim, Germany
Kubota, Keiichi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-30
kubota@cc.musashi.ac.jp
Graduate School of Strategic Management, Chuo University,
Japan
Kreter, Stefan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-12
stefan.kreter@tu-clausthal.de
Clausthal University of Technology, Clausthal-Zellerfeld,
Germany
Kuchina, Elena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-30
kuchina.elena1@gmail.com
University of Economics, Prague, Czech Republic
Kriebel, Johannes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-38
johannes.kriebel@student.kit.edu
Economics and Management, Karlsruhe Institute of Technology, Wentorf, Deutschland, Germany
Kuchta, Dorota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-13
dorota.kuchta@pwr.wroc.pl
Informatics and Management, Wroclaw University of Technology, Wroclaw, Poland
Krisciukaitiene, Irena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-14
irena@laei.lt
Lithuanian Institute of Agrarian Economics, Lithuania
Kucuk, Mahide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-18
mkucuk@anadolu.edu.tr
Department of Mathematics, Anadolu University, Eskisehir,
Turkey
Krishnamurti, Ramesh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-02
Kucuk, Yalcin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-18
354
IFORS 2014 - Barcelona
AUTHOR INDEX
ykucuk@anadolu.edu.tr
Department of Mathematics, Anadolu University, Eskisehir,
Turkey
Kundakcioglu, Erhun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-25
erhun.kundakcioglu@ozyegin.edu.tr
Industrial Engineering, Ozyegin University, Istanbul, Turkey
Kucukyazici, Beste . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-33
beste.kucukyazici@mail.mcgill.ca
Desautels Faculty of Management, McGill University, Montreal, Quebec, Canada
Kunnumkal, Sumit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-15
Sumit_Kunnumkal@isb.edu
Indian School of Business, Hyderabad, India
Kuhn, Heinrich . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-19, ME-19
heinrich.kuhn@ku-eichstaett.de
Operations Management, Catholic University of EichstaettIngolstadt, Ingolstadt, Bavaria, Germany
Kulkarni, Shailesh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-24
Shailesh.Kulkarni@unt.edu
Department of Information Technology & Decision Sciences,
University of North Texas, Denton, United States
Külünk, M.Erdem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-10
merdem@sabanciuniv.edu
Sabanci University, Istanbul, Turkey
Kulus, Marcin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-12
marcinkulus@gmail.com
Poznan University of Technology, Poznan, Poland
Kumam, Poom . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-37, TA-37
poom.kumam@mail.kmutt.ac.th
Mathematics, King Mongkut’s University of Technology
Thonburi, Bangkok, Thailand
Kumam, Wiyada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-37
jeabkum@gmail.com
Mathematics and Computer Science, Rajamangala University
of Technology Thanyaburi, Pathumthani, Thailand
kumar, Ashwani . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-16
ashwanikumar@nus.edu.sg
Industial and Systems Engineering, National University of
Singapore, Singapore, Singapore
kumar, Pankaj . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-34
maths.pk@gmail.com
Mathematics, Indian Institute of Technology Kharagpur
(W.B.) India, Kharagpur, West Bengal, India
Kumar, Shruthi S . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-13
shruthulisha@gmail.com
MBA, University of Business in Wroclaw, Wroclaw, Poland
Kumar, Sushil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-44
sk@iiml.ac.in
Operations Management, Indian Institute of Management,
Lucknow, Lucknow, India
Kummer, Sebastian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-06
sebastian.kummer@wu.ac.at
Institute of Transport and Logistics Management, Vienna
University of Business and Economics, Vienna, Austria
Kümmling, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-01
michael.kuemmling@tu-dresden.de
Faculty of Transportation and Traffic Sciences, Chair of Traffic Flow Science, Technische Universität Dresden, Dresden,
Sachsen, Germany
Kunc, Martin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-24
martin.kunc@wbs.ac.uk
Warwick Business School, University of Warwick, Coventry,
United Kingdom
Kuno, Seiya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-30
kuno@sigmath.es.osaka-u.ac.jp
Graduate School of Economics, Osaka University, Toyonaka,
Osaka, Japan
Kunsch, Pierre . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-07
pkunsch@vub.ac.be
BUTO, Vrije Universiteit Brussel, Brussels, Belgium
Kunz, Timo P. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-15
t.p.kunz@lancaster.ac.uk
Management Science, Lancaster University Management
School, Lancaster, United Kingdom
Kuo, Yong Hong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-22
yhkuo@must.edu.mo
School of Business, Macau University of Science and Technology, Taipa, Macau
Kupfer, Stefan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-08
stefan.kupfer@ovgu.de
Otto-von-Guericke University Magdeburg, Germany
Kurasova, Olga . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-18
Olga.Kurasova@mii.vu.lt
Vilnius University, Institute of Mathematics and Informatics,
Vilnius, Lithuania
Kurbanlı, Abdullah Selçuk . . . . . . . . . . . . . . . . . . . . . . . . . . TD-12
akurbanli42@gmail.com
Mathematics, Necmettin Erbakan University, Konya, Konya,
Turkey
Kurhofer, Kai . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-43
kai.kurhofer@uni-bielefeld.de
Chair for Quantitative Accounting & Financial Reporting,
University of Bielefeld, Bielefeld, Germany
Kurilic, Mico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-05
kurilicm@macewan.ca
Decision Science and Supply Chain Management, Grant
MacEwan University, Edmonton, Alberta, Canada
Kuroiwa, Daishi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-18
kuroiwa@math.shimane-u.ac.jp
Shimane University, Japan
Kurt, Mustafa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-07
mkurt@gazi.edu.tr
Industrial Engineering, Gazi University, Turkey
Kurt, Suat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-12
suatkurt81@gmail.com
Makine Muhendisliği, Kara Harp Okulu, Ankara, Turkey
Kurttila, Mikko . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-36
mikko.kurttila@metla.fi
Joensuu Research Unit, Finnish Forest Research Institute,
Joensuu, Finland
Kusunoki, Yoshifumi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-35
kusunoki@eei.eng.osaka-u.ac.jp
Osaka University, Japan
355
AUTHOR INDEX
IFORS 2014 - Barcelona
Kuyzu, Gultekin . . . . . . . . . . . . . . . . . . . . . . TB-02, TA-04, HD-37
gkuyzu@etu.edu.tr
Industrial Engineering, TOBB University of Economics and
Technology, Ankara, Turkey
Kuzgunkaya, Onur . . . . . . . . . . . . . . . . . . . . . . . . . MB-22, HB-41
onurk@encs.concordia.ca
Mechanical and Industrial Engineering, Concordia University, Montreal, Quebec, Canada
Kuzmin, Arsentii . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-16
senatormipt@gmail.com
Department of Control and Applied Mathematics, Moscow
Institute of Physics and Technology, Moscow, Russian Federation
Kuzmina, Lyudmila . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-44
Lyudmila.Kuzmina@kpfu.ru
Theoretical mechanics, Kazan National Research Technical
University - Kazan Aviation Institute - National Research
University, Kazan, Russian Federation
Department of Mechanical, Energy and Management Engineering, University of Calabria, Rende, Italy
Laguna, Manuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-40, TB-45
laguna@colorado.edu
Leeds School of Business, University of Colorado at Boulder,
Boulder, Colorado, United States
Lahaie, Sebastien . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-22
slahaie@microsoft.com
Microsoft Research, United States
Lahdelma, Risto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-31
risto.lahdelma@aalto.fi
Department of Energy Technology, Aalto University, Espoo,
Finland
Lai, Chien-Jung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-23
laicj@ncut.edu.tw
Department of Distribution Management, National Chin-Yi
University of Technology, Taichung, Taiwan
Kuznetsov, Mikhail . . . . . . . . . . . . . . . . . . . . . . . . . . HA-16, TB-16
mikhail.kuznecov@phystech.edu
Moscow Institute of Physics and Technology, Russian Federation
Lai, Chun-Mei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-14, TB-14
chunmei@cc.feu.edu.tw
Department of Marketing and Logistics Management, Far
East University, Tainan, Taiwan
Kvamsdal, Sturla. . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-07, MA-36
sturla.kvamsdal@nhh.no
Snf As, Norway
Lai, Chunhui . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-12
laich2011@msn.cn
School of Mathematics and Statistics, Minnan Normal University, Zhangzhou, Fujian, China
Kwon, Oh-Jin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-16
dbajin@kisti.re.kr
Korea Institute of Science and Technology Information, Korea, Republic Of
Kwon, Suehyun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-24
suehyun.kwon@ucl.ac.uk
Department of Economics, University College London, London, United Kingdom
Kyriakidis, Epaminondas . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-41
ekyriak@aueb.gr
Statistics, Athens University of Economics and Business,
Athens, Greece
Laas-Nesbitt, Eric . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-09
eric-john.laas-nesbitt@univie.ac.at
Statistics and Operations Research, University of Vienna,
Austria
Labbé, Martine . . . . . . . . . . . . . . MD-11, MA-15, HB-25, FB-41
mlabbe@ulb.ac.be
computer Science, Université Libre de Bruxelles, Bruxelles,
Belgium
Laborie, Philippe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-41
laborie@fr.ibm.com
Software Group, IBM, Gentilly, France
Ladhari, Talel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-14
talel_ladhari2004@yahoo.fr
Unité de recherche ROI, Ecole Polytechnique de Tunisie, La
Marsa, France
Ladrón de Guevara, Antonio . . . . . . . . . . . . . . . . . . . . . . . . HB-40
antonio.ladron@upf.edu
Economics and Business, Universitat Pompeu Fabra,
Barcelona, Spain
Laganà, Demetrio . . . . . . . . . . . . . . . . . . . . . . . . . . HA-41, MD-45
demetrio.lagana@unical.it
356
Lakner, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-34
plakner@stern.nyu.edu
IOMS, New York University, New York, NY, United States
Lal, Tarun Mohan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-06
mohanlal.tarun@mayo.edu
Mayo Clinic, Rochester, MN, United States
Lalla Ruiz, Eduardo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-40
elalla@ull.es
Estadística, I.O. y Computación, University of La Laguna,
Spain
Lalla Samira, Touhami . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-37
lalla-samira.touham.1@ulaval.ca
Génie Mécanique, Université Laval, Quebec, Canada
Lam, Siu Lee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-16
SLLam@ntu.edu.sg
School of Civil and Environmental Engineering, Nanyang
Technological University, Singapore, Singapore
Lamers, Martien . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-38
Martien.Lamers@UGent.be
Department of Financial Economics, Ghent University,
Ghent, Belgium
Lamghari, Amina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-29
amina.lamghari@mcgill.ca
Mining and Materials Engineering, McGill University, Montreal, Quebec, Canada
Lami, Isabella . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-23, MD-24
isabella.lami@polito.it
Polytechnic of Turin, Turin, Italy
Lamorgese, Leonardo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-27
leonardo.lamorgese@sintef.no
Applied Mathematics, SINTEF, Oslo, Oslo, Norway
IFORS 2014 - Barcelona
Lamsali, Hendrik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-04
hendrik@uum.edu.my
School of Technology Management & Logistics, Northern
University of Malaysia, Sintok, Malaysia
Lančinskas, Algirdas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-18
algirdas.lancinskas@mii.vu.lt
Institute of Mathematics and Informatics, Vilnius University,
Vilnius, Lithuania
Landete, Mercedes . . . . . . . . . . . . . . . . . . . . . . . . . . HA-03, MA-11
landete@umh.es
Departamento de Estadística y Matemática Aplicada, University Miguel Hernández of Elche, Elche, Alicante, Spain
Lange, Anne . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-24
a.lange@bwl.tu-darmstadt.de
Department of Law and Economics, Technische Universität
Darmstadt, Darmstadt, Germany
AUTHOR INDEX
Cass Business School, London, United Kingdom
Larsen, Jesper . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-01
jesla@man.dtu.dk
Department of Management Engineering, Technical University of Denmark, Kgs. Lyngby, Denmark
Larsson, Aron. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-31
aron@dsv.su.se
Dept. of Computer and System Sciences, Stockholm University, kista, Stockholm, Sweden
Lastusilta, Toni . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-21
tlastusilta@gams.com
GAMS Software GmbH, Frechen, Germany
Laumanns, Marco. . . . . . . . . . . . . . . . . . . . . . . . . . . TB-01, MA-43
mlm@zurich.ibm.com
IBM Research - Zurich, Rueschlikon, Switzerland
Langensiepen, Gerd . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-14
gerd.langensiepen@tu-dresden.de
Department of Mathematics, Technische Universität Dresden, Dresden, Germany
Laureano-Cruces, Aana Lilia . . . . . . . . . . . . . . . . . . . . . . . . FB-06
clc@azc.uam.mx
Sistemas, Universidad Autonoma Metropolitana, Mexico,
Distrito Federal, Mexico
Langton, Sebastian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-28
langton@hsu-hh.de
Logistics Management Department, Helmut-SchmidtUniversity, Hamburg, Germany
Lavieri, Mariel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-22
lavieri@umich.edu
The University of Michigan, Ann Harbor, United States
Lannez, Sebastien . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-23
sebastienlannez@fico.com
Xpress Optimization, FICO, Tours, Indre-Et-Loire, France
Lavigne, Denis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-30
denis.lavigne@cmrsj-rmcsj.ca
Science, Royal Military College Saint-Jean, Saint-Jean-surRichelieu, Québec, Canada
Lantz, Frederic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-14, MB-38
frederic.lantz@ifpen.fr
IFP-School, Rueil-Malmaison, France
Lavin, Claudio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-23
claudio.lavin@gmail.com
Universidad Diego Portales, Santiago, Chile
Laporte, Gilbert . . . . . . . FA-01, HA-01, HD-01, TB-02, TE-02
gilbert.laporte@cirrelt.ca
HEC Montreal, Montreal, Canada
Lavor, Carlile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-11, TA-11
clavor@ime.unicamp.br
Applied Mathematics, UNICAMP, Campinas, SP, Brazil
Laporte, Gilbert . . . . . . . . . . . . . . . . . . . . . HB-02, HA-05, HB-31
gilbert@crt.umontreal.ca
Canada Reserach Chair in Distribution Management, HEC
Montreal, Montreal, QC, Canada
Lawton, Craig . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-35
crlawto@sandia.gov
System Sustainment & Readiness, Sandia National Laboratories, Albuquerque, New Mexico, United States
Laraki, Rida . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-24
rida.laraki@gmail.com
LAMSADE, CNRS, Université Dauphine and Ecole Polytechnique, Paris, France
López Redondo, Juana . . . . . . . . . . . . . . . . . . . . . . HA-18, HD-45
jlredondo@ugr.es
Computer Architecture and Technology, University of
Granada, Spain
Lari, Isabella . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-03
isabella.lari@uniroma1.it
Statistics, La Sapienza University, Rome, Italy
López Sánchez, Ana Dolores . . . . . . . . . . . . . . . . . . . . . . . . . TB-37
adlopsan@upo.es
Economía, Métodos Cuantitativos e Historia Económica,
Universidad Pablo de Olavide, Sevilla, Spain
Lariviere, Martin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-22
m-lariviere@kellogg.northwestern.edu
Kellogg School of Management, Northwestern University,
Evanston, Illinois, United States
Larrain, Homero . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-02
larrain@gmail.com
Transporte y Logística, Pontificia Universidad Católica de
Chile, Santiago, RM, Chile
Larsen, Allan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-05
ala@transport.dtu.dk
DTU Transport, Kgs. Lyngby, Denmark
Larsen, Erik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-15
E.R.Larsen@city.ac.uk
López, Julio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-17, TE-17
julio.lopez@udp.cl
Instituto de Ciencias Básicas, Universidad Diego Portales,
Santiago, Metropolitana, Chile
López-Ibáñez, Manuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-33
manuel.lopez-ibanez@ulb.ac.be
IRIDIA, Université Libre de Bruxelles, Bruxelles, Belgium
Layter Xavier, Vinicius . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-17
viniciuslx@gmail.com
Systems Engineering and Computer Sciences Depart., Federal University of Rio de janeiro, Rio de Janeiro, RJ, Brazil
Létocart, Lucas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-11, TA-28
357
AUTHOR INDEX
IFORS 2014 - Barcelona
lucas.letocart@lipn.univ-paris13.fr
Lipn Umr Cnrs 7030, Institut Galilée - Université Paris 13,
Villetaneuse, France
Lazarev, Alexander . . . . . . . . . . . . . . . . . . . . . . . . . . TE-01, FB-12
jobmath@mail.ru
Scheduling theory and discrete optimization, Institute of Control Sciences, Lomonosov Moscow State University, Higher
School of Economics, Moscow, Russian Federation
Le Boudec, Jean-Yves. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-20
jean-yves.leboudec@epfl.ch
École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
Le Menec, Stéphane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-40
stephane.le-menec@mbda-systems.com
GCN, MBDA France, Le Plessis Robinson, France
Le Menestrel, Marc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-24
marc.lemenestrel@upf.edu
Department of Economics and Business, University Pompeu
Fabra, Barcelona, Spain
Le Thi, Hoai An . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-17, TB-17
hoai-an.le-thi@univ-lorraine.fr
Computer Science, University of Lorraine, Metz, France
Le, Hoai Minh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-17, TB-17
minh.le@univ-lorraine.fr
University of Lorraine, Lita, Ufr Mim, Metz, France
Leber, Dennis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-42
dennis.leber@nist.gov
National Institute of Standards and Technology, Gaithersburg, MD, United States
Leboucher, Cedric . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-40
leboucher.cedric@gmail.com
MBDA France, France
Lederman, Shulamit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-22
shulamitl@mail.tau.ac.il
Tel Aviv University, Ramat Aviv, Israel
Ledesma, Juan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-45
jledesma@unq.edu.ar
Economy and Administration, Universidad Nacional de
Quilmes, Bernal, Buenos Aires, Argentina
Lee, Amy H. I. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-19, MD-37
amylee@chu.edu.tw
Department of Technology Management, Department of Industrial Management, Chung Hua University, Hsinchu, Taiwan
Lee, Andy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-22, HD-35
Andy.Lee@curtin.edu.au
Epidemiology and Biostatistics, Curtin University, Perth,
WA, Australia
Lee, Bokyung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-32
bokyunglee85@gmail.com
Yonsei university, Korea, Republic Of
Lee, Chungmok . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-35, MA-43
chungmok@gmail.com
IBM Research, Ireland, Ireland
Lee, Eva . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-28
eva.lee@isye.gatech.edu
Industrial and Systems Engineering, Georgia Institute of
358
Technology, Atlanta, GA, United States
Lee, Hong Tau . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-34, TE-43
leeht@ncut.edu.tw
Industrial Engineering and Management, National Chin-Yi
University of Technology, Taichung, Taiwan
Lee, Inseok . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-32
lston726@naver.com
Korea University, School of Industrial Management Engineering, Seoul, Korea, Republic Of
Lee, Jaewook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-42
jaewook@snu.ac.kr
Industrial Engineering, Seoul National University, Seoul, Korea, Republic Of
Lee, June Young . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-16
road2you@kisti.re.kr
Korea Institute of Science and Technology Information, Korea, Republic Of
Lee, Seungjae . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-04
sjlee@uos.ac.kr
Dept of Transportation Eng, University of Seoul, Seoul, Korea, Republic Of
Lee, Shinhae . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-04
newsun@si.re.kr
Transportation System, Seoul Institute, Seoul, Korea, Republic Of
Lee, William . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-10
William.Lee@ul.ie
University of Limerick, Limerick, Ireland
Lefèvre, Claude . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-24
clefevre@ulb.ac.be
ISRO, Université Libre de Bruxelles, Bruxelles, Belgium
Legros, Benjamin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-10
belegros@laposte.net
Génie Industriel, Ecole Centrale Paris, France
Lehrer, Ehud . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-24
lehrer@post.tau.ac.il
Tel Aviv University, Tel Aviv, Israel
Lehuédé, Fabien . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-04
fabien.lehuede@mines-nantes.fr
LUNAM Université, Ecole des Mines de Nantes, IRCCyN
UMR CNRS 6597, Nantes, France
Lei, Yong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-39
yong.lei@163.com
School of Electrical Engineering,Sichuan University, China
Leila, Younsi Née Abbaci . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-19
abbaci.leila@yahoo.fr
Technology, University, Bejaia, Algeria
Leitner, Markus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-31
markus.leitner@univie.ac.at
Department of Statistics and Operations Research, University
of Vienna, Vienna, Austria
Leitner, Stephan . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-44, MD-44
stephan.leitner@aau.at
Department of Controlling and Strategic Management,
Alpen-Adria-Universität Klagenfurt, Klagenfurt, Austria
Lejeune, Miguel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-31
IFORS 2014 - Barcelona
mlejeune@gwu.edu
Decision Sciences, George Washington University, Washington, DC, United States
Leleur, Steen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-44
sl@transport.dtu.dk
Department of Transport, Technical University of Denmark,
Kgs. Lyngby, Denmark
Lemarchand, Laurent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-12
Laurent.Lemarchand@univ-brest.fr
University of Brest, Brest, France
Lemay, Brian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-03
blemay@umich.edu
Industrial and Operations Engineering, University of Michigan, United States
Lemmens, Stef . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-06
stef.lemmens@kuleuven.be
Research Center for Operations Management, Katholieke
Universiteit Leuven, Leuven, Belgium
Leng, Mingming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-22
mmleng@ln.edu.hk
Computing and Decision Sciences, Lingnan University, Hong
Kong
Lengsfeld, Stephan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-43
lengsfeld@vwl.uni-freiburg.de
Finance and Accounting, University of Freiburg, Freiburg,
Germany
Lenz, Ralf . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-28
lenz@zib.de
Optimization, Zuse Institute Berlin, Berlin, Germany
Leon, Jorge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-18
leon@entc.tamu.edu
ETID and ISEN, Texas A&M University, College Station,
Texas, United States
Leopold-Wildburger, Ulrike . . . . . . . . . . . . . . . . . . . . . . . . . FA-29
ulrike.leopold@uni-graz.at
Statistics and Operations Research, Karl-FranzensUniversity, Graz, Austria
Leow, Mindy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-43
mindy.leow@ed.ac.uk
Business School, University of Edinburgh, Edinburgh, United
Kingdom
Lepki, Bengül . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-18
bengullepki@gmail.com
Industrial Engineering, Anadolu University, Turkey
Lepkova, Natalija . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-45
natalija.lepkova@vgtu.lt
Department of Construction Economics and Property Management, Vilnius Gediminas Technical University, Vilnius,
Lithuania
Leppänen, Ilkka . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-23
ilkka.j.leppanen@aalto.fi
Systems Analysis Laboratory, Aalto University, School of
Science, Espoo, Finland
Lera-Lopez, Fernando . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-41
lera@unavarra.es
Economics, Spanish National Open University (UNED),
Pamplona, Navarra, Spain
AUTHOR INDEX
Lerche, Nils . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-31
nils.lerche@wiwi.uni-goettingen.de
Chair of Production and Logistics, Georg-August-Universität
Göttingen, Germany
Lerida, Josep Lluis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-45
jlerida@diei.udl.cat
Computer Science, University of Lleida, Lleida, Catalunya,
Spain
Lesaja, Goran . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-14
goran@georgiasouthern.edu
Mathematical Sciences, Georgia Southern University, Statesboro, Georgia, United States
Leschik, Marius . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-28
marius.leschik@hsu-hh.de
Logistics Management, Helmut Schmidt University, Hamburg, Germany
Leslie, Andrew . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-34
andrew.leslie@asteronlife.co.nz
Asteron Life Ltd, Auckland, New Zealand
Leslie, David . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-24
david.leslie@bristol.ac.uk
School of Mathematics, University of Bristol, Bristol, -,
United Kingdom
Lessmann, Stefan . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-40, HE-40
lessmann@econ.uni-hamburg.de
Institute of Information Systems, University of Hamburg,
Hamburg, Germany
Letchford, Adam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-39
A.N.Letchford@lancaster.ac.uk
Department of Management Science, Lancaster University,
Lancaster, United Kingdom
Letifi, Nourdine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-34
n_letifi@yahoo.fr
THEMA, University of Cergy-Pontoise, Cergy-Pontoise,
France
Letmathe, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-08, HE-15
Peter.Letmathe@rwth-aachen.de
Faculty of Business and Economics, RWTH Aachen University, Aachen, Germany
Leung, Janny . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-22
janny@se.cuhk.edu.hk
Systems Engineering & Engineering Management Dept., The
Chinese University of Hong Kong, Shatin, Hong Kong
Levin, Asaf . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-39
levinas@ie.technion.ac.il
Industrial Engineering and Management, The Technion, Israel
Levin, Ilya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-41
ilia1@post.tau.ac.il
School of Education, Tel Aviv University, Tel Aviv, Israel
Levin, Yuri . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-15, TD-15, TD-27
ylevin@business.queensu.ca
School of Business, Queen’s University, Kingston, Ontario,
Canada
Levina, Tatsiana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-15
tlevin@business.queensu.ca
School of Business, Queen’s University, Kingston, Ontario,
Canada
359
AUTHOR INDEX
IFORS 2014 - Barcelona
Levit, Vadim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-17
levitv@ariel.ac.il
Computer Science and Mathematics, Ariel University, Ariel,
Israel
Leyer, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-15
m.leyer@fs.de
Management Department, Frankfurt School of Finance &
Management, Frankfurt a.M., Germany
Leyffer, Sven . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-17
leyffer@mcs.anl.gov
Argonne National Lab, Argonne, United States
Leyman, Pieter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-12
pieter.leyman@ugent.be
Faculty of Economics and Business Administration, Ghent
University, Ghent, Belgium
Leyva-Lopez, Juan Carlos . . . . . . . . . . . . . . . . . . . . . . . . . . ME-29
juan.leyva@udo.mx
Departamento de Ciencias Económico Administrativas, Universidad de Occidente, Culiacan, Sinaloa, Mexico
LHuillier, Gaston . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-25
glhuilli@gmail.com
Data Science, Groupon, Inc., Palo Alto, California, United
States
Li, Chengbo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-38
cb.riceu@gmail.com
Geophysical Technology, ConocoPhillips, Houston, Texas,
United States
Li, Duan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-29
dli@se.cuhk.edu.hk
Systems Engineering & Engineering Management Dept., The
Chinese University of Hong Kong, Shatin, NT, Hong Kong
Li, Feng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-19
fenglee@scut.edu.cn
Department of Industrial Engineeing, South China University
of Technology, Guangzhou, GuangDong, China
Li, Gendao . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-44
Gendao.li@beds.ac.uk
The Business School, University of bedfordshire, Luton,
United Kingdom
Li, Hongyan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-19
hojl@asb.dk
Department of Economics and Business, Business and Social
Science, Aarhus V, Denmark
Li, Jing-An . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-19
ajli@amss.ac.cn
MADIS, Institute of Systems Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences,
Beijing, China
LiQY@cardiff.ac.uk
Cardiff University, United Kingdom
Li, Ta-Hsin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-35
thl@us.ibm.com
IBM T. J. Watson Research Center, Yorktown Heights, NY,
United States
Li, Tao . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-41
tli1@scu.edu
Leavey School of Business - OMIS, Santa Clara University,
Santa Clara, CA, United States
Li, Xiangyong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-31
xyli@tongji.edu.cn
School of Economics and Management,Tongji University,
China
Li, Xiaoya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-02
xyli@amss.ac.cn
Institute of Applied Mathematics, Academy of Mathematics
and Systems Science, CAS, Beijing, China
Li, Xun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-29
malixun@polyu.edu.hk
Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong
Li, Xun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-32
xli26@uncc.edu
UNC Charlotte, United States
LI, Yan-Feng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-02
yanwaa@126.com
Department of Management Science, SouthWest Jiaotong
University, China, China
Li, Zhening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-16
zheningli@gmail.com
Department of Mathematics, University of Portsmouth,
Portsmouth, United Kingdom
Liao, Bo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-27
bo_liao@haas.berkeley.edu
Haas School of Business, University of California - Berkeley,
Berkeley, CA, United States
Liao, Feixiong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-32
f.liao@tue.nl
Urban planning group, TU/e, Eindhoven, Netherlands
Liberopoulos, George . . . . . . . . . . . . . . . . HE-09, HB-22, MA-42
glib@mie.uth.gr
Department of Mechanical Engineering, University of Thessaly, Volos, Magnesia, Greece
Liberti, Leo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-11
leoliberti@gmail.com
TJ Watson Research Center, IBM Research, Yorktown
Heights, NY, United States
Li, Ning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-37
84309809@qq.com
Applied Information Technology, The Kyoto College of
Graduate School for Informatics, Kyoto, Kyoto, Japan
Lidestam, Helene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-40
helene.lidestam@liu.se
Department of Management and Engineering, Production
economics, Linköping, Sweden
Li, Qingna . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-38
qnl@bit.edu.cn
School of Mathematics, Beijing Institute of Technology, Beijing, China
Lieder, Alexander . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-13
lieder@uni-mannheim.de
Chair of production management, University of Mannheim,
Mannheim, Germany
Li, Qinyun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-40
Liedtke, Gernot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-06
360
IFORS 2014 - Barcelona
liedtke@kit.edu
KIT Karlsruhe, Germany
Liers, Frauke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-11
frauke.liers@math.uni-erlangen.de
Department Mathematik, FAU Erlangen-Nuremberg, Erlangen, Germany
Liesiö, Juuso . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-31
juuso.liesio@aalto.fi
Systems Analysis Laboratory, Aalto University, Espoo, Finland
Lim, Chiehyeon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-23
arachon@postech.ac.kr
POSTECH, Korea, Republic Of
Lim, Junseok . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-42
kasia3302@gmail.com
Seoul National University, Korea, Republic Of
Lim, Yuchul . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-13
tmxhfl13@kaist.ac.kr
Industrial & System Engineering, KAIST, Korea, Republic
Of
Lima, Levi Adelino . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-31
levilima@joaosantos.com
Information Technology, Grupo João Santos, Recife, PE,
Brazil
Lima, Priscila . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-41
priscilamvl@gmail.com
iNCE, Universidade Federal do Rio de Janeiro, Rio de
Janeiro, RJ, Brazil
Limbourg, Sabine . . . . . . . . . . . . . . . . . . . . FA-19, HD-19, HA-21
sabine.limbourg@ulg.ac.be
HEC-Management School, University of Liège, Liege, Belgium
Lin, Chun Yu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-37
d09803006@cc.chu.edu.tw
Chung Hua University, Hsinchu, Taiwan
Lin, Congping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-12
c.lin@exeter.ac.uk
University of Exeter, Exeter, United Kingdom
Lin, Jian-Wei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-04
lianlih@yahoo.com.tw
Institute of Industrial Management, National Central University, Chung Li City, Taoyuan County, Taiwan
Lin, Ka Yuk Carrie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-39
mslincky@cityu.edu.hk
Dept. of Management Sciences, City University of Hong
Kong, Hong Kong, Hong Kong
Lin, Kuan-Min . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-44
k.lin1@lancaster.ac.uk
Management Science, Lancaster University, United Kingdom
AUTHOR INDEX
mari.paz.linares@upc.edu
Statistics and Operations Research, Universitat Politècnica
de Catalulunya - BarcelonaTECH, Barcelona, Spain
Linden, Isabelle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-42
isabelle.linden@unamur.be
Departement of Business Administration, University of Namur, Namur, Belgium
Lindorf, Christian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-28
c.lindorf@hsu-hh.de
Logistics Management, Helmut Schmidt University, Hamburg, Germany
Linker, Raphael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-25
linkerr@tx.technion.ac.il
The Technion - Israel Instiute of Technology, Haifa, Israel
Lino, M.Pilar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-12, MA-39
pilar.lino@uv.es
Mathematics for Economy, University of Valencia, Valencia,
Spain
Liou, James . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-37
jamesjhliou@gmail.com
Industrial Engineering and Management, National Taipei
University of Technology, Taipei, Taiwan
Lisboa, Adriano . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-14
adriano.lisboa@enacom.com.br
ENACOM - Handcrafted Technologies, Belo Horizonte, Minas Gerais, Brazil
Listes, Ovidiu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-44
o.listes@aimms.com
AIMMS, Haarlem, Netherlands
Litvinchev, Igor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-21
igorlitvinchev@gmail.com
Universidad Autónoma de Nuevo León, San Nicolás de los
Garza, Nuevo León, Mexico
Liu, Degang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-32
dliu@amt.ac.cn
Academy of Mathematics & Systems Science, Chinese
Academy of Sciences, Beijing, Beijing, China
Liu, De . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-15
de.liu@uky.edu
University of Kentucky, Lexington, United States
Liu, Fang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-27
fangliu.hfut@gmail.com
School of Management, Hefei University of Technology,
Hefei, China
Liu, Fang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-04
liu_fang@ntu.edu.sg
Nanyang Business School, Nanyang Technological University, Singapore, Singapore
Lin, Sifeng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-15
sifenglin@utexas.edu
University of Texas at Austin, Austin, TX, United States
Liu, Gang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-04
liugang1109@126.com
Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology,
Changsha, China
Lin, Yi-Chin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-06
yichinl@andrew.cmu.edu
Carnegie Mellon University, Pittsburgh, PA, United States
Liu, Jiangxia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-44, HB-44
liujxia@gmail.com
Gannon University, Erie, United States
Linares, Ma Paz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-04
Liu, Jiyin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-04
361
AUTHOR INDEX
IFORS 2014 - Barcelona
j.y.liu@lboro.ac.uk
School of Business and Economics, Loughborough University, Loughborough, Leicestershire, United Kingdom
mac_lic@yahoo.com
FIME, UANL, San Nicolas de los Garza, Nuevo Leon, Mexico
Liu, Jiyin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-20
jyliu@tli.neu.edu.cn
The Logistics Institute, Northeastern University, Shenyang,
China
Ljubic, Ivana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-31, HE-31
ivana.ljubic@univie.ac.at
Department of Statistics and Operations Research, University
of Vienna, Vienna, Austria
Liu, Ke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-37
kliu@amss.ac.cn
Operations Reserach, Institute of Appiled Math. AMSS,
CAS, Beijing, China
Llanes, Myrna . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-20
myrnabellanes@yahoo.com
ALTERPLAN, Quezon City, Philippines
Liu, Qian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-15
qianliu@ust.hk
IELM, HKUST, Hong Kong
Liu, Sam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-23
liusming@gmail.com
BA, National Central University, Jhongli City, , Taoyuan
County, Taiwan
Liu, Sanming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-38
liusanmingxyx@163.com
Department of Mathematics and Physics, Shanghai Dianji
University, Shanghai, Shanghai, China
Liu, Shaofeng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-42
shaofeng.liu@plymouth.ac.uk
Graduate School of Management, University of Plymouth,
Plymouth, United Kingdom
Liu, Shiang-Tai . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-26
stliu@vnu.edu.tw
Graduate School of Business & Management, Vanung University, Tao-Yuan, Taiwan
Liu, Shih-Wen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-27
liushihwen@gmail.com
Department of Industrial Management, National Taiwan University of Science and Technology, Taipei, Taiwan
Liu, Shih-Ya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-40
a8750057@hotmail.com
Chung Yuan Christian University, Taiwan
Liu, Shuang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-32
shuang.liu@csiro.au
CSIRO, Australia
Liu, Xiang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-05
liu94@illinois.edu
University of Illinois at Urbana-Champaign, Urbana, Illinois,
United States
Liu, Yifan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-45
yifanl@usc.edu
University of Southern California, Los Angeles, United
States
Liu, Zhaohui . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-39
zhliu@ecust.edu.cn
Mathematics, East China University of Science and Technology, Shanghai, China
Liu, Zhengliang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-44
e.liu2@lancaster.ac.uk
Management Science, Lancaster Univerisity, Lancaster, Lancashire, United Kingdom
Lizarraga, Giovanni . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-13
362
Lodi, Andrea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-11
andrea.lodi@unibo.it
D.E.I.S., University of Bologna, Bologna, Italy
Loeffler, Andreas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-30
al@wacc.de
Banking and Finance, Freie Universität Berlin, Berlin, Germany
Löhndorf, Nils . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-20
nils.loehndorf@wu.ac.at
Vienna University of Economics and Business, Wien, Austria
Loiseau, Irene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-02, HB-31
irene@dc.uba.ar
Departamento de Computación-, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires,
Argentina
Lokman, Banu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-18
banu.lokman@tedu.edu.tr
Industrial Engineering Department, TED University, Ankara,
Turkey
Lombardi, Patrizia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-08
patrizia.lombardi@polito.it
Casa-Città Department, Polytechnic of Turin, Turin, Italy
Long, Elisa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-06
elisa.long@anderson.ucla.edu
Anderson School of Management, UCLA, Los Angeles, California, United States
Lopes, Isabel Cristina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-01
cristinalopes@eu.ipp.pt
Dep. Mathematics, UNIAG, ESEIG - Polytechnic Institute of
Porto, Minho University, Vila do Conde, Portugal, Portugal
Lopes, Leo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-21, TB-25
Leo.Lopes@sas.com
SAS Institute, Cary, North Carolina, United States
Lopes, Luiz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-14
llopes@porto.ucp.pt
Universidade Católica Portuguesa no Porto, Porto, Portugal
Lopes, Manuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-21
mpl@isep.ipp.pt
School of Engineering, Polytechnic Institute of Porto, Porto,
Portugal
Lopes, Maria do Carmo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-39
mclopes@ipocoimbra.min-saude.pt
Ipoc-fg, Epe, Coimbra, Portugal
Lopes, Marta . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-38
mlopes@esac.pt
INESC Coimbra, ESAC-IPC, Coimbra, Portugal
IFORS 2014 - Barcelona
Lopes, Mário . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-41
lgrrf1@gmail.com
Faculty of Engineering of Porto University, Porto, Portugal
Lopez, Pierre . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-08
pierre.lopez@laas.fr
ROC, LAAS-CNRS, Toulouse, France
Lopez, Ruben . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-17
rlopez@ucsc.cl
Departamento de Matematica y Fisica Aplicadas (DMFA),
Universidad Catolica de la Santisima Concepcion, Concepcion, VIII Region, Chile
Lopez-Codina, Daniel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-41
daniel.lopez-codina@upc.edu
Física i enginyeria nuclear, School of Agricultural Engineering of Barcelona, The Technical University of Catalonia,
Castelldefels, Catalonia, Spain
Lopez-Paredes, Adolfo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-12
insisoc@gmail.com
INSISOC, University of Valladolid, Valladolid, Spain, Spain
Lopez-Ramos, Francisco . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-01
francisco.lopez.r@ucv.cl
School of Transportation Engineering, Pontificia Universidad
Católica de Valparaiso, Valparaiso, Valparaiso, Chile
Lorena, Luiz A. N. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-06
lorena@lac.inpe.br
LAC - Lab. Assoc. Computação e Mat. Aplicada, INPE Brazilian Space Research Institute, São José dos Campos,
São Paulo, Brazil
Lorenz, Ulf . . . . . . . . . . . . . . . . . . . . . . . . . . FA-08, TB-21, MA-43
ulf.lorenz@fst.tu-darmstadt.de
Chair of Fluid Systems, Technische Universität Darmstadt,
Darmstadt, Germany
Lotero, Irene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-29
iloteroh@andrew.cmu.edu
Chemical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Lotero, Laura . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-27
llotero0@unal.edu.co
Ciencias de la computación y de la decisión, Universidad
Nacional de Colombia, Medellin, Antioquia, Colombia
Loukil, Taicir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-14
Taicir.Loukil@fsegs.rnu.tn
Faculté des Sciences Economiques et de Gestion, Sfax,
Tunisia
Love, Ernie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-35
love@sfu.ca
Segal Graduate School of Business, Simon Fraser University,
Vancouver, British Columbia, Canada
Lovison, Alberto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-18
lovison@math.unipd.it
Dipartimento di Metodi e Modelli Matematici, Università
degli Studi di Padova, Padova, Italy
AUTHOR INDEX
Lu, Xiwen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-13
xwlu@ecust.edu.cn
Dept. of Math, East China University of Science & Technology, Shanghai, China
Lu, Yang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-04
yanglu@umd.edu
Department of Civil & Environmental Engineering, University of Maryland, College Park, Maryland, United States
Lu, Zhipeng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-11, HB-40
zhipeng.lui@gmail.com
Computer Science, Huazhong University of Science and
Technology, Wuhan, Hubei, China
Lübbecke, Marco . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-11, HA-39
marco.luebbecke@rwth-aachen.de
Operations Research, RWTH Aachen University, Aachen,
Germany
Lubis, Asrin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-17
lubis.asrin@yahoo.com
Mathematics, Unimed/Graduate School of Mathematics,
University of Sumatera Utara, Medan, Sumatra Utara, Indonesia
Lüer-Villagra, Armin . . . . . . . . . . . . . . . . . . . . . . . . TE-02, HD-03
arminluer@gmail.com
Electrical Engineering, Pontificia Universidad Católica de
Chile, Santiago, Select, Chile
Luh, Hsing Paul . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-26
slu@nccu.edu.tw
Dept. of Mathematical Sciences, National Chengchi University, Taipei, Taiwan
Luhandjula, Monga K . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-26
luhanmk@unisa.ac.za
Decision Sciences, University of South Africa, Pretoria,
Gauteng, South Africa
Lühn, Tobias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-31
tobias.luehn@wiwi.uni-goettingen.de
Chair of Production and Logistics, University of Goettingen,
Germany
Luig, Klaus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-14
luig@cognitec.com
Cognitec Systems GmbH, Dresden, Germany
Lukac, Zrinka . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-32
zlukac@efzg.hr
Faculty of Economics - Zagreb, Zagreb, Croatia
Lukas, Elmar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-08
elmar.lukas@ovgu.de
Faculty of Economics and Management, LS Financial
Management and Innovation Finance, Otto-von-GuerickeUniversity of Magdeburg, Magdeburg, Germany
Lukáčik, Martin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-15
martin.lukacik@euba.sk
University of Economics in Bratislava, Bratislava, Slovakia
Lu, Cheng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-17
c-lu06@mails.tsinghua.edu.cn
Electronic Engineering, Tsinghua University, Beijing, China
Lukáčiková, Adriana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-15
adriana.lukacikova@euba.sk
University of Economics in Bratislava, Slovakia
Lu, Meng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-15
mlu9901@hotmail.com
City University of Hong Kong, Hong Kong, Hong Kong
Lukszo, Zofia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-20
z.lukszo@tudelft.nl
Energy and Industry, Delft University of Technology, Delft,
363
AUTHOR INDEX
IFORS 2014 - Barcelona
Zuid Holland, Netherlands
Lumbreras, Sara . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-10
sara.lumbreras@iit.upcomillas.es
Institute for Research in Technology, Universidad Pontificia
Comillas, Madrid, Madrid, Spain
Luna, Henrique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-02
hpluna@gmail.com
Instituto de Computação, Universidade Federal de Alagoas,
Maceio, Alagoas, Brazil
Luna-Mota, Carlos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-40
carlos.luna-mota@upc.edu
Statistics and Operation Research, Universitat Politècnica de
Catalunya - BarcelonaTech, Barcelona, Barcelona, Spain
Lundy, Michele . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-37
michele.lundy@port.ac.uk
Business School, University of Portsmouth, United Kingdom
Luo, Jiabin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-26
jiabin.luo@coventry.ac.uk
Faculty of Engineering and Computing, Coventry University,
Coventry, United Kingdom
Luo, Li . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-39
luolicc@163.com
Industry Engineering, Sichuan University, Chengdu, Sichuan
Province, China
Luo, Sirong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-27
luo.sirong@mail.shufe.edu.cn
School of Statistics and Management, Shanghai University
of Finance and Economics, Shanghai, China
Luo, Ziyan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-38
zyluo@bjtu.edu.cn
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China
Lupia, Benedetta . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-22
benedetta.lupia@libero.it
Università degli Studi di Padova, Padova, Italy
Lutter, Pascal. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-01, ME-39
pascal.lutter@rub.de
Fac. of Management and Economics, Ruhr University
Bochum, Bochum, Germany
Lyra Filho, Christiano . . . . . . . . . . . . . . . . . . . . . . . FB-09, HE-28
chrlyra@densis.fee.unicamp.br
Sistemas e Energia, Universidade Estadual de Campinas,
Campinas, SP, Brazil
Ma, Li-Ching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-45
lcma@nuu.edu.tw
Department of Information Management, National United
University, Miaoli, Taiwan, Taiwan
Ma, Shiqian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-38
sqma@se.cuhk.edu.hk
Systems Engineering and Engineering Management, The
Chinese University of Hong Kong, Hong Kong
Maachou, Nacera . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-39
nacera_maachou@yahoo.fr
OR, USTHB, Bab Ezzouar, Algiers, Algeria
Maag, Volker . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-18
maag@itwm.fhg.de
Optimization,
Fraunhofer-Institut für Techno- und
Wirtschaftsmathematik, Kaiserslautern, Germany
Macharis, Cathy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-37
Cathy.Macharis@vub.ac.be
BUTO-MOBI, Vrije Universiteit Brussel, Brussels, Belgium
Machowiak, Maciej . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-13
maciej.machowiak@cs.put.poznan.pl
Institute of Computing Science, Poznan University of Technology, Poland
Maculan, Nelson . . . . . . . . . . . . . . . . . . . . . FB-11, HE-11, MA-17
maculan@cos.ufrj.br
Ufrj-coppe / Pesc, Universidade Federal do Rio de Janeiro,
Rio de Janeiro, RJ, Brazil
Lüpke, Lars . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-35
lars.luepke@uni-bielefeld.de
Department of Business Administration and Economics,
Bielefeld University, Bielefeld, Germany
Madaeva, Elena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-07
bit-bit_007@mail.ru
Applied mathematics, East Siberia State University of Technology and Management, Ulan-Ude, Republic of Buryatia,
Russian Federation
Luque, Mariano . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-18
mluque@uma.es
Applied Economics (Mathematics), University of Malaga,
Malaga, Spain
Maddah, Bacel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-19
bm05@aub.edu.lb
Engineering Management, American University of Beirut,
Beirut, Lebanon
Lurz, Kristina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-21
lurz.kristina@gmail.com
University of Würzburg, Germany
Madenoğlu, Fatma Selen . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-12
selen.madenoglu@deu.edu.tr
Department of Industrial Engineering, Dokuz Eylül University, Faculty of Engineering, Izmir, Turkey, Izmir, Turkey
Lusa, Amaia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-44
amaia.lusa@upc.edu
IOC Research Institute / Management Department, Universitat Politècnica de Catalunya, Barcelona, Spain
Lusby, Richard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-01
rmlu@man.dtu.dk
Department of Management Engineering, Technical University of Denmark, Kgs Lyngby, Denmark
Lustosa, Leonardo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-03
leonardo.lustosa@gmail.com
Independent Consultant, Rio de Janeiro, RJ, Brazil
364
Madlener, Reinhard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-34
rmadlener@eonerc.rwth-aachen.de
School of Business and Economics / E.ON Energy Research
Center, RWTH Aachen University, Aachen, Germany
Madsen, Henrik. . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-07, HA-09
hmad@dtu.dk
Applied Mathematics and Computer Science, Technical University of Denmark, Kgs. Lyngby, Denmark
Madureira, Andre . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-10
andre.g.madureira@inescporto.pt
IFORS 2014 - Barcelona
INESC Porto, Portugal
Maenhout, Broos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-12
Broos.Maenhout@Ugent.be
Business Informatics and Operations Management, Ghent
University, Gent, Belgium
Magagnotti, Mariah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-40
mariahm@clemson.edu
Industrial Engineering, Clemson University, Clemson, SC,
United States
Magbagbeola, Joshua . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-28
kunle_magbagbeola@yahoo.com
Dept. of Actuarial Science and Insurance, Joseph Ayo Babalola University, Ikeji-Arakeji, Osun State, Nigeria
Mageirou, Evangelos F. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-05
efm@aueb.gr
Informatics, Athens University of Economics, Athens,
Greece
Maggioni, Francesca . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-45
francesca.maggioni@unibg.it
Department of Management, Economics and Quantitative
Methods, University of Bergamo, Bergamo, Italy, Italy
Magnusson, Johan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-44
Johan.magnusson@handels.gu.se
Dept. of Business Administration, University of Goteborg,
Gothenburg, Sweden
Magos, Dimitrios . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-12, MD-12
dmagos@teiath.gr
Informatics, Technological Educational Institute of Athens,
Greece
Maher, Stephen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-03
maher@zib.de
Zuse Institute Berlin, Berlin, Germany
Maier, Thomas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-33
thomas.maier@era-gmbh.at
ERA Elektro Recycling Austria GmbH, Vienna, Austria
Maisiuk, Yauhen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-05
yauhen.maisiuk@himolde.no
Faculty of Economics, Informatics, and Social Sciences,
Molde University College - Specialized University in Logistics, Molde, Norway
Maknoon, Mohammad Yousef . . . . . . . . . . . . . . . . TD-02, TE-02
mohammad-yousef.maknoon@polymtl.ca
Mathematics and Industrial Engineering, Polytechnique
Montreal, Canada
Makojevic, Nikola . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-29
nmakojevic@kg.ac.rs
University of Kragujevac, Faculty of Economics, Kragujevac,
Serbia
Makui, Ahmad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-07
amakui@iust.ac.ir
Iran University of Science and Technology, Tehran, Iran, Islamic Republic Of
Maldonado, Michelli . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-41
michellimaldo@gmail.com
UNESP - Sao Paulo State University, SJ do Rio Preto, Sp,
Brazil
Maldonado, Sebastian . . . . . . . . . . . . . . . . . . . . . . . MA-20, HB-25
AUTHOR INDEX
smaldonado@uandes.cl
School of Engineering and Applied Sciences, Universidad de
los Andes, Santiago, Chile
Malekian, Azarakhsh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-06
azarakhsh.malekian@rotman.utoronto.ca
Rotman School of Business, University of Toronto, Toronto,
ON, Canada
Malerud, Stein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-33
sma@ffi.no
Norwegian Defence Research Establishment, Kjeller, Norway
Malhotra, Rahul . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-22
rahulmalhotra0312@gmail.com
Indian Institute of Technology (IIT), Delhi, India
Malitskaia, Yulia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-32
ymalitskaia@gmail.com
University College Cork, Ireland
Malladi, Krishna Teja . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-02
kmalladi@sfu.ca
Simon Fraser University, Surrey, BC, Canada
Mallozzi, Lina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-30
mallozzi@unina.it
Matematica e Applicazioni, Università di Napoli Federico II,
Napoli, Italy
Malo, Pekka . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-18
pekka.malo@aalto.fi
Information and Service Economy, Aalto University School
of Economics, Helsinki, Finland
Maltempi, Emanuele . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-09
emanuele.maltempi@mercatienergetici.org
Gestore dei Mercati Energetici S.p.A, Roma, Italy
Malyutin, Sergey . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-13, HE-13
sergey.malyutin@emse.fr
EMSE, St Etienne, France
Mamasis, Konstaninos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-44
k.mamassis@fme.aegean.gr
Financial and Management Engineering, University of the
Aegean, Chios, Greece
Mancini, Simona . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-11
simona.mancini@polito.it
Department of Computer Sciences and Automatic Control,
Politecnico di Torino, Torino, Italy
Mandel, Alexander . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-13
almandel@yandex.ru
Lab 44, Ics Ras, Moscow, Russia, Russian Federation
Mandrescu, Eugen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-17
eugen_m@hit.ac.il
Computer Science, Holon Institute of Technology, Holon,
Israel
Manerba, Daniele . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-02
daniele.manerba@unibs.it
Dept. of Information Engineering, University of Brescia,
Brescia, BS, Italy
Mangaraj, Bijaya Krushna . . . . . . . . . . . . . . . . . . . . . . . . . MD-20
mangaraj@xlri.ac.in
Production, Operations and Decision Sciences Area, XLRIXavier School of Management, Jamshedpur, Jharkhand, India
365
AUTHOR INDEX
IFORS 2014 - Barcelona
Mangelsdorf, André . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-27
andre.mangelsdorf@ovgu.de
Strategic Management and Organisation, Otto-von-GuerickeUniversität Magdeburg, Magdeburg, Germany
Manger, Robert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-11
manger@math.hr
Department of Mathematics, University of Zagreb, Zagreb,
Croatia
Mani, Vidya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-19
vmani@psu.edu
Penn State, University Park, United States
Mankowska, Dorota Slawa . . . . . . . . . . . . . . . . . . . . . . . . . . HA-02
dorota.mankowska@wiwi.uni-halle.de
Martin-Luther-University Halle-Wittenberg, Halle, Germany
Mannino, Carlo . . . . . . . . . . . . . . . . . . . . . MB-01, MB-03, HA-27
Carlo.Mannino@sintef.no
SINTEF, Oslo, Norway
Manshadi, Vahideh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-06
manshadi@mit.edu
MIT, Cambridge, MA, United States
Mansini, Renata . . . . . . . . . . . . . HB-02, ME-02, MA-11, MB-36
rmansini@ing.unibs.it
Department of Information Engineering, University of Brescia, Brescia, Italy
Mao, Mei-Chun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-45
it@www.cust.edu.tw
Graduate School of Business and Management, China University of Science Technology, Taipei, Taiwan
Mar Molinero, Cecilio. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-42
C.Mar-molinero@kent.ac.uk
Kent Business School, Canterbury, United Kingdom
Marí, Laura . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-10
laura.mari@upc.edu
Statistics and Operations Research, Univ. Politecnica de
Catalunya, Barcelona, Spain
Marín, Ángel . . . . . . . . . . FA-01, HA-01, ME-01, TA-01, MD-03
angel.marin@upm.es
Matemática Aplicada y Estadística, Universidad Politécnica
de Madrid, Madrid, Madrid, Spain
Marín, Alfredo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-03, HB-03
amarin@um.es
Departamento de Estadística e Investigación Operativa, University of Murcia, Murcia, Spain
Marchese, Mario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-31
mario.marchese@unige.it
University of Genoa, Italy
Marcotte, Patrice. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-15
marcotte@iro.umontreal.ca
DIRO, Université de Montréal, Montréal, Québec, Canada
Marecek, Jakub . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-16, FA-35
jakub.marecek@ie.ibm.com
IBM Research Dublin, Dublin 15, Ireland
Marenco, Javier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-35
jmarenco@dc.uba.ar
UBA, Buenos Aires, Argentina
366
Mareschal, Bertrand . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-29
bmaresc@ulb.ac.be
Solvay Brussels School of Economics and Management, Université Libre de Bruxelles, Brussels, Belgium
Marianov, Vladimir . . . . . . . . . . . . . . . . . . . . . . . . . TE-02, HD-03
marianov@ing.puc.cl
Electrical Engineering, Pontificia Universidad Catolica de
Chile, Santiago, Chile
Marinaki, Magdalene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-02
magda@dssl.tuc.gr
Production Engineering and Management, Technical University of Crete, Chania, Greece
Marinakis, Yannis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-02
marinakis@ergasya.tuc.gr
Production Engineering and Management, Technical University of Crete, Chania, Crete, Greece
Marinakos, Georgios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-43
george.marinakos@yahoo.com
Electrical and Computer Engineering, University of Patras,
Patras, Greece
Marinescu, Radu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-43
radu.marinescu@ie.ibm.com
IBM Research, Ireland
Marinescu-Ghemeci, Ruxandra . . . . . . . . . . . . . . . . . . . . . MA-12
verman@fmi.unibuc.ro
Computer Science, University of Bucharest, Romania
Marinovic, Minja . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-34
marinovic.minja@fon.bg.ac.rs
Laboratory for Operational Research "Jovan Petrić", University of Belgrade, Faculty of Organizational Sciences, Belgrade, Serbia
Markakis, Evangelos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-22
markakis@gmail.com
Department of Informatics, Athens University of Economics
and Business, Athens, Greece
Marla, Lavanya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-31
lavanyam@illinois.edu
Department of Industrial and Enterprise Systems Engineering, University of Illinois at Urbana-Champaign, Urbana, IL,
United States
Marlière, Grégory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-01
gregory.marliere@ifsttar.fr
IFSTTAR, Lille, France
Marmion, Marie-Éléonore . . . . . . . . . . . . . . . . . . . . . . . . . . HD-33
marie-eleonore.marmion@univ-lille1.fr
Université Lille 1, Villeneuve d Ascq, France
Maros, István . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-21, HE-33
maros@dcs.uni-pannon.hu
Department of Computer Science and Systems Technology,
University of Pannonia, Veszprém, Hungary
Maroti, Gabor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-01
g.maroti@vu.nl
Logistics, Innovation and Information, VU University Amsterdam, Amsterdam, Netherlands
Maroto, Concepcion . . . . . . . . . . . . . . . . . . . . . . . . . HA-36, TE-36
cmaroto@eio.upv.es
Applied Statistics, Operations Research and Quality, Universitat Politecnica de Valencia, Valencia, Spain
IFORS 2014 - Barcelona
Marqués, Inmaculada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-36
imarques@esp.upv.es
Economía y Ciencias Sociales, Universidad Politécnica de
Valencia, Spain
Marques de Sousa, José Jefferson . . . . . . . . . . . . . . . . . . . . HE-42
marques.jefferson805@gmail.com
Contabilidade, FIS- Faculdade de Integração do Sertão, Serra
Talhada, Pernambuco, Brazil
Marques Testa, Christina . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-10
christina.testa.marques@gmail.com
Engenharia Elétrica, UFU, Uberlândia, Minas Gerais, Brazil
AUTHOR INDEX
Rafael.Marti@uv.es
Departamento de Estadística e Investigación Operativa, Universitat de València, Valencia, Valencia, Spain
Martin, Alexander . . . . . . . . . . . . . . . . . . . . . . . . . . MA-01, HA-39
alexander.martin@math.uni-erlangen.de
Mathematics, FAU Erlangen-Nürnberg, Discrete Optimization, Erlangen, Germany
Martin, Sebastian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-07
sebastian.ii05@gmail.com
Department of Electrical Engineering, University of Malaga,
Malaga, Spain
Marques, Alexandra . . . . . . . . . . . . . . . . . HE-36, MB-36, ME-36
alexandra.s.marques@inescporto.pt
UESP, Inesc Tec, Porto, Portugal
Martin-Campo, F. Javier . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-28
javier.martin.campo@ccee.ucm.es
Estadistica e Investigacion Operativa II, Universidad Complutense de Madrid, Pozuelo de Alarcón (Madrid), Spain
Marques, Joan Manuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-41
jmarquesp@uoc.edu
Computer Sciences Studies, Universitat Oberta de Catalunya,
Barcelona, Catalunya, Spain
Martinez Sykora, Antonio . . . . . . . . . . . . . . . . . . . HB-02, HA-21
A.Martinez-Sykora@soton.ac.uk
Management School, University of Southampton, Southampton, United Kingdom
Marques, Pedro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-31
pedro.marques@dem.uc.pt
ADAI-LAETA, University of Coimbra, Coimbra, Portugal
Martinez, Carlos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-45
cemartinez@unq.edu.ar
Economy and Administration, Universidad Nacional de
Quilmes, Bernal, Buenos Aires, Argentina
Marquez, Leorey . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-08, MD-20
leorey.marquez@csiro.au
Computational Informatics, CSIRO, Clayton, Vic, Australia
Marquez, Maria Cherilyn . . . . . . . . . . . . . . . . . . . . . . . . . . MD-08
cherrymarquez@y7mail.com
University of Melbourne, Victoria, Australia
Martín, Jacinto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-35
jrmartin@unex.es
Mathematics, Universidad de Extremadura, Badajoz, Badajoz, Spain
Martínez de Albéniz, Victor . . . . . . . . . . . . . . . . . . TD-22, TE-22
valbeniz@iese.edu
IESE Business School, Barcelona, Spain
Martínez Gamboa, Jeyson Andrés . . . . . . . . . . . . . . . . . . . ME-42
je-i-sson92@hotmail.com
Ingeniería Industrial, Universidad Libre, Bogotá, Colombia
Martínez, María Luisa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-26
mmartinezcespedes@gmail.com
Universidad Politécnica de Madrid, Spain
Martínez-Gavara, Anna . . . . . . . . . . . . . . . . . . . . . . TD-40, TB-45
gavara@uv.es
Estadística i Investigació Operativa, Universitat de València,
Burjassot, Valencia, Spain
Martell, David . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-36, TB-36
david.martell@utoronto.ca
Faculty of Forestry, University of Toronto, Toronto, Ontario,
Canada
Martinez, Janis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-21
jamartinezm@pucp.pe
Pontificia Universidad Católica del Perú, Lima, Peru
Martins, Nelson . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-38
nmartins@ua.pt
Mech. Eng., University of Aveiro, Aveiro, Aveiro, Portugal
Martins, Pedro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-32, HB-40
pmartins@iscac.pt
ISCAC, Polytechnic Institute of Coimbra and Operations Research Center, Coimbra, Portugal
Martins, Sara . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-04
gei09095@fe.up.pt
INESC, Portugal
Martins, Thiago . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-21
thiago@usp.br
University of Sao Paulo, Sao Paulo, Brazil
Martonosi, Susan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-36
martonosi@math.hmc.edu
Mathematics Dept., Harvey Mudd College, Claremont, CA,
United States
Martzoukos, Spiros . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-43
baspiros@ucy.ac.cy
Cyprus
Maruyama, Toru . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-35
maruyama@econ.keio.ac.jp
Economics, Keio University, minatoku,mita, Tokyo, Japan
Martello, Silvano . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-11
silvano.martello@unibo.it
DEIS, University of Bologna, Bologna, Italy
Maruyama, Yukihiro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-09
maruyama@nagasaki-u.ac.jp
General Economics, Nagasaki University, Nagasaki, Japan
Marthinussen, Elin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-33
ema@ffi.no
Norwegian Defence Research Establishment, Norway
Maschietto, Gabriela Naves . . . . . . . . . . . . . . . . . . . . . . . . . TD-13
gabriela.maschietto@gmail.com
UFMG, Brazil
Marti, Rafael . . . . . . . . . . . . . . . . . . . . . . . . . TB-37, TD-40, TB-45
Mascia, Franco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-33
367
AUTHOR INDEX
IFORS 2014 - Barcelona
fmascia@ulb.ac.be
IRIDIA, Université libre de Bruxelles, Brussels, Belgium
Mason, Andrew J . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-30
a.mason@auckland.ac.nz
Dept Engineering Science, University of Auckland, Auckland, New Zealand
Mason, Andrew . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-37
anmason@asu.edu
School of Computing, Informatics, and Decision Systems
Engineering, Arizona State University, Tempe, AZ, United
States
Mason, Scott . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-40
mason@clemson.edu
Industrial Engineering, Clemson University, Clemson, SC,
United States
Masruroh, Nur. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-33
aini@ugm.ac.id
Mechanical and Industrial Engineering, Universitas Gadjah
Mada, Indonesia
Massacci, Fabio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-31
Fabio.Massacci@unitn.it
Department of Information Engineering and Computer Science, University of Trento, Trento, TN, Italy
Massol, Olivier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-07
olivier.massol@ifpen.fr
Center for Economics and Management, IFP School, RueilMalmaison, France
Masuda, Yasushi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-35
masuda@ae.keio.ac.jp
Faculty of Science and Tech, Keio University, Yokohama,
Japan
Mateo, Jordi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-45
jmateo@diei.udl.cat
Computer Science, University of Lleida, Lleida, Catalunya,
Spain
Mateo, Manuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-41
manel.mateo@upc.edu
Departament Business Administration, Universitat Politecnica Catalunya, Barcelona, Spain
Mateos, Alfonso . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-31
amateos@fi.upm.es
Inteligencia Artificial, Technical University of Madrid, Boadilla del Monte, Madrid, Spain
Mathelinea, Devy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-17
whitec4t_93@yahoo.com
Mathematics, University Sains Malaysia, Indonesia
Mathews, Kusum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-06
kusum.mathews@mssm.edu
Pulmonary, Critical Care & Sleep Medicine, Icahn School of
Medicine at Mount Sinai, United States
Matos Dias, Joana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-39
joana@fe.uc.pt
Univ Coimbra - FEUC, Inesc Coimbra, Coimbra, Portugal
Matos, Henrique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-44
henrimatos@ist.utl.pt
IST, Lisboa, Portugal
Matrosov, Mikhail . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-16
mikhail.matrosov@skolkovotech.ru
Department of Control and Applied Math, MIPT, Moscow,
Russian Federation
Matsatsinis, Nikolaos . . . . . . . . . . . . . . . . . . . . . . . . . TA-29, TE-29
nikos@ergasya.tuc.gr
Department of Production Engineering and Management,
Technical University of Crete, Chania, Greece
Matsui, Tomomi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-09
matsui.t.af@m.titech.ac.jp
Department of Social Engineering, Tokyo Institute of Technology, Tokyo, Japan
Matsui, Yasuko . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-09
yasuko@tokai-u.jp
Mathematical Sciences, Tokai University, Hiratsuka-shi,
Kanagawa, Japan
Matsypura, Dmytro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-31
d.matsypura@econ.usyd.edu.au
Discipline of Business Analytics, Business School, The University of Sydney, Sydney, NSW, Australia
Matta, Andrea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-11
andrea.matta@polimi.it
Politecnico di Milano, Milano, MI, Italy
Matthews, Jason . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-11
14855054@sun.ac.za
Department of Logistics, University of Stellenbosch, South
Africa
Mattia, Sara . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-11
sara.mattia@iasi.cnr.it
Istituto di Analisi dei Sistemi ed Informatica, Consiglio
Nazionale delle Ricerche, Roma, Italy
Maturana, Sergio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-40
smaturan@ing.puc.cl
Ingenieria Industrial y de Sistemas, P. Universidad Catolica
de Chile, Santiago, Chile
Matusiak, Marek . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-04
marek.matusiak@aalto.fi
Automation and Systems Technology, Aalto University, Espoo, Finland
Matuszyk, Anna . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-30, HD-34
amatuszyk@matuszyk.com
Institute of Finance, Warsaw School of Economics, Warsaw,
Poland
Matias, João . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-26
j_matias@utad.pt
Mathematics, CM-UTAD, Vila Real, Vila Real, Portugal
Mauricio, David . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-45
dms_research@yahoo.com
Computer Science - FISI, National San Marcos University,
Lima, Lima, Peru
Matko, Marusa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-42
marusa.matko@ijs.si
Environmental Sciences, Jozef Stefan Institute, Ljubljana,
Slovenia
Mauricio, De Souza . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-13
mauricio.souza@pq.cnpq.br
Departamento de Engenharia de Produção, Universidade
Federal de Minas Gerais, Belo Horizonte, Brazil
368
IFORS 2014 - Barcelona
Mauricio, Matheus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-14
matheusgaruti@gmail.com
State University of Campinas, LIMEIRA, Sao Paulo, Brazil
Maurovich-Horvat, Lajos . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-10
l.horvat@ucl.ac.uk
University College London, London, – Please Select (only
U.S. / Can / Aus), United Kingdom
Mavri, Maria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-32
m.mavri@ba.aegean.gr
Business Administration, University of the Aegean, Chios,
Greece
Mavrotas, George . . . . . . . . . . . . . . . . . . . . TB-18, TB-31, HD-42
mavrotas@chemeng.ntua.gr
Chemical Engineering, National technical University of
Athens, Athens, Greece
Mawengkang, Herman . . . . . . . . . . . . . . MB-17, MD-17, ME-17
mawengkang@usu.ac.id
Mathematics, The University of Sumatera Utara, Medan, Indonesia
Maximov, Yury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-16
yury.maximov@phystech.edu
Laboratory of structural methods of data analysis in predictive modeling, Moscow Institute of Physics and Technology,
Moscow, Moscow, Russian Federation
May, Jerrold . . . . . . . . . . . . . . . . . . . . . . . . . TE-06, HE-19, ME-32
jerrymay@katz.pitt.edu
KGSB, University of Pittsburgh, Pittsburgh, PA, United
States
Mayer, Stefan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-41
stefan.mayer@wiwi.uni-augsburg.de
Department of Analytics & Optimization, University of
Augsburg, Augsburg, Germany
Mäkelä, Marko M. . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-26, TE-26
makela@utu.fi
Department of Mathematics, University of Turku, Turku,
Finland
Mayorga Torres, Oscar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-07
oscar.mayorgat@unilibrebog.edu.co
Ingenieria Industrial, Universidad Libre, Bogota, Colombia,
Colombia
Mármol, Sergio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-41
smarmolg@repsol.com
Advanced Control, Petronor, Repsol, Muskiz, Spain
Mészáros, Csaba . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-17
csabameszaros@fico.com
Xpress Development Team, FICO, United Kingdom
Mazalov, Vladimir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-35
vmazalov@krc.karelia.ru
Karelia Research Center of Russian Academy of Sciences,
Institute of Appied Mathematical Research,Karelia Research
Center, Petrozavodsk, Karelia, Russian Federation
Mazurek, Jiri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-26
mazurek@opf.slu.cz
School of Business Administration in Karvina, Czech Republic
Mbiydzenyuy, Gideon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-04
gmb@bth.se
Department of Computer Science and Engineering, Blekinge
AUTHOR INDEX
Institute of Technology, Karlshamn, Sweden
McFarlane, Duncan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-03
dcm@eng.cam.ac.uk
Engineering Department, University of Cambridge, Cambridge, United Kingdom
McKenna, Russell . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-08, HB-09
mckenna@kit.edu
Chair for Energy Economics, IIP, KIT, Germany
McLaughlin, Ryan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-33
jryanmclaughlin@yahoo.com
Operations Research Department, Naval Postgraduate
School, Monterey, United States
McNaught, Ken . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-33
K.R.McNaught@cranfield.ac.uk
Dept of Informatics & Systems Engineering, Cranfield University, Swindon, United Kingdom
Meca, Ana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-22
ana.meca@umh.es
Operations Research Center, Universidad Miguel Hernández,
Elche, Alicante, Spain
Medina-Borja, Alexandra . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-45
alexandra.medinaborja@upr.edu
Industrial Engineering, Nsf/ Uprm, Falls Church, VA, United
States
Medrano, F. Antonio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-18
medrano@geog.ucsb.edu
Geography, UC Santa Barbara, Santa Barbara, CA, United
States
mehregan, mohammadreza . . . . . . . . . . . . . . . . . . . . . . . . . . FB-36
mehregan@ut.ac.ir
Tehran University, Tehran, Iran, Islamic Republic Of
Meirinhos, Jose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-10
jlmm@inescporto.pt
INESC Porto, Porto, Portugal
Meisel, Frank . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-02, HD-44
frank.meisel@wiwi.uni-halle.de
Martin-Luther-University Halle-Wittenberg, Halle, Germany
Meissner, Joern . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-32, FB-37
joe@meiss.com
Kuehne Logistics University, Hamburg, Germany
Mejía-Argueta, Christopher . . . . . . . . . . . . . . . . . . . . . . . . . TD-37
cmejia@logyca.org
CLI, Logyca / Research, Bogota, Cundinamarca, Colombia
Mejia Delgadillo, Gonzalo Enrique . . . . . . . . . . . . . . . . . . TA-13
gmejia@uniandes.edu.co
Industrial Engineering, Universidad de Los Andes, Bogota,
Colombia
Melacci, Stefano . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-16
mela@dii.unisi.it
University of Siena, Siena, Italy
Melachrinoudis, Emanuel . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-37
emelas@coe.neu.edu
Mechanical and Industrial Engineering, Northeastern University, Boston, MA, United States
Melamed, Michal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-45
michalro@tx.technion.ac.il
369
AUTHOR INDEX
IFORS 2014 - Barcelona
Industrial Engineering and Management, Technion - Israel
institute of technology, Israel
Technisches Büro HAUER Umweltwirtschaft GmbH, Korneuburg, Austria
Melega, Gislaine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-41
gislainemelega@gmail.com
Departamento de Matemática Aplicada, UNESP-IBILCE,
São José do Rio Preto, SP, Brazil
Mertikopoulos, Panayotis . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-24
panayotis.mertikopoulos@imag.fr
Laboratoire d’Informatique de Grenoble, French National
Center for Scientific Research (CNRS), France
Melian Batista, Belen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-40
mbmelian@ull.es
Estadística, I.O. y Computación, University of La Laguna,
La Laguna, Spain
Mesa, Eddy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-23
ejmesad@unal.edu.co
Facultad De Minas, Universidad Nacional De Colombia,
Medellin, Antioquia, Colombia
Memmedli, Memmedaga . . . . . . . . . . . . . . . . . . . MD-26, MA-35
mmammadov@anadolu.edu.tr
Statistics, T.C. Anadolu University, Eskisehir, Turkey
Mesa, Juan A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-01, HD-01
jmesa@us.es
University of Seville, Sevilla, Spain
Menéndez, Borja . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-37
borja.menendez@urjc.es
Universidad Rey Juan Carlos, Móstoles, Spain
Meskens, Nadine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-18, 19
nadine.meskens@uclouvain-mons.be
Louvain School of Management, UCL, Mons, Belgium
Mendes, Aline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-32
li.m@hotmail.com
Medicine, Universidade São Francisco, Bragança Paulista,
São Paulo, Brazil
Mestre, Pedro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-26
pmestre@utad.pt
Engineering, CITAB - University of UTAD, Vila Real, Portugal
Mendez-Aguirre, A. Carlos . . . . . . . . . . . . . . . . . . . . . . . . . . TA-21
cmendez@intec.unl.edu.ar
Intec (unl-conicet), Santa Fe, Santa Fe, Argentina
Mesyagutov, Marat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-21
marat.mesyagutov@tu-dresden.de
Numerical Mathematics, Dresden University of Technology,
Dresden, Germany
Menendez, Monica . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-04, TE-04
monica.menendez@ivt.baug.ethz.ch
ETH, Zurich, Zurich, Switzerland
Metello, Camila . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-43
camilanmetello@gmail.com
Industrial Engineering, PUC-Rio, Rio de Janeiro, RJ, Brazil
Menezes, Mozart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-03
mozartmenezes@me.com
Haskayne School of Business, University of Calgary, Calgary, Alberta, Canada
Metrane, Abdelmoutalib . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-02
abdelmoutalib.metrane@gerad.ca
Gerad, Montreal, Quebec, Canada
Meng, Lingyun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-01
menglingyun2001@hotmail.com
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China
Meunier, Frédéric . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-28, ME-35
frederic.meunier@enpc.fr
LVMT, Ecole Nationale des Ponts et Chaussées, Marne-laVallée, France
Meng, Ying . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-20
mengying@ise.neu.edu.cn
The Logistics Institute, Northeastern University, Shenyang,
China
Mevissen, Martin . . . . . MB-16, MD-16, FA-35, HE-35, MA-43
martmevi@ie.ibm.com
IBM Research - Ireland, Dublin, Ireland
Menou, Abdellah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-31
amenou@yahoo.com
Mohammed VI International Academy of Civil Aviation, National Airports Authority of Morocco, ONDA, Casablanca,
Morocco
Merino, María . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-45
maria.merino@ehu.es
Matemática Aplicada, Estadística e Investigación Operativa,
Facultad de Ciencia y Tecnología. Universidad del Pais
Vasco, Leioa, Vizcaya, Spain
Merkel, Erik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-09
erik.merkel@kit.edu
KIT-IIP, Germany
Merkert, Rico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-14
rico.merkert@sydney.edu.au
Institute of Transport and Logistics Studies (ITLS), The University of Sydney Business School, Sydney, NSW, Australia
Merstallinger, M. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-33
tbhauer@tbhauer.at
370
Meyer, Anne . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-02, TD-02
meyer@fzi.de
Information Process Engineering, FZI Research Center for
Information Technology, Karlsruhe, Germany
Meyer, Jörn C. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-38
meyer@b-n-p.de
Business Net Partners GmbH, Cologne, Germany
Meyer, Matthias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-44
matthias.meyer@tu-harburg.de
Hamburg University of Technology, Hamburg, Germany
Meyr, Herbert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-04, MD-41
H.Meyr@uni-hohenheim.de
Department of Supply Chain Management, University of Hohenheim, Stuttgart, Germany
Miao, Zhaowei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-44
miaozhaowei@gmail.com
Management Science, Xiamen University, Xiamen, Fujian,
China
Michel, Rudnianski . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-32
IFORS 2014 - Barcelona
michel.rudianski@wanadoo.fr
CNAM, Paris, France
Michelon, Philippe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-43
philippe.michelon@univ-avignon.fr
LIA, Université d’Avignon et des Pays de Vaucluse, Avignon
Cedex 9, France
Middleton, Victor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-08
middletv@woh.rr.com
College of Engineering & Computer Science, Wright State
University, Kettering, OH, United States
Midthun, Kjetil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-20, HE-29
Kjetil.Midthun@sintef.no
Applied Economics, SINTEF, Trondheim, Norway
Mielcová, Elena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-25
mielcova@opf.slu.cz
Department of Mathematical Methods in Economics, Silesian University Opava, School of Business Administration in
Karvina, Karviná, Czech Republic
Miettinen, Kaisa . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-18, TD-18
kaisa.miettinen@jyu.fi
Dept. of Mathematical Information Technology, University
of Jyväskyla, University of Jyväskyla, Finland
Miglionico, Giovanna . . . . . . . . . . . . . . . . . . . . . . . . HD-26, TE-26
gmiglionico@deis.unical.it
DIMES, Università della Calabria, Arcavacata di Rende, Italy
Miholca, Livia-Mihaela . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-26
mihaela.berchesan@yahoo.com
Mathematics, Babes-Bolyai University, Cluj-Napoca, Romania
Mika, Marek . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-12
Marek.Mika@cs.put.poznan.pl
Institute of Computing Science, Poznan University of Technology, Poznan, Poland
Mikhailov, Yuri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-16
ymikhailoff@yandex.ru
Nyurbinsky Technical Lyceum, Russian Federation
Mikhaylova, Anastasia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-05
a.mikhaylova.mba@gmail.com
Russian State University of Oil and Gas, Russian Federation
Milan, Lauriane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-37
Lauriane.Milan@vub.ac.be
MOBI — Mobility, Logistics and Automotive Technology,
Vrije Universiteit Brussel, Brussels, Belgium
Mild, Andreas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-27
andreas.mild@wu.ac.at
Production Management, Wirtschaftsuniversität Wien, Wien,
Austria
Mileva-Boshkoska, Biljana . . . . . . . . . . . . . . . . . . . . . . . . . . FA-42
biljana.mileva@gmail.com
Department of Knowledge Technologies, Jozef Stefan Institute, Ljubljana, Slovenia
Milios, Konstantinos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-34
kmchios@gmail.com
Electrical & Computer Engineering, National Technical University of Athens, Greece, Zografou, Greece
Milivojevic, Milica . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-39
milica.milivojevic.88@gmail.com
AUTHOR INDEX
Faculty of Science, University of Kragujevac, Kragujevac,
Serbia
Miller-Hooks, Elise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-25
elisemh@umd.edu
University of Maryland, College Park, MD, United States
Milone, Lucia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-30
lmilone@luiss.it
Economics and Finance, LUISS University, Rome, Italy
Milstein, Irena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-24
irenam@hit.ac.il
Faculty of Management of Technology, Holon Institute of
Technology, Holon, Israel
Miltenberger, Matthias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-39
miltenberger@zib.de
Optimization, Zuse Institute Berlin, Berlin, Germany
Minaev, Andrey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-16
andrej.minaev@phystech.edu
Moscow Institute of Physics and Technology, Moscow, Russian Federation
Minas, James . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-36
james.minas@rmit.edu.au
School of Mathematical and Geospatial Sciences, RMIT University, Melbourne, VIC, Australia
Mingozzi, Aristide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-11
mingozzi@csr.unibo.it
Department of Mathematics, University of Bologna, Cesena,
FC, Italy
Minis, Ioannis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-06, HE-44
i.minis@fme.aegean.gr
Financial and Management Engineering, University of the
Aegean, Cios, Greece
Minner, Stefan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-19, HD-41
stefan.minner@tum.de
TUM School of Management, Technische Universität
München, Munich, Germany
Minns, Steven . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-42
steven.minns@sauder.ubc.ca
SBE, University of British Columbia, Canada
Miralles, Cristobal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-42
cmiralles@omp.upv.es
Depto. Organización de Empresas, Universidad Politecnica
de Valencia, Valencia, Spain
Miranda, Jaime . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-44
jmirandap@fen.uchile.cl
Department of Management Control and Information Systems, Universidad de Chile, Chile
Miranda, Joao . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-44
jlmiranda@estgp.pt
Technologies and Design, ESTG/IPPortalegre, Portalegre,
Portugal
Mirchevska, Violeta . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-42
violeta.mircevska@ijs.si
Jozef Stefan Institute, Slovenia
Miroforidis, Janusz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-18
janusz.miroforidis@ibspan.waw.pl
Department of Intelligent Systems, Systems Research Institute of the Polish Academy of Sciences, Poland
371
AUTHOR INDEX
IFORS 2014 - Barcelona
Mirzaei Rabor, Fatemeh . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-07
mirzaeiftmh@yahoo.com
Faculty of Entrepreneurship, University of Tehran, Tehran,
Iran, Islamic Republic Of
Mizgier, Kamil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-30
kmizgier@ethz.ch
Department of Management, Technology, and Economics,
Swiss Federal Institute of Technology Zurich (ETH Zurich),
Zurich, Switzerland
Mishina, Tsutomu . . . . . . . . . . . . . . . . . . . . . . . . . . HB-27, MD-40
mishina@akita-pu.ac.jp
Systems Science and Technology, Akita Perfectural Univeristy, Akita, Japan
Mizhidon, Arsalan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-07
miarsdu@mail.ru
Applied Mathematics, East Siberia State University of Technology and Management, Ulan-Ude, Russian Federation
Mishra, Nishant . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-15
nmishra@rsm.nl
Management of Technology and Innovation, Rotterdam
School of Management, Erasmus University, Rotterdam,
Netherlands
Mizhidon, Klara . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-07
migka@mail.ru
Applied Mathematics, East Siberia State University of Technology and Management, Ulan-Ude, Russian Federation
Misra, Sidhant . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-06
sidhant@mit.edu
MIT, Cambridge, Massachusetts, United States
Mizuno, Shinji . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-40
mizuno.s.ab@m.titech.ac.jp
Industrial Engineering and Management, Tokyo Institute of
Technology, Tokyo, Japan
Missbauer, Hubert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-41
hubert.missbauer@uibk.ac.at
Information Systems, Production and Logistics Management,
University of Innsbruck, Innsbruck, Austria
Mladenovic, Nenad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-45
Nenad.Mladenovic@brunel.ac.uk
School of Mathematics, Brunel University, Uxbridge, Middlesex, United Kingdom
Mitra, Amitava . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-27
mitraam@auburn.edu
Aviation and Supply Chain Management, Auburn University,
Auburn, AL, United States
Mobtaker, Azdeh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-36
azadeh.mobtaker.1@ens.etsmtl.ca
École De Technologie Supérieure, Montréal, Canada
Mitra, Gautam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-21
gautam.mitra@brunel.ac.uk
CARISMA, Brunel University, Uxbridge, Middlesex, United
Kingdom
Moeke, Dennis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-13
d.moeke@vu.nl
Department of Mathematics, VU University Amsterdam,
Amsterdam, Netherlands
Mitropoulos, Ioannis . . . . . . . . . . . . . . . . HB-10, MD-22, HA-45
mitro@teipat.gr
Business Administration, Technological Educational Institute
of Western Greece, Patras, Greece
Moghaddas, Zohreh . . . . . . . . . . . . . . . . . . . . . . . . . HD-10, TE-14
info@mohsenvaez.com
Department of Electrical, Computer and Biomedical Engineering, Islamic Azad University, Qazvin branch, Tehran,
Iran, Islamic Republic Of
Mitropoulos, Panagiotis . . . . . . . . . . . . . . . . . . . . . HB-10, MD-22
pmitro@upatras.gr
Business Administration, Technological Educational Institute
of Western Greece, Patras, Greece
Moguerza, Javier M. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-20
javier.moguerza@urjc.es
Statistics and Operational Research, Rey Juan Carlos University, Móstoles (Madrid), Spain
Mitrovic Minic, Snezana. . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-02
snezanam@sfu.ca
Simon Fraser University, British Columbia, Canada
Mohamed, Souad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-34
s.mohamed@wmin.ac.uk
The University of Westminster, London, United Kingdom
Miura, Hidetoshi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-11
hmiura@nanzan-u.ac.jp
Nanzan university, Seto, Aichi, Japan
Moiseeva, Ekaterina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-07
moiseeva@kth.se
Electric Power Systems, KTH Royal Institute of Technology,
Stockholm, Sweden
Mixon, Dustin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-25
dustin.mixon@gmail.com
Air Force Institute of Technology, Dayton, OH, United States
Miyagawa, Masashi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-05
mmiyagawa@yamanashi.ac.jp
Regional Social Management, University of Yamanashi,
Kofu, Yamanashi, Japan
Miyata, Hiroyuki . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-09
hmiyata@dais.is.tohoku.ac.jp
Tohoku University, Japan
Miyazaki, Kenji . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-35
miya_ken@hosei.ac.jp
Faculty of Economics, Hosei University, Machida, Tokyo,
Japan
372
Molina, Julian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-37, TD-37
julian.molina@uma.es
University of Malaga, Malaga, Spain
Molina, Mariantonieta . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-29
mariantonieta9@hotmail.com
Industrial Engineer, Universidad Industrial de Santander, Bucaramanga, Santander, Colombia
Moliné, Joan Ignasi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-32
jnasi@hotmail.com
Departament d’Organització d’Empreses, Universitat Politècnica de Catalunya, Barcelona, Catalunya, Spain
Molinero, Xavier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-22
xavier.molinero@upc.edu
Matemàtica Aplicada 3, Upc - Albcom, Manresa, Barcelona,
IFORS 2014 - Barcelona
Spain
Momber, Ilan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-10
ilan.momber@iit.upcomillas.es
IIT - UP Comillas, Spain
Monaci, Michele . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-11, TE-11
monaci@dei.unipd.it
D.E.I., University of Padua, Padova, Italy
Monaco, M. Flavia . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-05, HE-05
monaco@deis.unical.it
DIMES - Dipartimento di Ingegneria Informatica, Modellistica, Elettronica e Sistemistica, Università della Calabria,
Rende (CS), Italy
Moncayo Gonzalez, Lina Marcela . . . . . . . . . . . . . . . . . . . HB-32
marc610@hotmail.es
Universidad San Buenaventura de Cali, Cali, Colombia
Moneta, Diana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-09
Diana.Moneta@rse-web.it
Ricerca sul Sistema Energetico - RSE SpA, Milano, Italy
Monfroy, Eric . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-25
monfroy.eric@gmail.com
Computer Science, University of Nantes, France
Monge, Juan Francisco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-03
monge@umh.es
Centro de Investigación Operativa, Universidad Miguel
Hernández, Elche, Alicante, Spain
Monks, Tom . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-23, MA-39
t.monks@exeter.ac.uk
University of Exeter Medical School, University of Exeter,
Exeter, Devon, United Kingdom
Monsuur, Herman . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-33
h.monsuur@nlda.nl
Faculty of Military Sciences, Netherlands Defence Academy,
Den Helder, Netherlands
Montanino, Marcello . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-04
m_montanino@msn.com
Department of Civil, Environmental and Architectural Engineering, University of Naples Federico II, Napoli, Italy
Montella, Bruno . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-01
montella@unina.it
Department of Civil, Architectural and Environmental Engineering, ’Federico II’ University of Naples, Naples, NA, Italy
Montenegro, Zaid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-19
zaidmontenegro@hotmail.com
CUCEA, Universidad de Guadalajara, Guadalajara, Jalisco,
Mexico
Montero, Lídia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-16
lidia.montero@upc.edu
Statistics and Operations Research Department, UPC
BarcelonaTech, Barcelona, Catalonia, Spain
Montero, Lídia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-01, HE-04
lidia.montero@upc.es
Statistics and Operational Research, UPC, Barcelona,
Barcelona, Spain
Montgomery, Douglas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-21
doug.montgomery@asu.edu
Industrial Engineering, Arizona State University, Tempe, Arizona, United States
AUTHOR INDEX
Montibeller, Gilberto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-23
g.montibeller@lse.ac.uk
Dept. of Management, London School of Economics, London, United Kingdom
Moon, Ilkyeong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-04
ikmoon@snu.ac.kr
Industrial Engineering, Seoul National University, Seoul, Korea, Republic Of
Moon, Jihwan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-15
jihwan.moon@warrington.ufl.edu
Marketing, University of Florida, Gainesville, Florida,
United States
Moore, Robyn . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-24
robyn@j.co.nz
Volunteering New Zealand, Porirua, Wellington, New
Zealand
Mora-Gutiérrez, Roman Anselmo. . . . . . . . . . . . . . . . . . . . FB-06
ing.romanmora@gmail.com
SISTEMAS, Universidad Autonoma Metropolitana, MEXICO, Distrito Federal, Mexico
Morabito, Reinaldo . . . . . . . . . . . . . . . . . . . . . . . . . MA-02, HA-05
morabito@ufscar.br
Dept. of Production Engineering, Federal University of São
Carlos, Sao Carlos, Sao Paulo, Brazil
Moradee, Seksun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-07
smoryade@umd.edu
Civil and Env. Eng., University of Maryland, College Park,
MD, United States
Morales, Juan Miguel . . . . . . . . . . . . . . . . . . . . . . . ME-07, HA-09
jmmgo@dtu.dk
Applied Mathematics and Computer Science, Technical University of Denmark, Kgs. Lyngby, Denmark
Morales, Nelson . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-29
nmorales@ing.uchile.cl
Mine Engineering, Universidad de Chile, Santiago, Chile
Morales-Espana, German . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-10
german.morales@iit.upcomillas.es
Institute for Research in Technology, Universidad Pontificia
Comillas, Madrid, Madrid, Spain
Moran, Diego . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-11
dmoran@gatech.edu
Industrial and Systems Engineering, Georgia Institute of
Technology, Atlanta, United States
Morari, Manfred . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-20
morari@ethz.ch
Automatic Control Laboratory, ETH Zurich, Zurich, Switzerland
Moreira, Alexandre . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-10
alexandremoreirads@gmail.com
Dept of Electrical Engineering, Pontifical Catholic University
of Rio de Janeiro, Rio de Janeiro, Brazil
Moreira, António José . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-27
1050812@isep.ipp.pt
School of Engineering, Polytechnic of Porto, Porto, Portugal
Moreira, Fábio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-06
fnssm26@gmail.com
INESC TEC, INEGI, Faculty of Engineering, University of
373
AUTHOR INDEX
IFORS 2014 - Barcelona
Porto, Porto, Portugal
Moreira, Fernando . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-34, TE-34
fernando.moreira@ed.ac.uk
Management Science and Business Economics, University of
Edinburgh, Edinburgh, United Kingdom
Moreno, Eduardo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-29
eduardo.moreno@uai.cl
Faculty of Engineering and Sciences, Universidad Adolfo
Ibañez, Santiago, Chile
Moreno, Luis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-23, MD-34
lfmoreno@unal.edu.co
Sistemas, Universidad Nacional de Colombia, Medellin, Antioquia, Colombia
Moreno, Placido . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-14, TD-14
placidomb@us.es
Engineering School, University of Seville, Seville, Spain
Moreno, Rodrigo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-10
r.moreno@imperial.ac.uk
Dept. of Electrical Engineering, University of Chile & Imperial College, Chile
Moreno-Vega, Marcos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-40
jmmoreno@ull.es
Estadística, I.O. y Computación, University of La Laguna,
La Laguna, Spain
Moretti, Antônio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-05, TA-14
moretti@ime.unicamp.br
State University of Campinas, Campinas, São Paulo, Brazil
Morgul, Ender . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-06
enderfaruk@gmail.com
CUE, NYU, Brooklyn, NY, United States
Morini, Cristiano . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-05
cristiano.morini@fca.unicamp.br
University of Campinas, Limeira, São Paulo, Brazil
Morini, Cristiano . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-14
professorcristianomorini@gmail.com
State University of Campinas, State University of Campinas,
Piracicaba, Sao Paulo, Brazil
Morisada, Masayo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-37
marine.mm7@gmail.com
Applied Information Technology, The Kyoto College of
Graduate School for Informatics, Kyoto, Japan
Morohoshi, Hozumi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-32
morohosi@grips.ac.jp
School for Policy Studies, National Graduate for Policy
Studiea, Tokyo, Tokyo, Japan
Mortenson, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-44
m.j.mortenson@lboro.ac.uk
School of Business & Economics, Loughborough University,
Loughborough, United Kingdom
Morton, Alec . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-24
alec.morton@strath.ac.uk
University of Strathclyde, United Kingdom
Moschioni, Luisa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-32
luisa.moschioni@gmail.com
Medicine, Universidade São Francisco, Bragança Paulista,
SP, Brazil
374
Mosheiov, Gur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-13
msomer@huji.ac.il
School of Business, Hebrew University, Jerusalem, Israel
Mosher, Charles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-38
Chuck.C.Mosher@conocophillips.com
ConocoPhillips, Houston, TX, United States
Mosidze, Aleksandre . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-09
a.mosidze@freeuni.edu.ge
Mathematics And Computer Sciences, Free University Of
Tbilisi, Tbilisi, Georgia
Mosquera Rodríguez, Manuel Alfredo . . . . . . . . . . . . . . . TA-22
mamrguez@uvigo.es
Statistics and Operations Research, University of Vigo,
Ourense, Ourense, Spain
Möst, Dominik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-07
Dominik.Moest@tu-dresden.de
Chair of Energy Economics, Technische Universität Dresden,
Dresden, Germany
Mostert, Martine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-19
martine.mostert@ulg.ac.be
University of Liege, Belgium
Mota, Enrique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-11
Enrique.Mota@uv.es
Statistics & Operations Research, University of Valencia,
Burjassot (Valencia), Spain
Motrenko, Anastasia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-16
pastt.petrovna@gmail.com
Applied mathematics and management, Moscow Institute of
Physics and Technology, Moscow, Russian Federation
Motti, Luigi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-34
luigi.motti@standardandpoors.com
Financial Institutions, Standard & Poor’s, Madrid, Spain
Moulai, Mustapha . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-39
mmoulai@usthb.dz
Department of Operations Research, University of Sciences
and Technology Houari Boumediene, Faculty of Mathematics, Algiers, Algeria
Moulai, Mustapha . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-19
mmoulai@usthb.dz
Operations research, Faculty of Mathematics / USTHB, Algiers, Algeria
Mourad, Amad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-16, FB-31
amad.mourad@gmail.com
LAMOS, Bejaia University, Bejaia, Bejaia, Algeria
Mourão, Cândida . . . . . . . . . . . . . . . . . . . . . . . . . . MB-02, MD-02
cmourao@iseg.utl.pt
Dep. Matemática, Instituto Superior de Economia e Gestão,
ULisboa / Centro IO, Lisboa, Portugal
Mourtos, Yiannis . . . . . . . . . . . . . . . . . . . . MB-12, MD-12, FA-39
mourtos@aueb.gr
Management Science & Technology, Athens University of
Economics & Business, Greece
Mousseau, Vincent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-24
vincent.mousseau@ecp.fr
LGI, Ecole Centrale Paris, Chatenay Malabry, France
Msakni, Mohamed Kais . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-05
msakni.kais@qu.edu.qa
IFORS 2014 - Barcelona
Mechanical and Industrial Engineering, University of Qatar,
Doha, Qatar
Muaualo, Miranda Albino Martins. . . . . . . . . . . . . . . . . . MD-22
mamuaualo@gmail.com
Operational Research, Federal University of Rio de Janeiro UFRJ, Rio de Janeiro, Rio de Janeiro, Brazil
Muñoz, Michelle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-40
ichi0819@hotmail.com
Facultad de Arquitectura e Ingenieria, Colegio Mayor de Antioquia, medellin, antioquia, Colombia
Mucherino, Antonio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-11
antonio.mucherino@irisa.fr
IRISA, University of Rennes 1, Rennes, France
Mueller, Ann-Kathrin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-38
ann-kathrin.mueller@kit.edu
Institute of Industrial Production, Karlsruhe Institute of Technology, Karlsruhe, Germany
AUTHOR INDEX
Autonomo de Mexico, Mexico City, Mexico
Muona, Tommi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-05
tommi.muona@aalto.fi
Automation and Systems Technology, Aalto University, Finland
Muradov, Khafiz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-20
Khafiz.Muradov@pet.hw.ac.uk
Institute of Petroleum Engineering, Heriot-Watt University,
Edinburgh, Select State, United Kingdom
Murali, Pavankumar . . . . . . . . . . . . . . . . . . . . . . . . ME-15, HE-20
pmurali@usc.edu
USC, CA, United States
Muriel Villegas, Juan Esteban . . . . . . . . . . . . . . . . . . . . . . . FB-27
jemuriel1@gmail.com
Industrial Engineering, Universidad de Antioquia - Instituto
Tecnológico Metropolitano, Medellín, Antioquia, Colombia
Mueller-Frank, Manuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-06
mmuellerfrank@iese.edu
IESE Business School, Spain
Muromachi, Yukio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-44
muromachi-yukio@tmu.ac.jp
Graduate school of Social Sciences, Tokyo Metropolitan University, Tokyo, Japan
Mues, Christophe . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-40, HE-40
C.Mues@soton.ac.uk
Management School, University of Southampton, Southampton, United Kingdom
Murphy, Frederic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-09
fmurphy@temple.edu
Fox School of Business and Management, Temple University, Philadelphia, PA, United States
Mujica Mota, Miguel . . . . . . . . . . . . . . . . . . . . . . . . HE-23, TD-41
m.mujica.mota@hva.nl
Aviation Academy, Amsterdam University of Applied Sciences, Amsterdam, Netherlands
Murphy, Liam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-29
liam.murphy@ucd.ie
Computer Science and Informatics, UCD, Dublin, Ireland
Mukhamedrakhimova, Liliya . . . . . . . . . . . . . . . . . . . . . . . HD-30
Liliya.Muhamedrahimova@gmail.com
Informatics and Robotics, Ufa State Aviation Technical University, Ufa, Bashkortostan, Russian Federation
Mula, Josefa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-26
fmula@cigip.upv.es
Research Centre on Production Management and Engineering, Universitat Politècnica de València, Alcoy, Alicante,
Spain
Mulder, Judith . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-05
mulder@ese.eur.nl
Erasmus University Rotterdam, Netherlands
Mulic, Ilhana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-08
Mulic@controlling.rwth-aachen.de
RWTH Aachen University, Aachen, Germany
Mumtaz, Mohammad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-04
mmumtaz@iba.edu.pk
IBA/LUMS, Pakistan
Munari, Pedro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-05, HB-26
munari@dep.ufscar.br
Industrial Engineering Department, Federal University of
Sao Carlos, Sao Carlos, Sao Paulo, Brazil
Munoz de Cote, Enrique . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-20
jemc@inaoep.mx
Computer Science, INAOE, Sta. Ma. Tonanzintla, Puebla,
Mexico
Munoz, David . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-35
davidm@itam.mx
Industrial & Operations Engineering, Instituto Tecnologico
Musmanno, Roberto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-45
musmanno@unical.it
DEIS, Università della Calabria, Rende (CS), Italy
Mustafa, Adli . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-23
adli@cs.usm.my
School of Mathematical Sciences, Universiti Sains Malaysia,
Georgetown, Penang, Malaysia
Muter, Ibrahim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-02
ibrahim.muter@gmail.com
Industrial Engineering, Bahcesehir University, Turkey
Mutlu, Fatih . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-05, TB-32
fatihmutlu@qu.edu.qa
Qatar University, Doha, Qatar
Mutlu, Sinem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-18
sinemmutlu01@gmail.com
Industrial Engineering, Middle East Technical University,
Ankara, Turkey
Mutluoglu, Omer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-04
omutluoglu@selcuk.edu.tr
Vocational School Of Technical Sciences, Selcuk University,
Turkey
Muto, Shigeo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-35
muto@soc.titech.ac.jp
Social Engineering, tokyo Institute of Technology, Tokyo,
Japan
Mwakilama, Elias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-41
mwakilamae@gmail.com
Mathematical Sciences, University of Malawi-Chancellor
College, Zomba, South-Eastern Region, Malawi
375
AUTHOR INDEX
IFORS 2014 - Barcelona
Myachin, Alexey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-11
a_miachin@mail.ru
National Research University Higher School of Economics,
Moscow, Russian Federation
Nabona, Narcis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-10
narcis.nabona@upc.edu
Statistics and Operations Research, Univ. Politecnica de
Catalunya, Barcelona, Spain
Nachtigall, Karl . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-01
karl.nachtigall@t-online.de
Faculy of Transportation and Traffic Science, TU Dresden,
Dresden, Sachsen, Germany
Nadal, Esteve . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-36
enr1@alumnes.udl.cat
Universitat de Lleida, Spain
Naderi, Bahman . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-14
bahman.naderi@aut.ac.ir
Department of Industrial Engineering, Faculty of Engineering, University of Kharazmi, Karaj, Iran, Islamic Republic Of
Naderi, Siamak . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-26
Siamak@sabanciuniv.edu
Faculty of Engineering and Natural Sciences, Sabanci University, Turkey
Nagano, Marcelo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-30
drnagano@usp.br
Accounting, University of Sao Paulo, Ribeirão Preto, Sao
Paulo, Brazil
Nagaoka, Sakae . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-03
nagaoka@enri.go.jp
Air Traffic Management, Electronic Navigation Research Institute, Chofu, Tokyo, Japan
Nagarajan, Mahesh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-22
mahesh.nagarajan@sauder.ubc.ca
Sauder School of Business, University of British Columbia,
Vancouver, British Columbia, Canada
Nagurney, Anna . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-33
nagurney@gbfin.umass.edu
Department of Finance and Operations Management, University of Massachusetts, Amherst, MA, United States
Nagy, Gábor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-45, HD-45
G.Nagy@kent.ac.uk
Kent Business School, University of Kent, Canterbury,
United Kingdom
Nahas, Nabil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-21
nahas@kfupm.edu.sa
Systems Engineering, KFUPM, Dhahran, Saudi Arabia
Naibaho, Tutiarny . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-17
tutiarny.naibaho@yahoo.com
Mathematics, Quality University, Medan, North Sumatera
Province, Indonesia
Nakagawa, Yuji . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-19
nakagawa@res.kutc.kansai-u.ac.jp
Faculty of Informatics, Kansai University, Osaka, Japan
Nakai, Toru . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-14
t-nakai@faculty.chiba-u.jp
Faculty of Education, Chiba University, Chiba, Japan
Nakamura, Kátia Yoshime . . . . . . . . . . . . . . . . . . . . . . . . . . MB-03
ktianakamura@gmail.com
Federal Univesity of São Paulo, Brazil
Nakamura, Shunya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-33
em51052@nda.ac.jp
Computer Science, National Defense Academy of Japan,
Japan
Nakanishi, Shingo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-30
nakanisi.suita@gmail.com
Computing Center, Osaka Institute of Technology, Osaka,
Osaka, Japan
Nakashima, Kenichi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-35
dr.nakasima@gmail.com
Department of Industrian Engineering and Management,
Kanagawa university, yokkaichi-shi, Mie prefecture, Japan
Nakayama, Hirotaka . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-37
nakayama@konan-u.ac.jp
Konan University, Kobe, Japan
Nakayama, Koki . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-25
k973722@kansai-u.ac.jp
Kansai University, Japan
Nakkas, Alper . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-06
nakkas@gmail.com
Nova School of Business and Economics, Lisbon, Portugal
Naldi, Simone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-16
naldi@laas.fr
LAAS - Toulouse, CNRS, Toulouse, Midi Pyrenees, France
Nallioğlu, Jülide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-43
jnallioglu@gmail.com
Institute of Science, Dokuz Eylül University, İzmir, Turkey
Namen Leon, Martha Isabel . . . . . . . . . . . . . . . . . . . . . . . . MA-22
mnamenle@asu.edu
Departamento de Ingeneria Industrial - School of Computing, Informatics and Decision Systems Engineering, Universidad de los Andes - Arizona State University, Bogota, D.C.,
Colombia
Nan, Zhu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-02, HB-10
zhunan@swufe.edu.cn
Southwestern University of Finance and Economics, Swufe,
chengdu, sichuan, China
Naoum-Sawaya, Joe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-43
joenaoum@ie.ibm.com
IBM Research, Dublin, Ireland
Naimer, Simone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-20
si_c_n@hotmail.com
Federal University of Santa Maria, Santa Maria, Brazil
Nascimento, Ana Cristina . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-14
anasoares_nascimento@hotmail.com
Neurology, Hospital of Faro, Faro, Algarve, Portugal
Nakade, Koichi. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-35
nakade@nitech.ac.jp
Department of Civil Engineering and Systems Management,
Nagoya Institute of Technology, Nagoya, Japan
Nascimento, Mariá C. V. . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-03
mariah.cris@gmail.com
Instituto de Ciência e Tecnologia, Universidade Federal de
São Paulo, São José dos Campos, São Paulo, Brazil
376
IFORS 2014 - Barcelona
Nasini, Stefano . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-17
stefano.nasini@upc.edu
Dept. of Statistics and Operations Research, Universitat Politecnica de Catalunya, Barcelona, Spain
Nasiry, Javad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-15
nasiry@ust.hk
ISOM, Hong Kong University of Science and Technology,
Hong Kong
Nassief, Wael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-02
w.nassief@gmail.com
Concordia University, Canada
Nasution, Azizah Hanim . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-17
azizahhanimn@yahoo.com
Education, Ministry of Religion Affair, Medan, North Sumatera Province, Indonesia
Núñez-Serna, Rosa Iris . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-39
iris_nuser@hotmail.com
Ingeniería de Procesos e Hidráulica, Universidad Autónoma
Metropolitana - Iztapalapa, Mexico, DF, Mexico, DF, Mexico
Néia, Silvely . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-42
silvelysalomao@fct.unesp.br
Statistic, UNESP, Presidente Prudente, São Paulo, Brazil
Nazarenko, Olga . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-44
olga.nazarenko@ukr.net
National Technical University of Ukraine "Kyiv Polytechnic
Institute", Kyiv, Ukraine
Nazari, Asef . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-43
asef.nazari@unisa.edu.au
School of Mathematics and Statistics, University of South
Australia, Mawson Lakes, South Australia, Australia
Nazemi, Abdolreza . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-38
abdolreza.nazemi@kit.edu
Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Ndlovu, Fadzayi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-34
fgangayi@gmail.com
Department of Statistics and Operations Research, National
University of Science and Technology, Zimbabwe, Bulawayo, Zimbabwe
Neaga, E. Irina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-42
irina.neaga@plymouth.ac.uk
Plymouth Graduate School of Management, Plymouth University, Plymouth, United Kingdom
Necil, Jan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-32
necil@fzi.de
Information Process Engineering, FZI Research Center for
Information Technology, Karlsruhe, Baden-Württemberg,
Germany
Nediak, Mikhail . . . . . . . . . . . . . . . . . . . . . . HB-15, TD-15, TD-27
mnediak@business.queensu.ca
School of Business, Queen’s University, Kingston, Ontario,
Canada
Negenborn, Rudy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-05
r.r.negenborn@tudelft.nl
Marine & Transport Technology, Delft University of Technology, Delft, Netherlands
Negreiros, Marcos José . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-02
negreiro@graphvs.com.br
Mestrado Estrado Profissional EM COMPUTAÇÃO, Univer-
AUTHOR INDEX
sitade Estadual do Ceara, Fortaleza, Ceara, Brazil
Negrotto, Daniel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-02
negrotto@gmail.com
Departamento de Computación- Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires,
Argentina
Neiva de Figueiredo, Joao . . . . . . . . . . . . . . . . . . . . . . . . . . MD-32
jneiva@sju.edu
Management, St Josephs University, Philadelphia, PA, United
States
Nel, Hannelie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-02
jhnel@sun.ac.za
Department of Logistics, Stellenbosch University, Stellenbosch, Western Province, South Africa
Nelis, Gonzalo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-29
gonza.nelis@gmail.com
Universidad de Chile, Chile
Nembhard, David . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-13
dnembhard@psu.edu
Industrial and Manufacturing Engineering, The Pennsylvania
State University, University Park, PA, United States
Nemcova, Zuzana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-26
zuzana.nemcova@uhk.cz
Department of Information Technologies FIM, University of
Hradec Kralove, Hradec Kralova, Czech Republic, Czech
Republic
Nemhauser, George . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-45
george.nemhauser@isye.gatech.edu
Georgia Institute of Technology, Atlanta, GA, United States
Nemoto, Toshio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-11
nemoto@shonan.bunkyo.ac.jp
Bunkyo University, Chigasaki, Kanagawa, Japan
Nencioni, Gianfranco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-11
gianfranco.nencioni@iet.unipi.it
Universita di Pisa, Pisa, Italy
Nenova, Zlatana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-19
zdn3@pitt.edu
Joseph M. Katz Graduate School of Business, University of
Pittsburgh, Pittsburgh, PA, United States
Nesi, Luan Carlos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-40
luannesi@gmail.com
Graduate Program in Applied Computing, University of Vale
do Rio dos Sinos, São Leopoldo, Rio Grande do Sul, Brazil
Ng, Chi To . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-19
lgtctng@polyu.edu.hk
Department of Logistics and Maritime Studies, The Hong
Kong Polytechnic University, Hong Kong, Hong Kong
Ng, Tony . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-43
ngh@mail.smu.edu
Department of Statistical Science, Southern Methodist University, Dallas, Texas, United States
Nganga, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-37
peternnganga@gmail.com
School of Economics, Nagasaki University, Nagasaki-shi,
Japan
Ngueveu, Sandra Ulrich . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-06
ngueveu@laas.fr
377
AUTHOR INDEX
IFORS 2014 - Barcelona
Université de Toulouse, INP, LAAS, Toulouse, France
Nguyen Thi, Bich Thuy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-17
thi-bich-thuy.nguyen9@etu.univ-lorraine.fr
Computer Science, University of Lorraine, Metz, France
Nguyen, Viet Anh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-16
nguyenvietanh@nus.edu.sg
Industrial and Systems Engineering, National University of
Singapore, Singapore
Nguyen, Viet Anh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-07
viet-anh.nguyen@epfl.ch
Ecole Polytechnique Federale de Lausanne, Switzerland
Niño Pérez, Esmeralda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-18
esmeralda.nino@upr.edu
Industrial Engineering, University of Puerto Rico at
Mayagüez, Mayagüez, Puerto Rico, Puerto Rico
Niño, Karen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-13
Ky.nino20@uniandes.edu.co
Industrial Engineering, Universidad de Los Andes, Bogotá,
Colombia
Niblett, Matthew . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-36
mniblett@geog.ucsb.edu
Geography, University of California Santa Barbra, Santa Barbara, California, United States
Desautels Faculty of Management, McGill University, Montreal, Canada
Nikulin, Yury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-19
yurnik@utu.fi
Department of Mathematics and Statistics, University of
Turku, Turku, Finland
Nilsson, Malin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-36
malin.nilsson@sveaskog.se
Sveaskog Förvaltnings AB, Vindeln, Sweden
Nimana, Nimit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-37
nimitn55@nu.ac.th
Naresuan University, Phitsanulok, Thailand
Nishihara, Michi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-34
nishihara@econ.osaka-u.ac.jp
Graduate School of Economics, Osaka University, Osaka,
Japan
Nishimura, Etsuko . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-05
e-nisi@maritime.kobe-u.ac.jp
Graduate School of Maritime Sciences, Kobe University,
Kobe, Japan
Nocera, Giacomo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-29
gnocera@audencia.com
Audencia Nantes School of Management, Nantes, France
Nicasio de Rosas, Nicasio . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-20
nickderosas@gmail.com
ALTERPLAN, Quezon City, Philippines
Nodet, Xavier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-21
xavier.nodet@fr.ibm.com
IBM, France
Nickel, Stefan . . . . . . . . . HA-02, ME-02, FA-03, HE-32, ME-39
stefan.nickel@kit.edu
Institute for Operations Research (IOR), Karlsruhe Institute
of Technology (KIT), Karlsruhe, Germany
Nogales, Adelaida . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-10
adelaida.nogales@iit.upcomillas.es
Instituto de Investigación Tecnológica, Universidad Pontificia Comillas, Madrid, Madrid, Spain
Nicoloso, Sara . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-12
nicoloso@disp.uniroma2.it
IASI-CNR, Roma, Italy
Nogales-Gómez, Amaya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-25
amayanogales@us.es
Estadística e Investigación Operativa, Universidad de Sevilla,
Seville, Spain
Nielsen, Kurt . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-08
kun@ifro.ku.dk
Department of Food and Resource Economics, University of
Copenhagen, Frederiksberg C., Denmark
Nielsen, Lars Relund . . . . . . . . . . . . . . . . . . . . . . . . . FA-19, HD-36
lars@relund.dk
Dept. of Economics and Business, Aarhus University, Aarhus
V, Denmark
Nielsen, Otto Anker . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-01
oan@transport.dtu.dk
DTU Transport, Kgs. Lyngby, Denmark
Niesen, Lenja . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-07
Lenja.Niesen@uni-due.de
Chair for Energy Economics, University Duisburg-Essen, Essen, Germany
Nieuwoudt, Isabelle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-11
isabelle@sun.ac.za
University of Stellenbosch, Stellenbosch, South Africa
Nikolova, Evdokia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-28
Nikolova2009@gmail.com
CSE, Texas A&M university, United States
Nikoofal, Mohammad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-32
menikoo@gmail.com
378
Nogo, Goranka . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-25
nogo@math.hr
Department of Mathematics, University of Zagreb, Zagreb,
Croatia
Noh, Kyung-Ran . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-16
infor@kisti.re.kr
KISTI, Korea, Republic Of
Nohadani, Omid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-43
nohadani@northwestern.edu
Industrial Engineering & Management Sciences, Northwestern University, Evanston, Illinois, United States
Nolz, Pamela . . . . . . . . . . . . . . . . . . . . . . . . TE-31, ME-33, MB-42
pamela.nolz@ait.ac.at
Mobility Department - Dynamic Transportation Systems,
AIT Austrian Institute of Technology, Vienna, Austria
Nonato, Maddalena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-43
nntmdl@unife.it
EndIF, Universita’ di Ferrara, Ferrara, Italy
Nonås, Lars Magne . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-05
Lars.Nonaas@marintek.sintef.no
Department of Maritime Transport Systems, MARINTEK,
Trondheim, Norway
IFORS 2014 - Barcelona
Nonobe, Koji . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-40
nonobe@k.hosei.ac.jp
Art and Technology, Hosei University, Koganei, Japan
Noordkamp, Wouter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-33
wouter.noordkamp@tno.nl
Military Operations, TNO, The Hague, Netherlands
Noparumpa, Tim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-24
tnoparum@providence.edu
Providence College, Providence, RI, United States
Norde, Henk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-22
h.norde@uvt.nl
Econometrics and Operations Research, Tilburg University,
Tilburg, Netherlands
Norese, Maria Franca . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-31
mariafranca.norese@polito.it
Dipartimento di Ingegneria Gestionale e della Produzione DIGEP, Politecnico di Torino, Torino, Italy
Norikumo, Shunei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-29
shunei.norikumo@gmail.com
General Management Department, Osaka University of Commerce, Higashiosaka, Osaka, Japan
Norlund, Ellen Karoline . . . . . . . . . . . . . . . . . . . . MA-05, MD-05
ellen.k.norlund@himolde.no
Faculty of Economics, Informatics and Social Sciences,
Molde University College - Specialized University in Logistics, Molde, Norway
Nossack, Jenny . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-12
jenny.nossack@uni-siegen.de
Institute of Information Systems, University of Siegen,
Siegen, North Rhine-Westphalia, Germany
Nowak, Dimitri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-18
dimitri.nowak@itwm.fraunhofer.de
Fraunhofer ITWM, Kaiserslautern, Germany
Nowak, Thomas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-33
thomas.nowak@wu.ac.at
Transport and Logistics Management, Vienna University of
Economics and Business, Wien, Austria
Noyan, Nilay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-31
nnoyan@sabanciuniv.edu
Manufacturing Systems/Industrial Engineering, Sabanci University, Istanbul, Turkey
Ntakolia, Charis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-21
charis.nt@hotmail.com
Applied Mathematical and Physical sciences, National Technical University of Athens, Athens, Greece
Nuñez, Cristina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-02
cristina.nunez@upc.edu
Statistics and Operations Research, Universitat Politècnica
de Catalunya, Barcelona, Spain
Nuggehalli, Ranganath . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-23
Rnuggehalli@ups.com
Operations Research, UPS, Timonium, MD, United States
Nunes, Cláudia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-24
cnunes@math.ist.utl.pt
Mathematics, IST, Lisboa, Portugal
Nunes, Pedro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-40
pnunes@uac.pt
AUTHOR INDEX
Economics, University of the Azores, Ponta delgada, Portugal
Nunez, Marina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-44
mnunez@ub.edu
Mathematical Economics, University of Barcelona,
Barcelona, Spain
Nuo, Qin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-27
nuoqi32013@gmail.com
Applied Imformation Technology, The Kyoto College of
Graduate school for Informatics, Kyoto, Kyoto, Japan
Nygreen, Bjørn . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-31
bjorn.nygreen@iot.ntnu.no
Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology,
Trondheim, Norway
O’Brien, Frances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-24
Frances.O-Brien@wbs.ac.uk
Warwick Business School, University of Warwick, Coventry,
United Kingdom
O’Hanley, Jesse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-03
j.ohanley@kent.ac.uk
Kent Business School, University of Kent, Canterbury,
United Kingdom
O’Neil, Ryan J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-21
roneil1@gmu.edu
Department of Systems Engineering and Operations Research, George Mason University, Washington, DC, DC,
United States
Ochi, Luiz Satoru . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-02, MD-43
luiz.satoru@gmail.com
Computer Science, Fluminense Federal University, Niteroi,
Rio de Janeiro, Brazil
Ochi, Luiz Satoru . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-06, FB-23
satoru@ic.uff.br
Institute of Computing, Fluminense Federal University,
Niterói, Rio de Janeiro, Brazil
Odegaard, Fredrik . . . . . . . . . . . . . . . . . . . . . . . . . . HE-08, HB-15
fodegaard@ivey.uwo.ca
Ivey Business School, Western University, London, Ontario,
Canada
Odoni, Amedeo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-35
arodoni@mit.edu
Operations Research Center, Massachusetts Inst. of Technology, Cambridge, MA, United States
Oesterle, Jonathan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-13
jno@ipa.fraunhofer.de
Fraunhofer IPA, Germany
Oggioni, Giorgia . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-07, HA-09
oggioni@eco.unibs.it
Department of Economics and Management, University of
Brescia, Italy, Brescia, Italy, Italy
Ogiwara, Kei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-27
d12s005@akita-pu.ac.jp
Operating Research, Yurihonjo City, Japan
Oguz, Murat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-03
mo2g12@soton.ac.uk
Southampton Management School, University of Southampton, Southampton, United Kingdom
379
AUTHOR INDEX
IFORS 2014 - Barcelona
Ohimmou, Mustapha . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-36
mustapha.ouhimmou@etsmtl.ca
Logistics and Operations Engineering, École de Technologie
Supérieure, Montréal, québec, Canada
Ohlmann, Jeffrey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-41
jeffrey-ohlmann@uiowa.edu
Management Sciences, University of Iowa, Iowa City, Iowa,
United States
Ohnishi, Masamitsu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-30
ohnishi@econ.osaka-u.ac.jp
Graduate School of Economics, Osaka University, Toyonaka,
Osaka, Japan
Oikonomikou, Leoni Eleni . . . . . . . . . . . . . . . . . . . . . . . . . . MD-26
leoni-eleni.oikonomikou@wiwi.uni-goettingen.de
Economics, Georg-August Universität Göttingen, Göttingen,
Lower Saxony, Germany
Oishi, Jun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-30
v10013@shibaura-it.ac.jp
Mathematical Science, Shibaura Institution of Technology,
Saitama, Saitama, Japan
Ojakian, Kerry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-17
kerry.ojakian@bcc.cuny.edu
Math, Bcc (cuny), Bronx, NY, United States
Olabode, Adewoye . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-14
boka152002@yahoo.com
Mathematics, Yaba College of Technology, Yaba, Lagos
State, Nigeria
Oladejo, Michael O . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-04
mikeoladejo2003@yahoo.co
Mathematics, Nigerian Defence Academy Kaduna, Kaduna
Nigeria, Kaduna, Kaduna, Nigeria
Olgun, Mehmet Onur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-30
onurolgun@sdu.edu.tr
Industrial Engineering, Süleyman Demirel University, Turkey
Oliphant, Terry-leigh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-14
terryloveleigh@yahoo.com
Computational and Applied Mathematics, University of the
Witwatersrand, Johanesburg, South Africa
Oliu Barton, Miquel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-24
oliubart@gmail.com
Institut de Mathématiques, Université de Neuchâtel, Neuchâtel, Switzerland
Oliveira, Andrea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-05
andrea.oliveira@fca.unicamp.br
Applied Science Faculty, University of Campinas, Limeira,
São Paulo, Brazil
Oliveira, Aurelio . . . . . . . . . . . . . . . . . . . . . HB-17, TD-17, HE-28
aurelio@ime.unicamp.br
Computational & Applied Mathematics, State University of
Campinas, Campinas, SP, Brazil
Oliveira, Bruno M.P. M. . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-30
bmpmo@fcna.up.pt
Fcnaup & Inesc-tec, Porto, Portugal
carlos_m_oliveira88@hotmail.com
IST-CEMAT, Portugal
Oliveira, Fabrício . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-29, HB-43
fabricio.oliveira@puc-rio.br
Industrial Engineering, PUC-Rio, Rio de Janeiro, Rio de
Janeiro, Brazil
Oliveira, José Fernando . . . . . . . FA-11, MA-19, FA-21, HA-21
jfo@fe.up.pt
INESC TEC, Faculty of Engineering, University of Porto,
Porto, Portugal
Oliveira, Jurandir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-26
jurandir@ufpi.edu.br
Mathematics, Federal University of Piaui, Teresina, Piauí,
Brazil
Oliveira, Tiago . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-36
tiago.oliveira@portucelsoporcel.com
Forest Proctection, grupo Portucel Soporcel, Setúbal, Portugal
Öllinger, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-25
michael.oellinger@unibw.de
Universität der Bundeswehr München, Germany
Olthoff, Inken . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-28
olthoff@zib.de
Zuse Institute Berlin, Germany
Olyazadeh, Roya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-27
roya.olyazadeh@unil.ch
UNIL, Lausanne, Vaud, Switzerland
Öner, Nihat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-37
nihatoner10@gmail.com
Industrial Engineering Department, TOBB University of Economics and Technology, Ankara, Turkey
Onn, Shmuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-45
onn@ie.technion.ac.il
Davidson Faculty of IE & M, Technion - Israel Institute of
Technology, Haifa, Israel
Ono Koroishi, Giovanna . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-21
gikoroishi@gmail.com
Mechatronics and Mechanical Systems Engineering Department, Escola Politecnica da Universidade de Sao Paulo, Sao
Paulo, SP, Brazil
Onoda, Takashi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-16
onoda@criepi.denken.or.jp
System Engineering Lab., CRIEPI, Tokyo, Japan
Oosthuizen, Louzanne . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-36
louzanne@sun.ac.za
Industrial Engineering, Stellenbosch University, Matieland,
Western Cape, South Africa
Opitz, Jens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-01
jens.opitz@tu-dresden.de
Faculty of Transport and Traffic Sciences, Institut for Logistics and Aviation, Technical University of Dresden, Dresden,
Sachsen, Germany
Oliveira, Bruno . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-36
bruno.oliveira282@gmail.com
Uesp, Inesc Tec, Cascais, Portugal
Ordóñez, Luis G. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-10
luis.g.ordonez@upc.edu
Signal Theory and Communications, Technical University of
Catalonia, Barcelona, Barcelona, Spain
Oliveira, Carlos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-24
Ordieres-Mere, Joaquin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-40
380
IFORS 2014 - Barcelona
j.ordieres@upm.es
Industrial Management, Universidad Politécnica de Madrid,
Madrid, Madrid, Spain
Ordin, Burak . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-26
burak.ordin@ege.edu.tr
Mathematics, Ege University, izmir, bornova, Turkey
Ordonez, Fernando . . . . . . . . . . . . . . . . . . . . . . . . . . HD-25, FB-41
fordon@usc.edu
Industrial and Systems Engineering, University of Southern
California, Los Angeles, CA, United States
AUTHOR INDEX
Osipenko, Denys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-34
denis.osipenko@gmail.com
Business School, the University of Edinburgh, Edinburgh,
United Kingdom
Osmetti, Silvia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-38
silvia.osmetti@unicatt.it
Università Cattolica di Milano, Milano, Italy
Osogami, Takayuki . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-09
osogami@jp.ibm.com
IBM Research - Tokyo, Japan
Orjuela Castro, Javier Arturo . . . . . . . . . . . . . . . . . . . . . . MD-04
jaorjuelac@unal.edu.co
Engineering, Universidad Distrital, Bogota, Colombia
Osorio, Juan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-40
juan.osorio@correounivalle.edu.co
Ingeniería Industrial, Universidad del Valle, Colombia
Orozco, Erick. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-44
eorozco15@unisimonbolivar.edu.co
Departamento de Ingeniería Industrial, Universidad Simon
Bolívar, Barranquilla, Atlantico, Colombia
Osorio, Maria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-07
mariauxosorio@gmail.com
Chemical Engineering, Universidad Autonoma de Puebla,
Puebla, Puebla, Mexico
Orpiszewski, Tomasz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-43
tomasz.orpiszewski@gmail.com
Fixed Income / Sdfi, Candriam / University Paris Dauphine,
Bruxelles, Belgium
Ospina Lopez, Diana Yomali . . . . . . . . . . . . . . . . . . . . . . . . . FA-11
deg08015@fe.up.pt
Faculty of Engineering, University of Porto, Porto, Portugal
Ortega Riejos, Francisco A. . . . . . . . . . . . . . . . . . . . . . . . . . HD-01
riejos@us.es
Applied Mathematics I, University of Seville, Seville, Spain
Ortega-Mier, Miguel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-13
miguel@etsii.upm.es
Department of Industrial Engineering, Business Administration and Statistics, Technical University of Madrid (UPM),
Madrid, Spain
Ortigosa, Javier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-04
javier.ortigosa@ivt.baug.ethz.ch
IVT, ETH Zurich, Zurich, Switzerland
Ortigosa, Pilar M. . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-18, HD-45
ortigosa@ual.es
Departament of Informatics, University of Almería, Almería,
Spain
Ortiz Pimiento, Néstor Raúl . . . . . . . . . . . . . . . . . . . . . . . . . TA-29
nortiz@uis.edu.co
Universidad Industrial de Santander, Colombia
Ortiz, Camilo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-31
camiloortiza@gmail.com
Mechanical and Industrial Engineering, Concordia University, Montreal, Canada
Ortiz, Julian. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-29
jortiz@ing.uchile.cl
Mining Engineering, Universidad de Chile, Santiago, Chile
Ortner, André . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-07
ortner@eeg.tuwien.ac.at
Technical University of Vienna, Austria
Ortuño, M. Teresa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-37
mteresa@mat.ucm.es
Estadística e Investigación Operativa, Universidad Complutense de Madrid, Madrid, Spain
Osadchiy, Nikolay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-15
nikolay.osadchiy@emory.edu
Emory University, Atlanta, GA, United States
Ostermaier, Andreas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-15
andreas.ostermaier@tum.de
TUM School of Management, Technische Universität
München, München, Germany
Ostrihon, Filip . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-23
filip.ostrihon@savba.sk
Institute of Economic Research, Slovak Academy of Sciences, Slovakia
OSullivan, Barry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-32
barry.osullivan@gmail.com
University College Cork, Ireland
Otapasidis, Panagiotis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-06
p.otapasidis@gmail.com
Financial & Management Engineering, University of the
Aegean, Thermi, Thessaloniki, Greece
Ott, Marion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-41
marion.ott@rwth-aachen.de
School of Business and Economics, RWTH Aachen University, Aachen, Germany
Oubraham, Aichouche . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-25
oubraham.aichouche@gmail.com
Operational Research, LAMOS, Bejaia, Algeria
Ouenniche, Jamal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-25
jamal.ouenniche@ed.ac.uk
Management School and Economics, Edinburgh University,
Edinburgh, Scotland, United Kingdom
Ouhoud, Amina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-35, MB-44
ami_ouh@yahoo.fr
Manufacturing Engineering Laboratory of Tlemcen (MELT),
Tlemcen University, Algeria
Oussedik, Sofiane . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-01, MA-21
soussedik@fr.ibm.com
IBM, France
Ovchinnikov, Anton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-15
aovchinnikov@darden.virginia.edu
University of Virginia, Darden School of Business, Charlottesville, VA, United States
381
AUTHOR INDEX
IFORS 2014 - Barcelona
Oyama, Tatsuo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-32
oyamat@grips.ac.jp
School for Policy Studies, National Graduate Institute for
Policy Studies, Tokyo, Japan
Oyatoye, Olateju Emmanuel . . . . . . . . . . . . . . . . . . . . . . . . MA-37
eoyatoye@unilag.edu.ng
Department of Business Administration, University of Lagos,
Lagos, Nigeria
Oyemomi, Oluwafemi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-42
oluwafemi.oyemomi@plymouth.ac.uk
Graduate School of Management, Plymouth University, Plymouth, United Kingdom
Ozawa, Masanori . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-30
ozawa@ae.keio.ac.jp
Faculty of Science and Technology, Keio University, Yokohama, Japan
Ozbay, Kaan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-06
kaan.ozbay@gmail.com
Civil and Urban Engineering, New York University, New
York City, New York, United States
Ozdemir, Ozer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-26, MA-35
ozerozdemir@anadolu.edu.tr
Statistics, Anadolu University, Eskisehir, Turkey
Özdemir, Rifat Gürcan . . . . . . . . . . . . . . . TB-19, TB-24, ME-29
rg.ozdemir@iku.edu.tr
Industrial Engineering Department, Istanbul Kültür University, Istanbul, Turkey
Ozen, Ulas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-22
ulas.ozen@ozyegin.edu.tr
Ozyegin University, Istanbul, Turkey
Ozener, Okan . . . . . . . . . . . . . . . . . . . . . . . . MA-02, TB-02, TE-27
orsan.ozener@ozyegin.edu.tr
Industrial Engineering, Ozyegin University, Istanbul, Turkey
Ozer, Ozalp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-15
oozer@utdallas.edu
Jindal School of Management, The University of Texas at
Dallas, Richardson, TX, United States
Özkan, Ozan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-12, TD-12
oozkan@selcuk.edu.tr
Mathematics, Selçuk University, KONYA, Turkey, Turkey
Özcan, Ender . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-33, HE-33
exo@cs.nott.ac.uk
Computer Science, University of Nottingham, Nottingham,
United Kingdom
Ozlen, Melih . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-36
melih.ozlen@rmit.edu.au
School of Mathematical and Geospatial Sciences, RMIT University, Melbourne, VIC, Australia
Özcan, Özkan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-33
ozkanozcan@hvkk.tsk.tr
Scientific Decision Support Department, Turkish Air Force
Command, Çankaya, Ankara, Turkey
Ozluk, Ozgur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-39
ozgur@sfsu.edu
College of Business, San Francisco State University, San
Francisco, CA, United States
Ozcetin, Erdener . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-23
eozcetin@anadolu.edu.tr
Industrial Engineering, Anadolu University, Eskişehir,
Turkey
Özmen, Ayse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-09
ayseozmen19@gmail.com
Scientific Computing, Institute of Applied Mathematics,
Middle East Technical University, Ankara, Turkey
Ozcil, Abdullah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-21
aozcil@pau.edu.tr
Business Administration, Pamukkale University, Denizli,
Turkey
Ozogur-Akyuz, Sureyya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-43
sureyya.akyuz@bahcesehir.edu.tr
Department of Mathematics and Computer Science, Bahcesehir University, Istanbul, Turkey
Ozdaglar, Asu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-06
asuman@mit.edu
EECS, MIT, Cambridge, MA, United States
Ozpeynirci, Ozgur . . . . . . . . . . . . . . . . . . . . . . . . . . HA-16, MD-40
ozgur.ozpeynirci@ieu.edu.tr
Department of Logistics Management, Izmir University of
Economics, Izmir, Turkey
Özdağoğlu, Aşkın . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-27
askin.ozdagoglu@deu.edu.tr
Business, Dokuz Eylul University, Turkey
Özdağoğlu, Güzin . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-27, HD-43
guzin.kavrukkoca@deu.edu.tr
Business, Dokuz Eylul University, Turkey
Ozdemir, Abdullah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-15
abdullahozdemir@arel.edu.tr
İstanbul Arel University, Istanbul, Turkey
Ozdemir, Deniz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-05
deniz.ozdemir@yasar.edu.tr
Dept. of International Logistics Management, Yasar University, Izmir, Turkey
Ozdemir, Gultekin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-30
gultekinozdemir@sdu.edu.tr
Industrial Engineering, Suleyman Demirel University, Isparta, Turkey
382
Ozpeynirci, Selin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-16
selin.ozpeynirci@ieu.edu.tr
Industrial Systems Engineering, Izmir University of Economics, Izmir, Turkey
Ozsakalli, Gokberk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-05
gokberk.ozsakalli@gmail.com
Yasar University, Izmir, Turkey
Ozsoydan, Fehmi Burcin . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-23
burcin.ozsoydan@deu.edu.tr
Industrial Engineering, Dokuz Eylul University, Turkey
Özsüt, Zeynep . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-18
zozsut@anadolu.edu.tr
Industrial Engineering, Anadolu University, Denizli, Turkey
Ozturk, Gurkan . . . . . . . . . . . . . . . . . . . . . . TE-16, FB-23, HE-26
gurkan.o@anadolu.edu.tr
Industrial Engineering, Anadolu University, Eskisehir,
Turkey
IFORS 2014 - Barcelona
Ozuna Espinosa, Edith Lucero . . . . . . . . . . . . . . . . . . . . . . HB-21
luceroozuna@gmail.com
Facultad de Ingeniería Mecánica y Eléctrica, Universidad
Autónoma de Nuevo León, San Nicolás de los Garza, Nuevo
León, Mexico
Pacciarelli, Dario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-01
pacciarelli@dia.uniroma3.it
Dipartimento di Ingegneria, Università Roma Tre, Roma,
Italy
Pacheco, Abílio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-36
apacheco@mit.edu
INESC Porto, Faculty of Engineering, University of Porto,
Matosinhos, Portugal
Pacino, Dario . . . . . . . . . . . . . . . . . . . . . . . . . FB-05, HB-05, HE-05
darpa@transport.dtu.dk
Transport, Technical University of Denmark (DTU), Kgs.
Lyngby, Denmark
Padman, Rema . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-06
rpadman@cmu.edu
The Heinz College, Carnegie Mellon University, Pittsburgh,
PA, United States
Padmanabhan, Paddy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-15
paddy.padmanaban@insead.edu
INSEAD, Singapore, Singapore
Paetz, Friederike . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-19
friederike.paetz@tu-clausthal.de
Marketing, Clausthal University of Technology, Institute of
Management and Economics, Germany
Paetz, Tobias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-12
tobias.paetz@tu-clausthal.de
Operations Management Group, Clausthal University of
Technology, Clausthal-Zellerfeld, Germany
Pages Bernaus, Adela . . . . . . . . . . . . . . . . . . . . . . . TD-10, MB-45
adela.pages@iot.ntnu.no
IOT, NTNU, Trondheim, Norway
Pajala, Tommi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-18
tommi.pajala@aalto.fi
Industrial Management, Aalto University, Espoo, Finland
Pakhomova, Nadezda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-40
n.pahomova@spbu.ru
Economic Faculty, St. Petersburg State University, St. Petersburg, Russian Federation
Paksoy, Turan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-39
tpaksoy@yahoo.com
Industrial Engineering, Selçuk University, Konya, Turkey
Pala, Ozge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-15
opala@ku.edu.tr
Koc University, Turkey
Palancı, Osman . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-30
osmanpalanci@sdu.edu.tr
Mathematics, Suleyman Demirel University, Isparta, Turkey
Palekar, Udatta . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-19
palekar@illinois.edu
Business Administration, University of Illinois at UrbanaChampaign, Champaign, Illinois, United States
Palma, Jaime . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-32
AUTHOR INDEX
jaime.palma@itam.mx
Ingenieria Industrial y Operaciones, ITAM, Instituto Tecnológico Autónomo de México, Mexico DF, Distrito Federal,
Mexico
Palomar, Daniel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-10
palomar@ust.hk
ECE, HKUST, Hong Kong
Palos Delgadillo, Humberto . . . . . . . . . . . . . . . . . . . . . . . . . TD-19
josechavez@iteso.mx
Maestría en Administración de Negocios, CUCEA, Universidad de Guadalajara, Zapopan, Jalisco, Mexico
Pamplona, Edson . . . . . . . . . . . . . . . . . . . . MA-30, HB-34, TB-34
pamplona@unifei.edu.br
Engenharia de Produção e Gestão, UNIFEI, Itajubá, Minas
gerais, Brazil
Pan, Rong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-21
rong.pan@asu.edu
Arizona State University, Tempe, United States
Pana, Anca . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-08
anca.pana@bf.uzh.ch
Department of Banking and Finance, University of Zurich,
Zürich, Switzerland
Panda, Geetanjali . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-34
geetanjali@maths.iitkgp.ernet.in
Mathematics, Indian Institute of Technology, Kharagpur,
Kharagpur, West Bengal, India
Pang, Gu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-35
gu.pang@ncl.ac.uk
Newcastle University Business School, Newcastle upon
Tyne, United Kingdom
Pang, King-Wah Anthony . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-02
lgtapang@polyu.edu.hk
Department of Logistics and Maritime Studies, The Hong
Kong Polytechnic University, Hong Kong, Hong Kong
Pantrigo, Juan J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-37
juanjose.pantrigo@urjc.es
Universidad Rey Juan Carlos, Móstoles, Spain
Panzica, Roberto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-38
robpanzica@hotmail.it
Goethe University, Frankfurt am Main, Germany
Paolone, Mario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-20
mario.paolone@epfl.ch
École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
Paolotti, Luisa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-36
luisa.paolotti@gmail.com
Agricultural, Agrifood and Environmental Sciences, University of Perugia, Perugia, Italy
Papadaki, Katerina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-27
k.p.papadaki@lse.ac.uk
Management, London School of Economics and Political
Science, London, United Kingdom
Papadimitriou, Dimitri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-31
dimitri.papadimitriou@alcatel-lucent.com
Bell Labs, Alcatel-Lucent, Antwerp, Antwerp, Belgium
Papadopoulos, Thanos . . . . . . . . . . . . . . . . . . . . . . . TA-23, HA-38
Athanasios.Papadopoulos@sussex.ac.uk
383
AUTHOR INDEX
IFORS 2014 - Barcelona
Sussex School of Business, Management, and Economics,
University of Sussex, Falmer, Brighton, United Kingdom
Papageorgiou, Markos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-04
markos@dssl.tuc.gr
Production Engineering and Management, Technical University of Crete, Chania, Greece
Papamichail, Ioannis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-04
ipapa@dssl.tuc.gr
Production Engineering and Management, Technical University of Crete, Chania, Greece
Papamichail, K. Nadia . . . . . . . . . . . . . . . . . . . . . . . TA-31, HD-42
nadia.papamichail@mbs.ac.uk
Manchester Business School, University of Manchester,
Manchester, United Kingdom
Papanastasiou, Yiangos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-15
yiangosp.phd2010@london.edu
London Business School, London, United Kingdom
Papastamatiou, Ilias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-42
ipapastamatiou@epu.ntua.gr
Electrical and Computer Engineering, Decision Support Systems Laboratory (DSSL), National Technical University of
Athens, athe, Greece
Papavasiliou, Anthony . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-07
anthony.papavasiliou@uclouvain.be
Mathematical Engineering, CORE, Catholic University of
Louvain, Louvain la Neuve, Belgium
Papayanopoulos, Lee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-19
lp1@business.rutgers.edu
MSIS, Rutgers University, Newark, NJ, United States
Pape, Christian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-20
Christian.Pape@uni-due.de
Chair for Management Science and Energy Economics, Universität Duisburg-Essen, Essen, NRW, Germany
Papoula, Paraskevi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-34
papoula@swissquant.ch
swissQuant Group, Zürich, Switzerland
Paquay, Célia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-21
cpaquay@ulg.ac.be
HEC - Management School, University of Liège, Liège, Belgium
Paquet, Marc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-36, ME-40
Marc.Paquet@etsmtl.ca
École De Technologie Supérieure, Montreal, Quebec, Canada
Parada, Víctor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-02
victor.parada@usach.cl
Universidad de Santiago de Chile, Santiago, Chile
Paraschiv, Florentina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-09
florentina.paraschiv@unisg.ch
Energy Finance, ior/cf HSG, Switzerland
Paraskevopoulos, Dimitris . . . . . . . . . . . . . . . . . . . . . . . . . . MD-14
d.paraskevopoulos@bath.ac.uk
School of Management, University of Bath, Bath, United
Kingdom
Parbo, Jens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-01
jepar@transport.dtu.dk
DTU Transport, Kgs. Lyngby, Denmark
384
Pardalos, Panos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-18, FB-39
pardalos@ufl.edu
ISE Department, University of Florida, Gainesville, Florida,
United States
Paredes, Fernando . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-25
fernando.paredes@udp.cl
Universidad Diego Portales, Santiago, Chile
Paredes, Fernando . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-23, HE-25
fernandoparedesc@gmail.com
Escuela de Ingeniería Industrial, Universidad Diego Portales,
Santiago, Chile
Paredes-Belmar, Germán . . . . . . . . . . . . . . . . . . . . TE-02, HD-03
germanparedes@gmail.com
Systems Engineering, Pontificia Universidad Católica de
Chile, Santiago, Select, Chile
Park, Bum Hwan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-01
bumhwan.park@gmail.com
Railroad Management and Logistics, Korea National University of Transportation, Uiwang, Gyeonggi-Do, Korea,
Republic Of
Park, Cheong Sool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-16
dumm97@korea.ac.kr
School of Industrial Management Engineering, Korea University, Seoul, Korea, Republic Of
Park, Heewoong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-42
hee188@snu.ac.kr
Seoul National University, Korea, Republic Of
Park, Hyoshin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-04
hspark@umd.edu
University of maryland, College Park, United States
Park, Inbeom . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-42
articulate@snu.ac.kr
Seoul National University, Korea, Republic Of
Park, Jinwoo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-08
autofact@snu.ac.kr
Dept. of Industrial Engineering, Seoul National University,
Seoul, Korea, Republic Of
Park, Jonghun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-42
jonghun@snu.ac.kr
Industrial Engineering, Seoul National University, Seoul, Korea, Republic Of
Park, Kyung Min . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-32
kminpark@yonsei.ac.kr
Yonsei University, Korea, Republic Of
Park, Seongtaek. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-32
solpherd@cbnu.ac.kr
Management Information Systems, Chungbuk National University, Cheongju, Chungbuk, Korea, Republic Of
Park, Seung Hwan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-34
udongpang@korea.ac.kr
School of Industrial Management Engineering, Korea University, Seoul, Korea, Republic Of
Park, You-Jin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-21
eugenepark@cau.ac.kr
School of Business Administration, College of Business and
Economics, Chung-Ang University, Seoul, Korea, Republic
Of
IFORS 2014 - Barcelona
Park, Young Joon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-42
dmqm.yjpark@gmail.com
Korea Univ., Korea, Republic Of
Parkes, Andrew J. . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-33, HE-33
ajp@cs.nott.ac.uk
School of Computer Science, University of Nottingham, Nottingham, United Kingdom
Parmentier, Axel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-35
axel.parmentier@cermics.enpc.fr
Cermics, Champs sur Marne, France
Parreño, Francisco . . . . . . . . . . . . . . . . . . . . . . . . . . HB-05, HD-21
Francisco.Parreno@uclm.es
Mathematics, Universidad de Castilla-La Mancha, Albacete,
Spain
Parriani, Tiziano . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-11, HD-26
tiziano.parriani@unibo.it
DEIS, Università di Bologna, Perugia, Italy, Italy
Parwanto, Novia Budi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-32
noviabudi@bps.go.id
National Graduate Institute for Policy Studies (GRIPS), Japan
Pascal Simonsen Nielsen, Michael . . . . . . . . . . . . . . . . . . . TD-20
mpsn@dtu.dk
DTU, Copenhagen, Denmark
Pascoal, Marta . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-11, TE-37
marta@mat.uc.pt
Departamento de Matemática, Universidade de Coimbra,
INESC-Coimbra, Coimbra, Portugal
Pasia, Joseph . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-30
jmpasia@up.edu.ph
Institute of Mathematics, University of the Philippines, Quezon City, Philippines
Pasichny, Alexis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-44
alexis.pasichny@gmail.com
Students’ Science Association, National Technical University
of Ukraine, Kiev, Ukraine
Paslawski, Jerzy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-32, TD-45
jerzy.paslawski@put.poznan.pl
Civil and Environmental Eng., Poznan University of Technology, Poznan, Poland
Pastor, Rafael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-13
rafael.pastor@upc.edu
IOC, UPC, Barcelona, Spain
Paterakis, Stamatios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-09
stamatispaterakis@hotmail.co.uk
Electrical & Computer Engineering, National Technical University of Athens, Athens, Greece
Patino Rodriguez, Carmen . . . . . . . . . . . . . . . . . . . . . . . . . . FB-27
cepatino@gmail.com
Ingeniería Industrial, Universidad de Antioquia, Medellín,
Antioquia, Colombia
Patino-Echeverri, Dalia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-20
dalia.patino@duke.edu
Nicholas School of the Environment, Duke University,
Durham, NC, United States
Paucar-Caceres, Alberto . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-38
a.paucar@mmu.ac.uk
Business School, Manchester Metropolitan University,
AUTHOR INDEX
Manchester, United Kingdom
Pauwels, Benoît . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-18
benoit.pauwels@ifpen.fr
Mathématiques Appliquées, IFP Energies Nouvelles, RueilMalmaison, France
Pavlenko, Liudmyla . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-44
l.s.pavlenko@gmail.com
Academic Department, Ntuu Kpi, Kyiv, Ukraine, Ukraine
Pavlovic, Ljiljana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-39
pavlovic@kg.ac.rs
Department of Mathematics, Faculty of Natural Sciences and
Mathematics, Kragujevac, Serbia
Pawlak, Grzegorz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-13
grzegorz.pawlak@cs.put.poznan.pl
Institute of Computing Science, Poznan University of Technology, Poznan, Poland
Pólvora, Pedro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-24
pedro.polvora@gmail.com
Comenius University In Bratislava, Slovakia
Payne, Allan. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-42
allan.apayne@gmail.com
SORC, Saffron Walden, Essex, United Kingdom
Pérez Cervantes, Fernando . . . . . . . . . . . . . . . . . . . . . . . . . . HD-06
fernandoperez@uchicago.edu
Economics, Banco de Mexico, Mexco City, DF, Mexico
Pérez Galarce, Francisco Javier . . . . . . . . . . . . . . . . . . . . . HB-31
frperezga@gmail.com
Modelamiento y gestión industrial, Universidad de Talca,
Curicó, Chile
Pérez Sánchez, Carlos Javier . . . . . . . . . . . . . . . . . . . . . . . . HB-35
carper@unex.es
Matemáticas, Universidad de Extremadura, Cáceres, Spain
Pérez, M. Angeles . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-12, MA-39
angeles.perez@uv.es
Mathematics for Ecomomy, University of Valencia, Valencia,
Spain
Pérez-Gladish, Blanca . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-38
bperez@uniovi.es
Economía Cuantitativa, University of Oviedo, Oviedo, Asturias, Spain
Péton, Olivier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-04
olivier.peton@mines-nantes.fr
Automatic Control and Industrial Engineering, LUNAM Université, Ecole des Mines de Nantes, IRCCyN UMR CNRS
6597, Nantes, France
Pazgal, Amit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-15
pazgal@olin.wustl.edu
Olin School of Business, Washnigton University, United
States
Peano, Andrea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-43, HE-43
andrea.peano@unife.it
University of Ferrara, Ferrara, Italy
Pearman, Alan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-19
a.d.pearman@leeds.ac.uk
Leeds University Business School, University of Leeds,
Leeds, West Yorkshire, United Kingdom
385
AUTHOR INDEX
IFORS 2014 - Barcelona
Pearn, W. L. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-37
wlpearn@mail.nctu.edu.tw
Department of Industrial Engineering and Management, National Chiao Tung University, Hsinchu, Taiwan
Pentland, Alex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-03
sandy@media.mit.edu
Media Lab, Massachusetts Institute of Technology, Cambridge, MA, United States
Pecas Lopes, Joao . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-10
jpl@fe.up.pt
INESC Porto, Porto, Portugal
Perboli, Guido . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-45
guido.perboli@polito.it
Department of Control and Computer Engineering, Politecnico di Torino, Torino, Italy
Pechak, Olena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-31
opechak@hotmail.com
School of chemical engineering, National Technical University of Athens, Athens, Greece
Peixoto, Paulo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-38
marta.lopes75@gmail.com
Centre for Social Studies, University of Coimbra, Coimbra,
Portugal
Pekár, Juraj . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-02
pekar@euba.sk
Department of Operations Research and Econometrics, University of Economics in Bratislava, Bratislava, Slovakia
Pekec, Sasa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-06
pekec@duke.edu
Fuqua School of Business, Duke University, Durham, NC,
United States
Pelegrin, Blas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-18
pelegrin@um.es
Statistics and Operations Research, University of Murcia,
Spain
Pelizzari, Cristian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-07
pelizcri@eco.unibs.it
Department of Economics and Management, University of
Brescia, Italy, Brescia Bs, Italy
Pelizzon, Loriana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-38
pelizzon@unive.it
University of Venice, Venice, Italy
Pellegrini, Paola . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-01
paola.pellegrini@ifsttar.fr
IFSTTAR, France
Pelz, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-08, TB-21, MA-43
peter.pelz@fst.tu-darmstadt.de
Chair of Fluid Systems, Technische Universität Darmstadt,
Darmstadt, Germany
Penn, Marion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-13, HA-27
M.Penn@soton.ac.uk
School of Mathematics, University of Southampton,
Southampton, United Kingdom
Penn, Michal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-13
mpenn@ie.technion.ac.il
Industrial Engineering and Management, Technion, Haifa,
Israel
Penna, Puca Huachi . . . . . . . . . . . . . . . . . . . . . . . . . HD-02, FB-23
ppenna@ic.uff.br
Instituto de Computacao, Universidade Federal Fluminense,
Niteroi, RJ, Brazil
Pennings, Clint . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-19, FA-40
cpennings@rsm.nl
Rotterdam School of Management, Erasmus University,
Netherlands
386
Perea, Federico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-01, MB-14
perea@eio.upv.es
Estadística e Investigación Operativa Aplicadas y Calidad,
Universidad Politécnica de Valencia, Valencia, Spain
Pereira, Ana Rita . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-37
ritapereira.a@hotmail.com
Apartado 3008, Department of Mathematics, Coimbra, Portugal
Pereira, Javier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-23, HE-25
javier.pereira@udp.cl
Escuela de Ingeniería Informática, Universidad Diego Portales, Santiago, Chile
Pereira, Jordi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-13
jorge.pereira@upc.edu
Departament d’Organització d’Empreses, Universitat Politècnica de Catalunya, Barcelona, Spain
Pereira, Marcos Antonio . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-06
mapereira@feg.unesp.br
Departamento de Matemática, Universidade Estadual
Paulista - Campus de Guaratinguetá, Guaratinguetá, SP,
Brazil
Perelstein, Elizabeth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-06
eperelst@med.umich.edu
University of Michigan, Ann Arbor, United States
Pereverza, Kateryna . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-44
pereverza.kate@gmail.com
Students Science Association, National Technical University
of Ukraine, Kyiv, Ukraine
Perez Valdes, Gerardo . . . . . . . . . . . . . . . . . . . . . . . TD-10, MB-45
gerardoa.perez-valdes@sintef.no
Teknologi og Samfunn, SINTEF, Trondheim, Norway
Perez, Gloria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-45
gloria.perez@ehu.es
Applied Mathematics and Statistics and Operational Research, Universidad del País Vasco, Leioa, Spain, Spain
Perez, Ileana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-32
ileper@yahoo.com
Cali, Universidad San Buenaventura de Cali„ Cali, Valle del
Cauca, Colombia
Perez, Juan . . . . . . . . . . . . . . . . . . . . . . . . . . TB-02, MA-20, HB-25
jperez@uandes.cl
Industrial Engineering, Universidad de Los Andes de Chile,
Santiago, Región Metropolitana, Chile
Perez-Bernabeu, Elena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-41
elenapb@eio.upv.es
Applied Statistics, Operations Research, and Quality, Universitat Politèctica de Valencia, Alcoy, Spain
Perić, Tunjo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-14
tperic@efzg.hr
Department of Mathematics, University of Zagreb, Faculty
IFORS 2014 - Barcelona
of economics and business, Zagreb, Croatia
Persona, Alessandro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-13
alessandro.persona@unipd.it
Department of Management and Engineering (DTG), University of Padova, Vicenza, Italy
Perzina, Radomir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-26
perzina@opf.slu.cz
Department of Mathematical Methods in Economics, Silesian
University, School of Business, Karvina, Czech Republic
Peska, Ladislav . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-24
lpeska@seznam.cz
Software Engineering, Charles University, Prague, Czech Republic
Petricli, Gulcan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-44
gulcanp@uludag.edu.tr
Faculty of Economics and Administrative Sciences - Business
Administration, Uludag University, Nilufer, Bursa, Turkey
Petridis, Konstantinos . . . . . . . . . . . . . . . . . . . . . . ME-08, MD-38
kpetridi@fmenr.duth.gr
Department of Forestry and Management of the Environment
and Natural Resources, Democritus University of Thrace,
Orestiada, Greece
Petrot, Narin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-37
narinp@nu.ac.th
Mathematics, Naresuan University, MuangPhitsanulok, Phitsanulok, Thailand
Petrovic, Dobrila . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-26
D.Petrovic@coventry.ac.uk
Faculty of Engineering and Computing, Coventry University,
Coventry, United Kingdom
Petrovic, Slavica P. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-29
pslavica@kg.ac.rs
Faculty of Economics, University of Kragujevac, Kragujevac,
Serbia
Peura, Heikki . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-10
hpeura@london.edu
London Business School, United Kingdom
Pfetsch, Marc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-39
pfetsch@mathematik.tu-darmstadt.de
Discrete Optimization, Technische Universität Darmstadt,
Darmstadt, Germany
Pflug, Georg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-09, TE-09
georg.pflug@univie.ac.at
Department of Statistics and Decision Support Systems, University of Vienna, Vienna, Austria
Pham Dinh, Tao . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-17, TB-17
pham@insa-rouen.fr
INSA Rouen, Rouen, France
Phan, Duy Nhat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-17
duy-nhat.phan@univ-lorraine.fr
University of Lorraine, France
Philpott, Andy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-07, ME-20
a.philpott@auckland.ac.nz
Engineering Science, The University of Auckland, Auckland,
New Zealand
Philpott, Elly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-45
Elly.Philpott@beds.ac.uk
AUTHOR INDEX
Business School, University of Bedfordshire, Luton, Bedfordshire, United Kingdom
Phumchusri, Naragain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-37
naragain.p@chula.ac.th
Industrial Engineering, Chulalongkorn University, Bangkok,
Thailand
Pichler, Alois . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-07, HB-09
aloisp@ntnu.no
NTNU, Wien-Vienna, Vienna, Austria
Pickenhain, Sabine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-25
sabine.pickenhain@tu-cottbus.de
Mathematics, BTU Cottbus, Cottbus, Germany
Pickl, Stefan Wolfgang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-03
stefan.pickl@unibw.de
Department of Computer Science, UBw München
COMTESSA, Neubiberg-München, Bavaria, Germany
Pietrini, Maila . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-34
maila.pietrini@studenti.unicam.it
University of Camerino, Serra San Quirico, AN, Italy
Pietropaoli, Ugo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-12
ugo.pietropaoli@gmail.com
Dip. Informatica, Sistemi e Produzione, Un. Roma Tor Vergata, Roma, Italy
Pillon Torralba Fernandes, Jéssica . . . . . . . . . . . . . . . . . . . TD-18
pillon@fem.unicamp.br
Energy Department, UNICAMP, Campinas, São Paulo,
Brazil
Pineda Morente, Salvador . . . . . . . . . . . . . . . . . . . . . . . . . . ME-07
spinedamorente@gmail.com
Mathematics Department, University of Copenhagen, Copenhagen, Denmark
Pineda, Cristobal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-44
crpineda@ing.uchile.cl
Universidad de Chile, Santiago, Chile
Pino, José L. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-36
jlpino@us.es
Estadística e Investigación Operativa, Universidad de Sevilla,
Sevilla, Spain
Pino, Teresa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-36
mteresapinocaceres@gmail.com
Universidad de Sevilla, Spain
Pinson, Pierre . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-20
ppin@elektro.dtu.dk
Electrical Engineering, Technical University of Denmark,
Lyngby, Denmark
Pinto, Alberto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-30
aapinto1@gmail.com
Mathematics, University of Porto, Portugal
Pinto, Renan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-11, MA-17
renan_vicente@hotmail.com
Universidade Federal do Rio de Janeiro (UFRJ), Rio de
Janeiro, Rio de Janeiro, Brazil
Pirlot, Marc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-24, TE-29
marc.pirlot@fpms.ac.be
Mathematics and Operational Research, Université de Mons
UMONS, Faculté Polytechnique, Mons, Belgium
387
AUTHOR INDEX
IFORS 2014 - Barcelona
Pisciella, Paolo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-09, HE-09
paolo.pisciella@unibg.it
Department of Management, Economics and Quantitative
Methods, University of Bergamo, Italy
Pishchulov, Grigory . . . . . . . . . . . . . . . . . . . . . . . . . HE-21, MA-41
grigory.pishchulov@udo.edu
Faculty of Business, Economics and Social Sciences, TU
Dortmund University, Dortmund, Germany
Pisinger, David . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-01, TE-05
pisinger@diku.dk
DTU Management, Kgs. Lyngby, Denmark
Pitsoulis, Leonidas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-34
pitsouli@auth.gr
Electrical and Computer Engineering, Aristotle University of
Thessaloniki, Thessaloniki, Greece
Pitt, Martin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-39
m.pitt@exeter.ac.uk
Medical School, University of Exeter, Exeter, Devon, United
Kingdom
Piu, Francesco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-09
francesco.piu@gmail.com
Department of Management, Economics and Quantitative
Methods, University of Bergamo, Bergamo, Italy
Pla, LluisM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-36, MA-45
lmpla@matematica.udl.es
Mathematics, University of Lleida, Lleida, Spain
Pla-Santamaria, David . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-38
dplasan@esp.upv.es
Alcoy School, Technical University of Valencia, Alcoy, Spain
Placido, Antonio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-01
antonio.placido@unina.it
Department of Civil, Architectural and Environmental Engineering, ’Federico II’ University of Naples, Naples, NA, Italy
Plana, Isaac . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-02, ME-02
isaac.plana@uv.es
Matemáticas para la Economía y la Empresa, University of
Valencia, Valencia, Spain
Plateau, Agnès . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-36
aplateau@cnam.fr
Centre d’Étude et de Recherche en Informatique du Cnam,
Paris cedex 03, France
Plaumann, Daniel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-16
Daniel.Plaumann@uni-konstanz.de
Mathematics, University of Konstanz, Konstanz, Germany
Plavka, Ján . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-26
Jan.Plavka@tuke.sk
Department of Mathematics and Theoretical Informatics,
Technical University in Kosice, Kosice, Slovakia
Plitsos, Stathis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-12
stathisp@aueb.gr
Management Science and Technology, Athens University of
Economics and Business, Athens, Greece
Plociennik, Kai . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-18
kai.plociennik@itwm.fhg.de
Optimization, Fraunhofer ITWM, Kaiserslautern, Germany
Ploskas, Nikolaos. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-40
ploskasn@gmail.com
388
Department of Applied Informatics, University of Macedonia, Thessaloniki, Greece
Plubtieng, Somyot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-37
somyotp@nu.ac.th
Mathematics, Naresuan University, Phitsanulok, Thailand
Podkopaev, Dmitry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-18
dmitry.podkopaev@jyu.fi
Dept. of Mathematical Information Technology, University
of Jyväskylä, University of Jyväskylä, Finland
Pohl, Edward . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-45
epohl@uark.edu
Industrial Engineering, University of Arkansas, Fayetteville,
Arkansas, United States
Pohl, Letitia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-06
lpohl@uark.edu
Industrial Engineering, University of Arkansas, Fayetteville,
AR, United States
Pokharel, Shaligram . . . . . . . . . . . . . . . . . . . . . . . . . ME-19, TB-32
shaligram@qu.edu.qa
Qatar University, Doha, Qatar
Poledica, Ana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-26
apoledica@fon.bg.ac.rs
Faculty of Organizational Sciences, Belgrade, Serbia
Poler, Raul . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-26
rpoler@cigip.upv.es
Research Centre on Production Management and Engineering, Universidad Politecnica de Valencia, Alcoy, Alicante,
Spain
Polotski, Vladimir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-13
Vladimir.Polotski@etsmtl.ca
Mechanical Engineering Department, Ecole de Technologie
Supérieure, Montreal, Québec, Canada
Polyakov, Yury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-16
polyakovyury@gmail.com
Moscow Institute of Physics and Technology, Moscow, Russian Federation
Pomar, Candido . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-36
pomarc@agr.gc.ca
Agriculture and Agri-Food Canada, Lennoxville (Qc),
Canada
Ponomarenko, Alexander . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-34
aponom84@gmail.com
Laboratory of Algorithms and Technologies for Networks
Anlysis, National Research University Higher School of Economics, Nizhny Novgorod, Russian Federation
Pons, Montserrat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-27
montserrat.pons@upc.edu
Applied Mathematics 3, Technical University of Catalonia,
Manresa, Spain
Ponsich, Antonin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-06
aspo@correo.azc.uam.mx
Sistemas, Universidad Autónoma Metropolitana - Azcapotzalco, Mexico
Popescu, Ioana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-15
ioana.popescu@insead.edu
Decision Sciences, INSEAD, Singapore, Singapore
Popovic, Milena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-34
IFORS 2014 - Barcelona
milenap@fon.bg.ac.rs
Laboratory for Operational Research "Jovan Petrić", Faculty
of Organizational Sciences, Belgrade, Serbia
Popovic, Zarko . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-29
zpopovic@eknfak.ni.ac.rs
Faculty of Economics, University of Nis, Nis, Serbia, Serbia
Portela, Maria. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-14
csilva@porto.ucp.pt
Faculdade de Economia e Gestão, Universidade Católica Portuguesa, Porto, Portugal
Porumbel, Daniel . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-06, TE-40
daniel.porumbel@univ-artois.fr
LGI2A & IUT Béthune, Universite Artois, Bethune, France
Pospelov, Alexis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-18, TE-18
alexis.pospelov@datadvance.net
Datadvance, Russian Federation
Poss, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-45
michael.poss@hds.utc.fr
Cnrs, Utc, France
Possani, Edgar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-14
epossani@itam.mx
Department of Mathematics, Instituto Tecnologico Autonomo de Mexico, Mexico City, D.F. - Mexico, Mexico
Postmus, Douwe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-29, TA-39
d.postmus@umcg.nl
Epidemiology, University Medical Center Groningen,
Netherlands
Posypkin, Mikhail . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-18
mposypkin@gmail.com
Iitp Ras, Cc Ras, Russian Federation
Potgieter, Linke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-07
lpotgieter@sun.ac.za
Logistics, Stellenbosch University, Matieland, Western Cape,
South Africa
Potharst, Rob . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-24
potharst@ese.eur.nl
Erasmus School of Economics, Rotterdam, Netherlands
Potpinkova, Eva . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-12
eva.potpinkova@student.upjs.sk
P.J. Safarik University, Kosice, Slovakia
Pöttgen, Philipp . . . . . . . . . . . . . . . . . . . . . . FA-08, TB-21, MA-43
philipp.poettgen@fst.tu-darmstadt.de
Chair of Fluid Systems, Technische Universität Darmstadt,
Germany
Potts, Chris . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-13, MA-39
C.N.Potts@soton.ac.uk
School of Mathematics, University of Southampton,
Southampton, Hampshire, United Kingdom
Potvin, Jean-Yves . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-41
potvin@IRO.UMontreal.CA
Centre de recherche sur les transports, Université de Montréal, Montréal, Québec, Canada
Poudel, Diwakar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-07
diwakarpoudel@yahoo.com
Business and Management Science, NHH, Norway, Bergen,
Norway
AUTHOR INDEX
Pourakbar, Morteza . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-32
MPourakbar@rsm.nl
Technology and Operations Management, Rotterdam School
of Management, Erasmus University, Netherlands
pourasghari, hamid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-36
hamid.pourasghari@gmail.com
Health Policy, Iran medical science univercity, Iran, Islamic
Republic Of
Pourmoayed, Reza . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-36
rpourmoayed@econ.au.dk
Department of Economics and Business, Aarhus University,
Aarhus, Aarhus, Denmark
Poursaeidi, Mohammad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-25
mohammad.poursaeidi@innovativescheduling.com
Innovative Scheduling, Gainesville, FL, United States
Powell, Warren . . . . . . . . . . . . . . . . . . . . . . FB-20, ME-20, MA-45
powell@princeton.edu
Department of Operations Research and Financial Engineering, Princeton University, Princeton, NJ
Pozehl, William . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-06
pozewil@umich.edu
University of Michigan, Ann Arbor, United States
Pozo, Miguel Angel . . . . . . . . . . . . . . . . . . . . . . . . . . HD-01, TE-44
miguelpozo@us.es
Statistics and OR, Universidad de Sevilla, Seville, Spain
Pradeau, Thomas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-28
thomas.pradeau@enpc.fr
CERMICS, Université Paris-Est, Marne la Vallée, France
Pradenas, Lorena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-02
lpradena@udec.cl
Ingeniería Industrial, Universidad de Concepción, Concepción, Concepción, Chile
Pradhananga, Rojee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-32
rojee@qu.edu.qa
Department of Mechanical and Industrial Engineering, Qatar
University, Doha, Qatar
Prasad, Ashutosh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-27
aprasad@utdallas.edu
UT Dallas, United States
Pratt, Rob . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-21
rob.pratt@sas.com
SAS Institute, Cary, North Carolina, United States
Pretorius, Philip . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-22
Philip.pretorius@nwu.ac.za
School of Information Technology, North-West University,
Vanderbijlpark, North-West, South Africa
Priese, Benjamin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-21
benjamin.priese@basf.com
BASF, Germany
Prigent, Jean-Luc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-34
jean-luc.prigent@u-cergy.fr
ThEMA, University of Cergy-Pontoise, Cergy-Pontoise,
France
Prior, Diego . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-10
diego.prior@uab.es
Departament d’Economia de l’Empresa, Universitat Autonoma de Barcelona, Barcelona, Catalunya, Spain
389
AUTHOR INDEX
IFORS 2014 - Barcelona
Prudente, Maria Cheryl . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-20
cheprudent@yahoo.com
ALTERPLAN, Quezon City, Philippines
Pryn, Marie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-37
mapry@transport.dtu.dk
Technical University of Denmark, Kgs. Lyngby, Denmark
Psaraftis, Harilaos N. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-05
hnpsar@gmail.com
Technical University of Denmark, Lyngby, Denmark
Psarras, John . . . . . . . . . . . . . . . . . . . . . . . . TB-31, MD-34, HD-42
john@epu.ntua.gr
Electrical & Computer Engineering, National Technical University of Athens, Athens, Greece
Ptak-Chmielewska, Aneta . . . . . . . . . . . . . . . . . . . . . . . . . . ME-30
aptak@sgh.waw.pl
Institute of Statistics and Demography, Warsaw School of
Economics, Warsaw, Poland
Puchert, Christian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-39
puchert@or.rwth-aachen.de
Operations Research, RWTH Aachen University, Aachen,
Germany
Puchinger, Jakob . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-42
jpuchinger@gmail.com
Mobility, AIT Austrian Institute of Technology GmbH, Wien,
Österreich, Austria
Pucihar, Andreja . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-42
andreja.pucihar@fov.uni-mb.si
Department of Information Systems, eCenter, University of
Maribor, Faculty of Organizational Sciences, Kranj, Slovenia
Puerto, Justo . . . . . . . . . . HA-03, HD-03, HE-03, TE-03, TE-44
puerto@us.es
Estadistica e I.O., Universidad de Sevilla, Sevilla, Spain
Puetz, Markus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-43
markus.puetz@whl-lahr.de
Chair, Department of Managerial Accounting and Control,
WHL Graduate School of Business and Economics, Lahr,
Baden-Wuerttemberg, Germany
Punkka, Antti . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-31
antti.punkka@aalto.fi
Department of Mathematics and Systems Analysis, Aalto
University School of Science, Aalto, Finland
Punnen, Abraham . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-02, MB-11
apunnen@sfu.ca
Simon Fraser University, Canada
Punzo, Vincenzo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-04
vinpunzo@unina.it
Transportation Engineering, University of Naples, Napoli,
Italy, Italy
Pureza, Vitoria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-02
vpureza@dep.ufscar.br
Production Engineering, Universidade Federal de Sao Carlos,
Sao Carlos, Sao Paulo, Brazil
Purice, Victoria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-38
Victoria.Purice@UGent.be
Department of Economics, Ghent University, Ghent, Belgium
Pusane, Ali Emre . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-31
390
ali.pusane@boun.edu.tr
Department of Electrical and Electronics Engineering,
Bogazici University, Istanbul, Turkey
Puttkammer, Karen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-13
k.puttkammer@tu-bs.de
Institute of Automotive Management and Industrial Production, Technische Universität Braunschweig, Braunschweig,
Germany
Qablawi, Mona . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-21
mq090298@qu.edu.qa
Mechanical and Industrial Engineering, Qatar University,
Doha, Qatar, Qatar
Quadrifoglio, Luca . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-42
quadrifo@tamu.edu
Civil Engineering, Texas A&M University, College Station,
Texas, United States
Quaglietta, Egidio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-01
e.quaglietta@tudelft.nl
Transport & Planning, TU Delft, Delft, Netherlands
Quariguasi, Joao . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-08
joao.quariguasifrotaneto@manchester.ac.uk
MACE, University of Manchester, Manchester, United Kingdom
Quelhas, Ana Paula . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-32
aquelhas@iscac.pt
ISCAC, Polytechnic Institute of Coimbra, Coimbra, Portugal
Quilliot, Alain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-13
quilliot@isima.fr
IT, LIMOS, Clermont-Ferrand, France
Quintanilla, Israel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-36
iquinta@cgf.upv.es
Cartographic Engineering, Universitat Politécnica de Valencia, Valencia, Spain
Quintanilla, Sacramento . . . . . . . . . . . . . . . . . . . . . FB-12, MA-39
Maria.Quintanilla@uv.es
Matemáticas para la Economía y la Empresa, University of
Valencia, Valencia, Spain
Quinteros, Martin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-11
martinq46@gmail.com
Industrial Engineering, University of Chile, Santiago, Chile
Qureshi, Ali . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-06, ME-42
aligul@kiban.kuciv.kyoto-u.ac.jp
Urban Management, Kyoto University, Kyoto, Japan
R. M. da Costa, Geraldo . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-43
geraldo@sc.usp.br
Electrical Engineering, São Paulo University, Sao Carlos,
Sao Paulo, Brazil
Rabe, Markus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-41
markus.rabe@tu-dortmund.de
MB/ITPL, TU Dortmund, Dortmund, Germany
Rabiei, Nima . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-14
nima.rabiei@upc.edu
Applied Mathematics III, LACAN, Barcelona, Spain
Rademaker, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-24
michael.rademaker@ugent.be
Departement of Mathematical Modelling, Statistics and
Bioinformatics, Ghent University, Gent, Belgium
IFORS 2014 - Barcelona
Radjef, Mohammed Said . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-26
msradjef@hotmail.com
Laboratory LAMOS, University of Bejaia, Bejaia, Algeria
Radjef, Mohammed Said . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-25
radjefms@yahoo.fr
Operational Research, University of Bejaia, Bejaia, Algeria
Rado, Omar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-22
omar.rado@gmail.com
Università degli Studi di Padova, Padova, Italy, Padova, Italy
Raffray, Guilhem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-18
guilhem.raffray@cirad.fr
UMR Qualisud, CIRAD, Montpellier Cedex 5, France
Rafiey, Arash . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-02
arashr@sfu.ca
Computing Science, Simon Fraser University, Burnaby, BC,
Canada
Raghavan, S. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-15
raghavan@umd.edu
The Robert H. Smith School of Business, University of Maryland, College Park, MD, United States
Raghavan, Shalini . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-23
ShaliniRaghavan@fico.com
Analytic Offer Management, FICO, Roseville, MN, United
States
Rai, Varun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-20
varun.rai@mail.utexas.edu
LBJ School of Public Affairs, University of Texas at Austin,
Austin, Texas, United States
Rainer, Cornelia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-40
cornelia.rainer@edu.uni-graz.at
Produktion und Logistik, Karl-Franzens-Universität Graz,
Graz, Austria
Raith, Andrea. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-44
a.raith@auckland.ac.nz
Engineering Science, The University of Auckland, Auckland,
New Zealand
Raith, Sydney . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-35
sydny.raith@gmail.com
University of Denver, Denver, CO, United States
AUTHOR INDEX
ted@lehigh.edu
Lehigh University, United States
Ramalhinho Lourenco, Helena . . . . . . . . . . . . . . . HB-40, TE-41
helena.ramalhinho@upf.edu
UPF- Barcelona GSE, Barcelona, Spain
Ramanathan, Ramakrishnan . . . . . . . . . . . . . . . . . . . . . . . . HA-45
ram.ramanathan@beds.ac.uk
Business School, University of Bedfordshire, Luton, Bedfordshire, United Kingdom
Ramdane, Maamri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-23
rmaamri@yahoo.fr
Constantine University, Constantine, Algeria
Ramik, Jaroslav . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-26
ramik@opf.slu.cz
Dept. of Math. Methods in Economics, Silesian University,
School of Business, Karvina, Czech Republic
Ramirez Muñoz, Alejandra . . . . . . . . . . . . . . . . . . . . . . . . . . TB-40
aleja.r.m@hotmail.com
Antioquia, Institucion Universitaria Colegio Mayor de Antioquia, Medellin, Colombia
Ramirez, Hector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-17
hramirez@dim.uchile.cl
Mathematical Engineering Department, Universidad de
Chile, Santiago, RM, Chile
Ramirez, Javier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-06
jararo@azc.uam.mx
Sistemas, Universidad Autonoma Metropolitana, Mexico,
Distrito Federal, Mexico
Ramjee, Shivani . . . . . . . . . . . . . . . . . . . . . MD-22, FA-34, HA-45
shivani.ramjee@uct.ac.za
Actuarial Science, University of Cape Town, Cape Town,
Western Cape, South Africa
Ramli, Razamin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-23
razamin@uum.edu.my
Dept of Decision Science, Universiti Utara Malaysia, Sintok,
Kedah, Malaysia
Ramond, François . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-01
francoisramond@gmail.com
Innovation & Research, SNCF, PARIS Cedex 12, France
Rajkovic, Uros . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-42
uros.rajkovic@fov.uni-mb.si
University of Maribor, Faculty of Organizational Sciences,
Kranj, Slovenia
Ramos, Andres . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-10, TB-10
andres.ramos@iit.upco.es
Departamento de Organizacion Industrial - Instituto de Investigacion Tecnologica, Universidad Pontificia Comillas,
Madrid, Spain
Rajkovic, Vladislav . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-42, FB-42
vladislav.rajkovic@fov.uni-mb.si
University of Maribor, Faculty of Organizational Sciences,
Kranj, Slovenia
Ramos, Andres . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-10
andres.ramos@upcomillas.es
Institute for Research in Technology, Universidad Pontificia
Comillas, Madrid, Madrid, Spain
Rakha, Hesham . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-04
hrakha@vt.edu
Virginia Tech, Virginia Tech, Blacksburg, Virginia, United
States
Ramos, Angel Manuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-29
angel@mat.ucm.es
Universidad Complutense de Madrid, Madrid, Spain
Rakrouki, Mohamed Ali . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-14
rakroukidali2003@yahoo.fr
Computer Science Department, Taibah University, Madinah,
Tunisia
Ralphs, Ted . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-30
Ramos, António . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-21
deg09006@fe.up.pt
INESC TEC, Faculty of Engineering, University of Porto,
Portugal
Ramos, María Camila . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-15
mmramos@uc.cl
391
AUTHOR INDEX
IFORS 2014 - Barcelona
Pontificia Universidad Católica de Chile, Chile
Ramsundar, Ramajothi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-08
Ramajothi@controlling.rwth-aachen.de
RWTH Aachen University, Aachen, Germany
Ramsundar, Ramajothi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-08
Ramsundar@controlling.rwth-aachen.de
RWTH Aachen University, Aachen, Germany
Ranade, Abhiram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-01
ranade@cse.iitb.ac.in
Computer Science and Engineering, IIT Bombay, Mumbai,
Maharashtra, India
Rand, Graham . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-28
g.rand@lancaster.ac.uk
Dept. of Management Science, Lancaster University, Lancaster, Lancashire, United Kingdom
Rangel, Socorro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-21, ME-41
socorro@ibilce.unesp.br
UNESP - Sao Paulo State University, S.J. do Rio Preto, São
Paulo, Brazil
Rangoaga, Moeti . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-26
rangomj@unisa.ac.za
Decision Sciences, UNISA, Pretoria, South Africa
Ranyard, John . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-21
jranyard@cix.co.uk
Retired, Hope Valley, Derbyshire, United Kingdom
Rashidi Bajgan, Hannaneh . . . . . . . . . . . . . . . . . . . . . . . . . . HE-27
hannaneh.rashidi@gmail.com
Business & Management, Luiss Guido Carli University,
Rome, Lazio, Italy
Rasinmäki, Jussi . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-36, MB-36
jussi.rasinmaki@simosol.fi
Simosol Oy, Riihimäki, Finland
Ratajczak-Ropel, Ewa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-12
ewra@am.gdynia.pl
Department of Information Systems, Gdynia Maritime University, Poland
Ratier, Olivier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-03
olivier.ratier@amadeus.com
Amadeus, France
Rauner, Marion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-39
marion.rauner@univie.ac.at
Dept. Innovation and Technology Management, University
of Vienna, Vienna, Austria
Raupp, Fernanda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-03
nanda@impa.br
LNCC, Petropolis, Rio de Janeiro, Brazil
Rausch, Alexandra . . . . . . . . . . . . . . . . . . . . . . . . . MB-44, MD-44
Alexandra.Rausch@aau.at
Dept. for Controlling and Strategic Management, Klagenfurt,
Austria
Ravaja, Niklas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-18
Niklas.Ravaja@Aalto.fi
Aalto University School of Business, Helsinki, Finland
Raviv, Tal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-13
talraviv@eng.tau.ac.il
Department of Industrial Engineering, Tel Aviv University,
392
Tel Aviv, Israel
Ray, Sanjog . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-23
sanjogr@iimidr.ac.in
Information Systems, Indian Institute of Management Indore,
Indore, Madhya Pradesh, India
Raz, David . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-43
davidra@hit.ac.il
Management of Technology, Holon Institute of Technology,
Holon, Israel
Recalde, Diego . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-27
diego.recalde@epn.edu.ec
Mathematics, Escuela Politécnica Nacional, Quito, Pichincha, Ecuador
Redoblado, Sarah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-20
sarah_redoblado@yahoo.com
ALTERPLAN, Quezon City, Philippines
Redutskiy, Yury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-05
yury.redutskiy@himolde.no
Faculty of Economics, Informatics and Social Sciences
(ØIS), Molde University College, Molde, Norway
Reed, Joshua . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-34
jreed@stern.nyu.edu
IOMS, New York University, New York, NY, United States
Regan, Amelia C. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-25
aregan@uci.edu
Computer Science, University of California, Irvine, Irvine,
California, United States
Reichl, Harald . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-33
harald.reichl@wien.gv.at
R.U.S.Z. GmbH, Viena, Austria
Reig, Javier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-38
javier.reig.mullor@gmail.com
Universidad Miguel Hernandez de Elche, Alcoy, Alicante,
Spain
Reimann, Marc . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-04, MD-33
marc.reimann@uni-graz.at
Lehrstuhl für Produktion und Logistiks Management, Universität Graz, Graz, Austria
Reindorp, Matthew . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-24
m.j.reindorp@tue.nl
Eindhoven University of Technology, Eindhoven, Netherlands
Reinhardt, Line . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-05
lbre@dtu.dk
Management Engineering, The Technical University of Denmark, Kngs Lyngby, Denmark
Reisach, Ulrike . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-28
ulrike.reisach@hs-neu-ulm.de
Information Management Faculty, Neu-Ulm University of
Applied Sciences, Neu-Ulm, Bavaria, Germany
Reizes, Erwin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-44
bereizes@adinet.com.uy
O.R., Fac.Ing./UdelaR,Uruguay, Montevideo, Uruguay
Rekik, Monia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-41
Monia.Rekik@cirrelt.ca
Operations and decision systems, Laval University, Quebec,
Quebec, Canada
IFORS 2014 - Barcelona
Relvas, Susana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-44
susanaicr@ist.utl.pt
DEG, IST, Lisbon, Portugal
Renault, Jérôme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-24
jerome.renault@tse-fr.eu
Gremaq- Tse, Université Toulouse 1 Capitole, Toulouse,
France
Rendl, Franz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-17
franz.rendl@uni-klu.ac.at
Mathematics, Alpen-Adria-Universität Klagenfurt, Klagenfurt, Austria
Rentería Guerrero, Luis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-14
lrenter@guaymas.uson.mx
Economía, Universidad de Sonora, Hermosillo„ Sonora,
Mexico
Reodecha, Manop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-37
manop.r@chula.ac.th
Industrial Engineering, Chulalongkorn University, Bangkok,
Thailand
Repoussis, Panagiotis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-14
prepousi@aueb.gr
Howe School of Technology Management, Stevens Institute
of Technology, Hoboken, New Jersey, United States
Repoux, Martin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-06
martin.repoux@epfl.ch
ENAC, EPFL, Lausanne, Switzerland
Requejo, Cristina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-41
crequejo@ua.pt
Mathematics & CIDMA, University of Aveiro, Aveiro, Portugal
Resende, Mauricio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-39
mgcr@research.att.com
Algorithms & Optimization Research, AT&T Labs Research,
Florham Park, NJ, United States
Resic, Sead . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-14
sresic@gmail.com
Mathematics, Faculty for natural sciences and mathematics,
Tuzla, Bosnia And Herzegovina
Rethmann, Jochen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-39
jochen.rethmann@hsnr.de
Faculty of Electrical Engineering and Computer Science,
Niederrhein University of Applied Sciences, Krefeld, Germany
AUTHOR INDEX
Optimization, Zuse-Institut Berlin, Berlin, Germany
Revie, Matthew . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-20
matthew.j.revie@strath.ac.uk
University of Strathclyde, Glasgow, United Kingdom
Rey, Pablo A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-02, MD-44
pablo.rey@udp.cl
Industrial Engineering, Universidad Diego Portales, Santiago, Chile
Reyer, Ivan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-16
reyer@forecsys.ru
Dorodnicyn Computing Centre of RAS, Moscow, Russian
Federation
Reyes Chamorro, Lorenzo . . . . . . . . . . . . . . . . . . . . . . . . . . HD-20
lorenzo.reyes@epfl.ch
École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
Rialp, Josep . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-42
josep.rialp@uab.es
Departamento de Economía de la Empresa, Universitat
Autónoma de Barcelona, Bellaterra, Catalonia, Spain
Riane, Fouad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-19
fouad.riane@uclouvain-mons.be
Catholic University of Louvain - Mons Campus, Mons, Belgium
Ribal, Javier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-36
frarisan@esp.upv.es
Economía y Ciencias Sociales, Universitat Politecnica de Valencia, Valencia, Spain
Ribas, Gabriela . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-29
gabipribas@yahoo.com
Industrial Department, Catholic University, Rio de Janeiro,
Rio de Janeiro
Ribeiro, Bruno . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-29
agrelio@ele.puc-rio.br
Eletric Engeneering, PUC-Rio, Rio de Janeiro, Rio de
Janeiro, Brazil
Ricca, Federica . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-03
federica.ricca@uniroma1.it
University of Rome, Rome, Italy
Richter, Knut . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-40, MA-41
richter@europa-uni.de
Faculty of Economics, St. Petersburg State university, St.
Petersburg, Russian Federation
Rettieva, Anna . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-35
annaret@krc.karelia.ru
Institute of Applied Mathematical Research Karelian Research Centre of RAS, Petrozavodsk, Russian Federation
Rider, Marcos J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-10
mjrider@dee.feis.unesp.br
Departamento de Engenharia Elétrica, Universidade Estadual
Paulista, ILha Solteira, Sao paulo, Brazil
Rettke, Katja . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-33
katja.rettke@uni-jena.de
Department of Business Statistics, Friedrich Schiller University of Jena, Jena, Thuringia, Germany
Rieck, Julia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-12
julia.rieck@tu-clausthal.de
Operations Research Group, Clausthal University of Technology, Clausthal-Zellerfeld, Germany
Reuter, Melanie . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-08, ME-39
melanie.reuter@kit.edu
Institute for Operations Research, Karlsruhe Institute of
Technology (KIT), Germany
Ried, Sabrina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-08
Sabrina.Ried@kit.edu
Chair of Energy Economics and Project Competence-E, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Reuther, Markus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-01
reuther@zib.de
Riener, Cordian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-16
cordian.riener@aalto.fi
393
AUTHOR INDEX
IFORS 2014 - Barcelona
Aalto Science Institute, Aalto University, Helsinki, Finland
Ries, Jörg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-33
ries@bwl.tu-darmstadt.de
Department of Law and Economics, TU Darmstadt, Darmstadt, Germany
Rinaldi, Francesco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-25
rinaldi@math.unipd.it
Matematica, Università di Padova, Italy
Rincón-García, Eric Alfredo . . . . . . . . . . . . . . . . . . . . . . . . . FB-06
rigaeral@correo.azc.uam.mx
SISTEMAS, Universidad Autonoma Metropolitana, MEXICO, Distrito Federal, Mexico
Ringgaard Kristensen, Anders . . . . . . . . . . . . . . . . . . . . . . HD-36
ark@sund.ku.dk
Department of Large Animal Sciences, Faculty of Health and
Medical Sciences, Copenhagen, Denmark
Rios, Eyder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-23
eyder.rios@gmail.com
IC, UFF, Brazil
Rios-Insua, David . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-23, TD-31
david.rios@urjc.es
Rey Juan Carlos University, Mostoles, Madrid, Spain
Ripatti, Artem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-21
ripatti@inbox.ru
Ufa SATU, Russian Federation
Riquelme, Fabián . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-22
farisori@lsi.upc.edu
Departament de Llenguatges i Sistemes Informatics, Universitat Politècnica de Catalunya, Barcelona, Spain
Ritzenhofen, Ingmar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-09
ingmar.ritzenhofen@whu.edu
Kuehne Foundation Endowed Chair in Logistics Management, WHU - Otto Beisheim School of Management, Vallendar, Germany
Rivera, Orlando . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-29
orlandoriveraletelier@gmail.com
Universidad Adolfo Ibañez, Santiago, Chile
Rivier, Michel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-10
michel.rivier@iit.upcomillas.es
Instituto de Investigación Tecnológica, Universidad Pontificia Comillas, Madrid, Spain
Robenek, Tomás . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-01
tomas.robenek@epfl.ch
Enac Inter Transp-or, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
Roberti, Roberto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-11
roberto.roberti6@unibo.it
DEI, University of Bologna, Bologna, Italy
Robinson, Stewart . . . . . . . . . . . HD-23, MA-23, ME-23, TD-44
s.l.robinson@lboro.ac.uk
School of Business and Economics, Loughborough University, Loughborough, United Kingdom
Roboam, Xavier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-06
roboam@laplace.univ-tlse.fr
Université de Toulouse, LAPLACE (Laboratory on Plasma
and Conversion of Energy), Toulouse, France
394
Roca-Riu, Mireia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-06
mireia.roca-riu@upc.edu
CENIT - Centre for Innovation in Transport, Barcelona,
Spain
Rocchi, Lucia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-36
lucia.rocchi@unipg.it
DSEEA, University of Perugia, Perugia, Italy
Rocha, Humberto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-39
hrocha@mat.uc.pt
Inesc - Coimbra, Portugal
Rocha, Paula . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-09
mprocha@fe.up.pt
Dep. of Electrical and Computer Engeneering, Faculty of
Engineering, University of Porto, Porto, Portugal
Rocha, Pedro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-21
pmonteirorocha@sapo.pt
INESC TEC, Faculdade de Engenharia, Universidade do
Porto, Porto, Portugal
Rodrigues Costa, Fabricio . . . . . . . . . . . . . . . . . . . . . . . . . . HD-19
fabricio.costa@indt.org.br
Nokia Institute of Technology - INdT, Manaus, Amazon,
Brazil
Rodrigues, Antonio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-33
ajrodrigues@fc.ul.pt
CIO-FCUL, University of Lisbon, Lisboa, Portugal
Rodrigues, Rui . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-21
ruirodrig@fe.up.pt
INESC TEC, Faculdade de Engenharia, Universidade do
Porto, Porto, Portugal
Rodriguez, Joaquin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-01
joaquin.rodriguez@ifsttar.fr
Estas, Ifsttar, Villeneuve d’Ascq, France
Rodriguez, Victoria . . . . . . . . . . . . . . . . . . . . . . . . . TB-08, MD-41
vrodriguez@unav.es
Departamento de Empresa, Universidad de Navarra, Pamplona, Navarra, Spain
Rodriguez-Chia, Antonio Manuel . . . . . . . . . . . . HA-03, HB-03
antonio.rodriguezchia@uca.es
Estadistica e IO, Universidad de Cádiz, Puerto Real (Cadiz),
Cadiz, Spain
Rodriguez-Espindola, Oscar . . . . . . . . . . . . . . . . . . . . . . . . . HE-37
rodrigoe@aston.ac.uk
Operations and Information Management, Aston University,
Birmingham, West Midlands, United Kingdom
Roels, Guillaume . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-22
groels@anderson.ucla.edu
Anderson School of Management, UCLA, Los Angeles, CA
Rogerie, Jerome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-41
rogerie@fr.ibm.com
Software Group, France Lab, Ilog Optimisation, IBM, Gentilly, France
Rogetzer, Patricia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-07
patricia.rogetzer@wu.ac.at
Department of Information Systems and Operations, WU
Wien - Vienna University of Economics and Business, Vienna, Vienna, Austria
Rojas Lopez, Jose Alberto . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-32
IFORS 2014 - Barcelona
jarojas2@usbcali.edu.co
Universidad San Buenaventura de Cali, Cali, Colombia
Roma, Joan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-38
ddsierra@yahoo.com
Innova Institute, Barcelona, Barcelona, Spain
Romero Morales, Dolores . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-25
dolores.romero-morales@sbs.ox.ac.uk
Said Business School, University of Oxford, Oxford, United
Kingdom
Roncoli, Claudio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-04
croncoli@dssl.tuc.gr
Dynamic Systems & Simulation Laboratory, Technical University of Crete (TUC), Chania, Greece
Rönnqvist, Mikael . . . . . TA-22, HE-36, MD-36, ME-36, TD-36
mikael.ronnqvist@nhh.no
Département de génie mécanique, Québec, Canada
Roorda, Matthew . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-06
roordam@ecf.utoronto.ca
Civil Engineering, University of Toronto, Toronto, Ontario,
Canada
Roos, Kees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-14
c.roos@tudelft.nl
EWI, TU Delft, Delft, ZH, Netherlands
Ropars-Collet, Carole . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-36
carole.ropars@agrocampus-ouest.fr
Umr Smart, Rennes, France
Ropke, Stefan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-05, MB-42
sr@transport.dtu.dk
Department of Transport, Technical University of Denmark,
Kgs. Lyngby, Denmark
Rosati, Adolfo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-36
adolfo.rosati@entecra.it
CRA, Rome, Italy, Italy
Rosset, Christian . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-36, MB-36
christian.rosset@bfh.ch
School of Agricultural, Forest and Food Sciences HAFL,
Bern University of Applied Sciences BFH, Zollikofen, BE,
Switzerland
Rossi, Roberto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-13
robros@gmail.com
Business School, University of Edinburgh, Edinburgh, United
Kingdom
Rotela Junior, Paulo . . . . . . . . . . MA-30, MB-32, HB-34, TB-34
paulo.rotela@gmail.com
IEPG - Instituto de Engenharia de Produção e Gestão,
UNIFEI - Universidade Federal de Itajubá, Itajubá, Minas
Gerais, Brazil
Rötzel, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-15
peter.roetzel@bwi.uni-stuttgart.de
University of Stuttgart, Germany
Roupin, Frederic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-11
frederic.roupin@lipn.univ-paris13.fr
Lipn, Cnrs-umr 7030, Université Paris 13, Villetaneuse,
France
Rouse, Jack . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-21
jack.rouse@sas.com
SAS Institute, Cary, NC, United States
AUTHOR INDEX
Rousseau, Louis-Martin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-41
louism@crt.umontreal.ca
Centre de recherche sur les transports, Université de Montréal, Canada
Rouwette, Etienne . . . . . . . . . . . . . . . . . . . . . . . . . . MA-23, MB-23
e.rouwette@fm.ru.nl
Nijmegen School of Management, Radboud University Nijmegen, Nijmegen, Netherlands
Rowley, Ian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-27
I.T.Rowley@soton.ac.uk
Mathematics, University of Southampton, Southampton,
United Kingdom
Royer, Clément . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-14
clement.royer@enseeiht.fr
ENSEEIHT-IRIT, Toulouse, France
Rozenknop, Antoine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-28
antoine.rozenknop@lipn.univ-paris13.fr
LIPN, CNRS-UMR 7030, Université Paris 13, France
Rozycki, Rafal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-12
rafal.rozycki@cs.put.poznan.pl
Institute of Computing Science, Poznan University of Technology, Poznan, Poland
Ruan, Ning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-39
n.ruan@federation.edu.au
Federation University Australia, Australia
Rubaszewski, Julie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-40
julie.rubaszewski@utt.fr
LOSI, Université de Technologie de Troyes, Troyes, France
Rubio Blanco, José Antonio . . . . . . . . . . . . . . . . . . . . . . . . . TD-31
jose.rubio@urjc.es
Universidad Rey Juan Carlos, Spain
Rubio, Sergio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-08, TB-44
srubio@unex.es
Business Management & Sociology, Universidad de Extremadura, Badajoz, Spain
Ruckmann, Jan-J . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-26
Jan-Joachim.Ruckmann@ii.uib.no
Department of Informatics, University of Bergen, Bergen,
Norway
Rud, Linda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-20
linda.rud@nhh.no
Business and Management Science, NHH Norwegian School
of Economics, Bergen, Norway
Rudec, Tomislav . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-11
Tomislav.Rudec@etfos.hr
Faculty of Electrical Engineering, University of Osijek, Osijek, Croatia
Rudek, Agnieszka . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-14
agnieszka.wielgus@pwr.wroc.pl
Department of Systems of Signal Processing, Wroclaw University of Technology, Poland
Rudek, Radoslaw . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-14
radoslaw.rudek@ue.wroc.pl
Institute of Business Informatics, Wroclaw Univeristy of
Economics, Wroclaw, Poland
Rüdlin, Arndt. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-43
395
AUTHOR INDEX
IFORS 2014 - Barcelona
arndt.ruedlin@vwl.uni-freiburg.de
BWL Seminar I, Albert-Ludwigs-Universität Freiburg,
Freiburg, Germany
Rusyaeva, Olga . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-37
olga.rusyaeva@the-klu.org
Kuehne Logistics University, Germany
Rudnick, Hugh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-10
hrudnick@ing.puc.cl
Electrical Engineering, Pontificia Universidad Catolica de
Chile, Santiago, Chile
Rutledal, Frode . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-33
frode.rutledal@ffi.no
Norwegian Defence Research Establishment, Norway
Rudnicki, Tomasz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-45
trudnicki@gddkia.gov.pl
Generalna Dyrekcja Dróg Krajowych i Autostrad, Warszawa,
Poland
Rufo Bazaga, María Jesús . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-35
mrufo@unex.es
Mathematics, University of Extremadura, Cáceres, Spain
Rui, Huaxia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-15
huaxia.rui@simon.rochester.edu
Simon School of Business, University of Rochester, United
States
Ruiz, Ana Belen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-18
abruiz@uma.es
Applied Economics (Mathematics), University of Malaga,
Malaga, Spain
Ruiz, Angel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-18
Angel.Ruiz@osd.ulaval.ca
Laval University, Quebec, Canada
Ruiz, Efrain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-31
efrain.ruizyruiz@uabc.edu.mx
Ing. Industrial, UABC, Ensenada, Baja California, Mexico
Ruiz, Francisco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-42
francisco.javier.ruiz@upc.edu
Automatic Control Dep., BarcelonaTech, Vilanova i la Geltrú, Barcelona, Spain
Ruiz, Ruben . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-14, MB-14
rruiz@eio.upv.es
Departamento de Estadistica e Investigación Operativa Aplicadas y Calidad, Universitat Politècnica de València, Valencia, Spain
Ruiz-Tagle, Mauricio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-26
mruiztag@uach.cl
Facultad de Cs. de la Ingeniería, Universidad Austral de
Chile, Valdivia, Chile
Runger, George . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-42
george.runger@asu.edu
Arizona State University, Tempe, AZ, United States
Rupérez Micola, Augusto . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-07
augusto.ruperezmicola@gmail.com
Luxembourg School of Finance, University of Luxembourg,
Luxembourg, Luxembourg
Rusdiana, Siti . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-17
srusdiana10@yahoo.com
Mathematics, University of Syiah Kuala, Medan, North Sumatera Province, Indonesia
Russo, Alfredo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-45
arusso@frba.utn.edu.ar
Industrial Engineering, Universidad Tecnologica Nacional
Facultad Regional Buenos Aires, Buenos Aires, CABA, Argentina
396
Ruzickova, Gabriela . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-09
xruzick8@node.mendelu.cz
Mendel University in Brno, Brno, Czech Republic
S.Pinto, Leonor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-02, MD-02
lspinto@iseg.utl.pt
Dep. Matemática, Instituto Superior de Economia e Gestão,
ULisboa - cemapre, Lisboa, Portugal
Saarinen, Esa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-23
esa.saarinen@aalto.fi
Aalto University School of Science, AALTO, Finland
Saat, Rapik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-05
mohdsaat@illinois.edu
Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, United States
Sabach, Shoham . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-38
ssabach@gmail.com
Institute for Numerical and Applied Mathematics, University
of Goettingen, Goettingen, Germany
Sabene, Federico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-01
sabenefederico@gmail.com
Roma Tre University, Italy
Saber, Takfarinas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-29
takfarinas.saber@ucdconnect.ie
Computer Science and Informatics, Lero@University College Dublin, UCD, Dublin, Ireland
Saborido Infantes, Rubén . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-18
rsain@uma.es
Applied Economics (Mathematics), University of Málaga,
Málaga, Spain
Sachs, Anna-Lena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-19
anna.sachs@tum.de
Department of Supply Chain Management and Management
Science, University of Cologne, Germany
Sacone, Simona . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-05
simona.sacone@unige.it
DIST, University of Genova, Genova, Italy
Saddoune, Mohammed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-03
mohammed.saddoune@polymtl.ca
École Polytechnique de Montréal, Faculté des Sciences et
Techniques de Mohammedia, Montréal, QC, Canada
Sadeh, Arik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-34
sadeh@hit.ac.il
Management of Technology, Holon Institute of Technology,
Holon, Israel
Sadoghi, Amirhossein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-40
a.sadoghi@fs.de
Finance Department, Frankfurt School of Finance & Management, Frankfurt am Main, Germany
Sadyadharma, Hendaru . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-17
hendarusadyadharma@yahoo.com
Grad.School of Env. Manag & Natural Resources, Univer-
IFORS 2014 - Barcelona
sity of Sumatera Utara, Medan, North Sumatera Province,
Indonesia
Saeednia, Mahnam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-05
mah.saeednia@gmail.com
DIME, University of Genoa, Genoa, Italy
Saenz, Maria Jesus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-33
mjsaenz@zlc.edu.es
MIT-Zaragoza International Logistics Program, Zaragoza,
Spain
Safaei Farahani, Samira . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-20
s.safaeifarahani@tudelft.nl
Energy and Industry, Delft University of Technology, Delft,
Zuid Holland, Netherlands
Safari, Hossein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-07
hsafari@ut.ac.ir
Faculty of Management, University of Tehran, Tehran, Iran,
Islamic Republic Of
Safarian, Mher. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-38
mher.safarian@kit.edu
Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Safdar, Komal Aqeel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-32
safdarka@aston.ac.uk
Operations and Information Management Group, Aston Business School, Aston University, Birmingham, West Midlands,
United Kingdom
Safey El Din, Mohab . . . . . . . . . . . . . . . . . . . . . . . . MA-16, MB-16
Mohab.Safey@lip6.fr
Paris 6, Paris, France
Sagarra, Martí . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-42
marti.sagarra@uab.cat
Department of Business Economics, Universitat Autònoma
de Barcelona, Bellaterra (Cerdanyola del Vallès), Spain,
Spain
Sagawa, Juliana Keiko . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-30
juliana@dep.ufscar.br
Production Engineering, Federal University of São Carlos,
São Carlos, SP, Brazil
Saharidis, Georgios K.D. . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-42
saharidis@gmail.com
Mechanical Engineering, University of Thessaly, Volos,
Thessaly, Greece
Sahin, Evren . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-11
evren@lgi.ecp.fr
Ecole Centrale Paris, France
Sahin, Guvenc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-04
guvencs@sabanciuniv.edu
Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey
Sahin, Ozge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-15
ozge.sahin@jhu.edu
John Hopkins University, Baltimore, United States
Sahin, Ozge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-15
ozgesahin@arel.edu.tr
Arel University, Istanbul, Turkey
Sahman, Mehmet Akif . . . . . . . . . . . . . . . . . . . . . . ME-04, MB-18
asahman@selcuk.edu.tr
Guneysinir Vocational School, Selcuk University, Konya,
AUTHOR INDEX
Selçuklu, Turkey
Sağol, Gizem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-16
gizemsagol@gmail.com
Industrial Engineering, Koç University, Turkey
Sak, Halis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-34
halis.sak@gmail.com
Systems Engineering Department, Yeditepe University, Istanbul, Turkey
Saka, Onur Can . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-42
onurcans@gmail.com
Department of Industrial Engineering, Middle East Technical
University, Ankara, Turkey
Sakuma, Yutaka . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-31
sakuma@nda.ac.jp
Department of Computer Science, National Defense
Academy, Yokosuka-City, Kanagawa-Pref., Japan
Salah, Mohamed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-29
msalah511@yahoo.fr
Algiers University, Algiers, Algeria
Salais Fierro, Tomas Eloy . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-13
tomas.salaisfr@uanl.edu.mx
FIME - Posgrado, Universidad Autonoma de Nuevo Leon,
San Nicolas de los Garza, Nuevo Leon, Mexico
Salazar González, Juan José . . . . . . . . . . . . . . . . . . . . . . . . . HB-02
jjsalaza@ull.es
Estadística e Investigación Operativa, Universidad de La Laguna (Tenerife), La Laguna, Tenerife, Spain
Salazar, Eduardo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-40
esalazar@udec.cl
Department of Industrial Engineering, University of Concepción, Concepción, Chile
Salazar, Fernanda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-40
fernanda.salazar@epn.edu.ec
Mathematics, Escuela Politecnica Nacional, Quito, Ecuador
Saldanha-da-Gama, Francisco . . . . . . . . FA-03, HD-03, ME-39
fsgama@fc.ul.pt
CIO/DEIO, University of Lisbon, Lisbon, Portugal
Salehipour, Amir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-29
amir.salehipour@gmail.com
School of Mathematical and Physical Sciences, University of
Newcastle, Callaghan, NSW, Australia
Salhi, Said . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-45, HE-45
s.salhi@kent.ac.uk
Kent Business School, University of Kent, Canterbury, Kent,
United Kingdom
Salles Neto, Luiz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-05
luiz.leduino@unifesp.br
Federal São Paulo State University, São José dos Campos,
São Paulo, Brazil
Salles, André . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-22, HB-34
as@ufrj.br
Industrial Engeneering, Federal University of Rio de Janeiro
- UFRJ, Rio de Janeiro, Rio de Janeiro, Brazil
Salling, Kim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-44
kbs@transport.dtu.dk
Department for Transport, Technical University of Denmark,
Kgs. Lyngby, Denmark
397
AUTHOR INDEX
IFORS 2014 - Barcelona
Salman, Sibel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-32
ssalman@ku.edu.tr
Industrial Engineering, Koc University, Istanbul, Turkey
Salmeron, Javier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-09
jsalmero@nps.edu
Operations Research Dept., Naval Postgraduate School,
Monterey, CA, United States
Salminen, Olli . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-36
olli.salminen@metla.fi
Finnish Forest Research Institute, Vantaa, Finland
Salminen, Pekka . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-31
Pekka.Salminen@econ.jyu.fi
School of Business and Economics, University of Jyväskylä,
Jyväskylä, Finland
Salomon, Fernando . . . . . . . . . . . . . . . . . . MA-30, HB-34, TB-34
fer.salomon@hotmail.com
IEPG - Instituto de Engenharia de Produção e Gestão,
UNIFEI - Universidade Federal de Itajuba, Itajuba, MG,
Brazil
Salvagnin, Domenico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-11
dominiqs@gmail.com
DEI, University of Padova, Italy
Samà, Marcella . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-01
sama@dia.uniroma3.it
Roma Tre University, Italy
Samiedaluie, Saied . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-32
saied.samiedaluie@mail.mcgill.ca
Desautels Faculty of Management, McGill University, Montreal, Canada
Samii, Behzad. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-32
behzad.samii@vlerick.be
Operations and Technology Management Center, Vlerick Research, Gent, Belgium
Sammarra, Marcello. . . . . . . . . . . . . . . . . . . . . . . . . HB-05, HE-05
sammarra@icar.cnr.it
Istituto di Calcolo e Reti ad Alte Prestazioni, Consiglio
Nazionale delle Ricerche, Rende (CS), Italy
Sammaung, Wissanu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-37
b5005208@hotmail.com
Chulalongkorn University, Bangkok, Thailand
Samorani, Michele . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-19
michael.samorani@colorado.edu
Leeds School of Business, University of Colorado at Boulder,
Boulder, CO, United States
Samorani, Michele . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-10
samorani@ualberta.ca
Alberta School of Business, University of Alberta, Edmonton, Alberta, Canada
Samouylov, Konstantin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-31
ksam@sci.pfu.edu.ru
Telecommunication Systems Department, Peoples’ Friendship University of Russia, Moscow, Russian Federation
mersan@unavarra.es
Business Departament, Universidad Publica de Navarra,
Pamplona, Navarra, Spain
Sanchis, Jose Maria . . . . . . . . . . . . . . . . . . . . . . . . . MB-02, ME-02
jmsanchis@mat.upv.es
Departamento de Matematica Aplicada, Universidad Politecnica de Valencia, Spain
Sanda, Murat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-43
okaytr@gmail.com
Selcuk Unİversİty, Turkey
Sandal, Leif . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-07
leif.sandal@nhh.no
Business and Management Science, Norwegian School of
Economics, Bergen, Norway
Sandoh, Hiroaki . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-19
sandoh@econ.osaka-u.ac.jp
Graduate School of Economics, Osaka University, Toyonaka,
Osaka, Japan
Sandoval, Salvador . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-08
salvsanb@cucea.udg.mx
Métodos Cuantitativos, Universidad de Guadalajara,
Guadalajara, Jalisco, Mexico
Sangüesa, Carmen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-24
csangues@unizar.es
Universidad de Zaragoza, Zaragoza, Spain
Sanguineti, Marcello . . . . . . . . . . . . . . . . . . . . . . . . . TB-16, HD-31
marcello.sanguineti@unige.it
DIBRIS, University of Genoa, Genova, Italy
Sanjay, Kumar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-44, HB-44
sxk89@psu.edu
Black School of Business, Penn State University- Erie, Erie,
Pennsylvania, United States
Sanjuan, Neus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-36
nsanjuan@tal.upv.es
Tecnología de Alimentos, Universitat Politecnica de Valencia, Valencia, Valencia, Spain
Santos, Andréa Cynthia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-37
andrea.duhamel@utt.fr
ICD-LOSI, Université de Technologie de Troyes, Troyes,
France
Santos, Cátia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-37
catiaaasantos@gmail.com
Apartado 3008, Department of Mathematics, Coimbra, Portugal
Santos, Claudio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-27
ams.claudio@gmail.com
Department of Production and Systems, University of Minho,
Guimarães, Braga, Portugal
Santos, José . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-37
zeluis@mat.uc.pt
Department of Mathematics, University of Coimbra, Coimbra, Portugal
Samuylov, Andrey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-31
asam1988@gmail.com
Peoples’ Friendship University of Russia, Russian Federation
Santos, Paulo Sergio Marques . . . . . . . . . . . . . . . . . . . . . . . FA-26
psergio@ufpi.edu.br
Mathematics, Federal University of Piaui, Teresina, Piauí,
Brazil
Sanchez, Mercedes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-41
Santos, Sérgio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-14, TB-14
398
IFORS 2014 - Barcelona
AUTHOR INDEX
ssantos@ualg.pt
Faculdade de Economia, Universidade do Algarve and
CEFAGE, Faro, Portugal
gilles.savard@polymtl.ca
Mathématiques et génie industriel, École Polytechnique,
Montréal, Québec, Canada
Sarabia, Daniel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-41
dsarabia@autom.uva.es
Systems Engineering and Automatic Control, University of
Valladolid, Valladolid, Spain
Savard, Gilles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-15
gilles@crt.umontreal.ca
DMGI, Ecole Polytechnique de Montreal, Montreal, Quebec,
Canada
Saraç, Tugba . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-21
tsarac@ogu.edu.tr
Department of Industrial Engineering, Eskisehir Osmangazi
University, Eskisehir, Turkey
Savelsbergh, Martin . . . . . . . . . . . . . . . . . HD-25, HE-29, HD-31
martin.savelsbergh@newcastle.edu.au
University of Newcastle, Australia
Saracoglu, Ilkay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-19
ilkays@sbbdanismanlik.com
Industrial Engineering, Dokuz Eylul University, Izmir,
Turkey
Savva, Nicos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-15
nsavva@london.edu
Management Science and Operations, London Business
School, London, United Kingdom
Sarango, Adrian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-40
adrian.sarango@epn.edu.ec
Escuela Politecnica Nacional, Quito, Ecuador
Sawada, Kiyoshi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-12
Kiyoshi_Sawada@red.umds.ac.jp
Department of Policy Studies, University of Marketing and
Distribution Sciences, Kobe, Japan
Sareni, Bruno . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-06
sareni@laplace.univ-tlse.fr
Université de Toulouse, LAPLACE (Laboratory on Plasma
and Conversion of Energy), Toulouse, France
Sá Esteves, Jorge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-31
saesteves@ua.pt
Dep. of Mathematics, University of Aveiro, AVEIRO, Portugal
Sarin, Rakesh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-31
rakesh.sarin@anderson.ucla.edu
Anderson Graduate School of Management, UCLA, Los Angeles, CA, United States
Sayarshad, Hamid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-25
hsabarsh@ryerson.ca
Civil Engineering, Ryerson University, Toronto, Canada
Sarpong, Boadu Mensah . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-02
bmsarpon@laas.fr
LAAS-CNRS, Toulouse, France
Saydam, Cem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-32
saydam@uncc.edu
Business Information Systems and Operations Management,
University of North Carolina at Charlotte, Charlotte, North
Carolina, United States
Sartini, Brígida . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-11
brigida@ufrrj.br
DTL, UFRRJ, Rio de Janeiro, Rio de Janeiro, Brazil
Sato, Andre . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-21
andresato@hotmail.com
University of Sao Paulo, Brazil
Sato, Kimitoshi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-30
k-sato@aoni.waseda.jp
Graduate School of Finance, Accounting and Law, Waseda
University, Tokyo, Japan
Saucedo, Jania . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-13
jania.saucedo@gmail.com
Logistics and Supply Chain, FIME-UANL, San Nicolás de
los Garza, Nuevo León, Mexico
Saul, Benjamin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-43
benjamin.saul@informatik.uni-halle.de
Institute of Computer Science, Martin-Luther-University
Halle-Wittenberg, Halle (Saale), Germany
Sava, Magda Gabriela . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-32
mgsava@katz.pitt.edu
Business Analytics and Operations, Katz Graduate School
of Business, University of Pittsburgh, Pittsburgh, PA, United
States
Savan, Emanuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-27
emanuel-emil.savan@mbs.ac.uk
Manchester Business School, University of Manchester,
Manchester, United Kingdom
Savard, Gilles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-15, TB-15
Sánchez de la Nieta López, Agustín Alejandro HA-09, ME-10
agustinsnl@gmail.com
Electromechanical Engineering, University of Beira Interior,
Portugal, Covilha, Portugal
Sánchez Olaya, Maria Angélica . . . . . . . . . . . . . . . . . . . . . . TA-13
ma.sanchez116@uniandes.edu.co
Universidad de los Andes, Colombia
Sánchez Ramírez, Rodrigo Antonio . . . . . . . . . . . . . . . . . . HE-32
rodrigosanchez@ceap.cl
Mejoramiento de procesos, Centro de Estudios en Alimentos
Procesados (CEAP_R09I2001), Talca, Chile
Sánchez-Martín, Pedro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-10
pedro.sanchez@upcomillas.es
IIT, Comillas (ICAI-IIT), Madrid, Spain
Sbihi, Abdelkader . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-12
a.sbihi@em-normandie.fr
Axe Logistique-Terre-Mer-Risque, Ecole de Management de
Normandie, Le Havre, France, Le Havre Cedex, France
Scaparra, Maria Paola . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-03
M.P.Scaparra@kent.ac.uk
Kent Business School, University of Kent, Canterbury,
United Kingdom
Scarpin, Cassius Tadeu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-32
cassiusts@yahoo.com.br
Universidade Federal do Paraná, Curitiba, Paraná, Brazil
Scarsini, Marco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-06
marco_scarsini@sutd.edu.sg
399
AUTHOR INDEX
IFORS 2014 - Barcelona
ESD, SUTD, Singapore, Singapore
Schachinger, Werner . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-16
werner.schachinger@univie.ac.at
Dept. of Statistics and OR, University of Vienna, Wien, Austria
Schaefer, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-43
peter.schaefer@tum.de
TUM School of Management, Technische Universität
München, Munich, Germany
Schäfer, Guido . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-22
g.schaefer@cwi.nl
Networks and Optimization, CWI, Amsterdam, Netherlands
Scheimberg, Susana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-26
susana@cos.ufrj.br
COPPE/ Engenharia de Sistemas e Computação-Instituto de
Matemática, COPPE/PESC-IM, Universidade Federal do Rio
de Janeiro, Rio de Janeiro, RJ, Brazil
Scheithauer, Guntram . . . . . . . . . . . . . . . . . . . . . . . FB-21, HB-21
Guntram.Scheithauer@tu-dresden.de
Mathematik, Technische Universität Dresden, Dresden, Germany
Scheller-Wolf, Alan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-13
awolf@andrew.cmu.edu
Carnegie Mellon University, United States
Schemeleva, Ksenyia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-13
ksenia0885@gmail.com
IDRAC Business school, Lyon, France
Schepler, Xavier. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-36
xavier.schepler@gmail.com
Université du Havre, France
Schiffleitner, Andreas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-33
andreas.schiffleitner@kerp.at
KERP Kompetenzzentrum Elektronik & Umwelt GmbH,
Wien, Austria
Schimmelpfeng, Katja . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-06
katja.schimmelpfeng@uni-hohenheim.de
Lehrstuhl für Beschaffung und Produktion, Universität Hohenheim, Stuttgart, Germany
Schittekat, Patrick . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-03
patrick.schittekat@sintef.no
ICT, SINTEF, Oslo, Norway
Schlechte, Thomas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-01
schlechte@zib.de
Optimization, Zuse-Institute-Berlin, Berlin, Berlin, Germany
Schlünz, Evert B. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-11
bernard.schlunz@necsa.co.za
Radiation and Reactor Theory, South African Nuclear Energy
Corporation SOC Ltd, Pretoria, South Africa
Schmehl, Meike . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-31
schmehl@wiwi.uni-goettingen.de
Chair of Production and Logistics, Georg-August-Universität
Göttingen, Göttingen, Germany
Schmid, Verena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-02, TE-02
vschmid@europa-uni.de
Supply Chain Management, Europa-Universität Viadrina,
Frankfurt, Germany
400
Schmidt, Daniel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-11
schmidt@informatik.uni-koeln.de
Institut für Informatik, Universität zu Köln, Köln, Germany
Schmidt, Kerstin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-27
kerstin.schmidt@tu-braunschweig.de
Institute of Automotive Management and Industrial Production, Technische Universität Braunschweig, Braunschweig,
Germany
Schmidt, Marie . . . . . . . . . . . . . . . . . . . . . . HE-01, MD-01, TB-01
m.schmidt@math.uni-goettingen.de
Institut für Numerische und Angewandte Mathematik,
Georg-August-Universität Göttingen, Göttingen, Germany
Schmidt, Melanie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-11
melanie.schmidt@tu-dortmund.de
Department of Computer Science, TU Dortmund University,
Dortmund, Germany
Schnitzler, Daniel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-13
daniel.schnitzler@uni-siegen.de
Operations Research, University of Siegen, Siegen, NRW,
Germany
Schöbel, Anita . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-01, TA-18
schoebel@math.uni-goettingen.de
Institute for Numerical and Applied Mathematics, GeorgAugust Universiy Goettingen, Göttingen, Germany
Schoen, Fabio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-41
fabio.schoen@unifi.it
Dipartimento di Ingegneria dell’Informazione, Università
degli Studi di Firenze, Firenze, Italy
Scholz, André . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-02
andre.scholz@ovgu.de
Department of Management Science, Otto-von-Guericke
University Magdeburg, Magdeburg, Germany
Scholz, Johannes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-36
johannes.scholz@researchstudio.at
Studio iSPACE, Research Studios Austria, Salzburg,
Salzburg, Austria
Scholz, Yvonne . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-34
Yvonne.Scholz@dlr.de
Systems Analysis and Technology Assessment, German
Aerospace Center (DLR), Stuttgart, Germany
Schönberger, Jörn . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-42
jsb@uni-bremen.de
University of Bremen, Bremen, Germany
Schöneberg, Tim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-04
tim.schoeneberg@gmail.com
DS&OR Lab, University of Paderborn, Paderborn, Germany
Schramme, Torben . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-12
schramme@dsor.de
DS&OR Lab Paderborn, University of Paderborn, Paderborn,
Germany
Schröder, Stefan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-06
stefan.schroeder@kit.edu
Network economics, KIT, Karlsruhe, Germany
Schrödl, Holger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-42
holger.schroedl@ovgu.de
Otto-von-Guericke University Magdeburg, Magdeburg, Germany
IFORS 2014 - Barcelona
Schüle, Ingmar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-18
schuele@itwm.fraunhofer.de
Optimization, Fraunhofer ITWM, Kaiserslautern, Germany
Schülldorf, Hanno . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-01
hanno.schuelldorf@deutschebahn.com
GSV, Deutsche Bahn AG, Frankfurt am Main, Germany
Schultmann, Frank . . . . . . . . . . . . . . . . . . . . . . . . . MA-38, MD-38
frank.schultmann@kit.edu
Institute for Industrial Production, Karlsruhe Institute of
Technology (KIT), Karlsruhe, Germany
Schultz, Rüdiger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-41
schultz@math.uni-duisburg.de
Mathematics, University of Duisburg-Essen, Duisburg, Germany
Schürle, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-09
michael.schuerle@unisg.ch
Institute for Operations Research and Computational Finance, University of St. Gallen, St. Gallen, Switzerland
Schuster, Matias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-04
matias.schuster@uclouvain-mons.be
Louvain School of Management, Université catholique de
Louvain, Mons, Belgium
Schütz, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-05
peter.schuetz@dnvgl.com
Dnv Gl, Norway
Schwarz, Quique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-20
quique@auto-grid.com
AutoGrid, Redwood Shores, CA, United States
Schwarz, Robert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-28
schwarz@zib.de
Optimization, Zuse Institute Berlin, Berlin, Germany
Schweiger, Jonas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-28
schweiger@zib.de
Optimization, Zuse Institute Berlin (ZIB), Berlin, Germany
Schwindt, Christoph . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-12
christoph.schwindt@tu-clausthal.de
Institute of Management and Economics, Clausthal University of Technology, Clausthal-Zellerfeld, Germany
Schyns, Michaël . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-21
M.Schyns@ulg.ac.be
HEC - Management School, University of Liège, Liege, Belgium
Sciandrone, Marco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-41
sciandro@dsi.unifi.it
Dipartimento di Ingegneria dell’Informazione, Universita’ di
Firenze, Firenze, Italy, Italy
Sciomachen, Anna . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-05
sciomach@economia.unige.it
DIEM, University of Genova, Genova, Italy
Scozzari, Andrea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-03
andrea.scozzari@unisu.it
Economia, Università degli Studi Niccolò Cusano - Telematica, Roma, Italy
Scutari, Gesualdo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-10
gesualdo@buffalo.edu
Electrical Engineering, State University of New York at Buffalo, Buffalo, NY, United States
AUTHOR INDEX
Scutellà, Maria Grazia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-11
scut@di.unipi.it
Informatica, Universita’ di Pisa, Pisa, Italy
Sebastian, Patrick . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-18
patrick.sebastian@u-bordeaux.fr
I2m, Umr Cnrs 5295, Université de Bordeaux, Talence
Cedex, France
Seçerdin, Yusuf . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-03
yusufsecerdin@etu.edu.tr
Industrial Engineering Department, TOBB University of Economics and Technology, Ankara, -, Turkey
Sechi, Giovanni . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-43
SECHI@UNICA.IT
Dept. of Land Engineering, University of Cagliari, Cagliari,
Italy
Secomandi, Nicola . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-20
ns7@andrew.cmu.edu
Tepper School of Business, Carnegie Mellon University,
Pittsburgh, PA, United States
Sedakov, Artem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-35
a.sedakov@spbu.ru
Saint Petersburg State University, Russian Federation
Seddig, Katrin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-07
k.seddig@ensoc.de
Energy Solution Center e. V., Karlsruhe, Germany
Seeger, Alberto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-26
alberto.seeger@univ-avignon.fr
Department of Mathematics, University of Avignon, Avignon, France
Segev, Danny . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-32
segevd@stat.haifa.ac.il
Statistics, University of Haifa, Israel
Segura, Baldomero . . . . . . . . . . . . . . . . . . . . . . . . . . HA-36, TE-36
bsegura@upvnet.upv.es
Economía y Ciencias Sociales, Universidad Politécnica de
Valencia, Valencia, Spain
Segura, Marina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-36, TE-36
masema@posgrado.upv.es
Applied Statistics, Operations Research and Quality, Universitat Politècnica de València, Valencia, Spain
Seichanoglou, Gulnur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-43
gulnursahin@gmail.com
Mathematics, Bahcesehir University, Istanbul, Turkey
Seidmann, Abraham . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-43
seidmannav@simon.rochester.edu
University of Rochester, Rochester, NY, United States
Seifert, Ralf W. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-07
ralf.seifert@epfl.ch
TOM, EPFL, Lausanne, Switzerland
SEL, Çağrı . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-08
cagri.sel@wur.nl
Operations Research and Logistics, Wageningen University,
Wageningen, Netherlands
Selcuk, Baris . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-15, FB-39
bariselcuk@gmail.com
Industrial Engineering, Bahcesehir University, Istanbul,
401
AUTHOR INDEX
IFORS 2014 - Barcelona
Turkey
Selim, Hasan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-38
hasan.selim@deu.edu.tr
Industrial Engineering, Dokuz Eylul University, Izmir,
Turkey
Sellami, Khaled. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-16, TD-32
skhaled36@yahoo.fr
LMA Laboratory, Bejaia University / EISTI France, Bejaia,
Algeria
mehdi.sepehri@modares.ac.ir
Tarbiat Modares University, Tehran, Iran, Islamic Republic
Of
Serarslan, Nahit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-37
serarslann@itu.edu.tr
Technical University of Istanbul, Istanbul, Turkey
Serôdio, Carlos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-26
cserodio@utad.pt
Citab - Utad, Vila Real, Portugal
Sels, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-01
sels.peter@gmail.com
KU Leuven, Belgium
Serch, Oriol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-04
oriol.serch@upc.edu
UPC, Spain
Selviaridis, Kostas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-34
Kostas.Selviaridis@tlog.lth.se
Lund University, Lund, Sweden
Seref, Michelle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-25
mmhseref@vt.edu
ACIS, Virginia Tech, Blacksburg, VA, United States
Şen, Halil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-12
halilsen@sabanciuniv.edu
Industrial Engineering, Sabanci University, Istanbul, Turkey
Seref, Onur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-25
seref@vt.edu
Virginia Tech, Blacksburg, Virginia, United States
Şen, Nur Nazlı . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-30
nurnazlisen@gmail.com
Industrial Engineering, Istanbul Kültür University, Turkey
Serin, Yasemin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-18
serin@ie.metu.edu.tr
Industrial Engineering, Middle East Technical University,
Ankara, Turkey
Sen, Suvrajeet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-45
s.sen@usc.edu
Daniel J. Epstein Dept. of ISE, University of Southern California, Los Angeles, CA, United States
Sermpinis, Georgios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-26
Georgios.Sermpinis@glasgow.ac.uk
University of Glasgow, Glasgow, United Kingdom
Şenay, Nurdinç . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-33
n.senay@hvkk.tsk.tr
Scientific Decision Support Department, Turkish Air Force
Command, Çankaya, Ankara, Turkey
Serna, Maria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-22
mjserna@lsi.upc.edu
Software, Technical University of Catalonia, Barcelona, Catalonia, Spain
Şengel, Öznur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-10
o.sengel@iku.edu.tr
Computer Engineering, İstambul Kültür University, İstanbul,
Bakırköy, Turkey
Serote, Ernesto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-20
eserote@yahoo.com
SURP, Univ of the Phil, Quezon City, Philippines
Senna, Valter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-08
valtersenna@gmail.com
Computer Modelling, SENAI-CIMATEC, Brazil
Serrano, Adrian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-41
adserher@gmail.com
Statistics and Operations Research, Public University of
Navarre, Spain
Sennaroglu, Bahar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-29
bsennaroglu@gmail.com
Industrial Engineering, Marmara University, Istanbul, Turkey
Seth, Dinesh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-32
dseth@qu.edu.qa
Qatar University, Doha, Qatar
Şenol, Mehmet Burak . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-07
senolmehmet81@hotmail.com
Quality Management Directorate, Turkish Land Forces5.Main Maintenance Center, Ankara, Turkey
Sethi, Suresh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-41
sethi@utdallas.edu
Jindal School of Management - ISOM, University of Texas at
Dallas, Richardson, TX, United States
Senturk, Sevil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-07
sdeligoz@anadolu.edu.tr
Statistics, Anadolu University, Turkey
Setzer, Thomas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-34
thsetzer@gmail.com
Business Engineering and Management, KIT, Muenchen,
Baden-Wuerttemberg, Germany
Seow, Hsin-Vonn . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-40
Hsin-Vonn.Seow@nottingham.edu.my
Business School, University of Nottingham- Malaysia Campus, Semenyih, Selangor, Malaysia
Sepehr, Adel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-24
adelsepehr@aol.com
Faculty of Natural Resources and Environment, Ferdowsi
University of Mashhad, Mashhad, Khorasan Razavi, Iran,
Islamic Republic Of
Sepehri, Mehdi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-43
402
Seuring, Stefan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-08
seuring@uni-kassel.de
University of Kassel, Kassel, Germany
Sevcovic, Daniel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-24
sevcovic@fmph.uniba.sk
Department of Applied Mathematics and Statistics, Comenius University, Bratislava, Slovakia
Sezen, Tugbanur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-19
tsezenn@gmail.com
IFORS 2014 - Barcelona
Industrial Engineering, İstanbul Kültür University, İstanbul,
Turkey
Sgarbossa, Fabio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-13
fabio.sgarbossa@unipd.it
Department of Management and Engineering (DTG), Univerity of Padova, Vicenza, Italy
Sgouritsa, Alkmini . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-22
asgourits@liv.ac.uk
University of Liverpool, Liverpool, United Kingdom
Shabelnikova, Natalia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-39
kriagell@gmail.com
Mecanics and Mathematics, Novosibirsk State University,
Novosibirsk, Russian Federation
Shah, IrfanUllah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-27
shahafghan1983@gmail.com
Business Administration, Dokuz Eylül University, Turkey
Shah, Nilay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-38
n.shah@ic.ac.uk
Centre for Process Systems Engineering, Imperial College
London, London, United Kingdom
Shahabuddin, Syed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-32
shaha1s@cmich.edu
Management, Central Michigan University, Mt Pleasant, MI,
United States
Shahin, Arash . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-19
arashshahin@hotmail.com
University of Isfahan, Isfahan, Iran, Islamic Republic Of
Shahzad, Sadeeqa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-08
sadeeqa.shahzad@lums.edu.pk
Lahore University of Management Sciences, Lahore, Punjab,
Pakistan
AUTHOR INDEX
Shapoval, Katerina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-34
shapovalova@fzi.de
Department of Economics and Management, Karlsruhe Institute of Technology, Germany
Sharif Azadeh, Shadi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-15
shadi.sharifazadeh@polymtl.ca
Mathematics, Polytechnique Montreal, Montreal, Quebec,
Canada
Sharma, Jitendra . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-40
sjiten1@gmail.com
OPERATIONS, IMT, Nagpur, Nagpur, MS, India
Sharma, Megha . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-15
megha@iimcal.ac.in
Operations Management, Indian Institute of Management
Calcutta, Kolkata, West Bengal, India
Shaton, Katerina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-05
katsiaryna.shaton@himolde.no
Molde University College, Specialized University in Logistics, Norway
Shaukat, Syed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-03
sshaukat29@yahoo.com.au
Aviation, University of New South Wales, Sydney, New
South Wales, Australia
Shayegh, Soheil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-20
soheilsh@gatech.edu
Georgia Institute of Technology, Atlanta, United States
Shchegryaev, Alexander . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-02
aleksandr.shchegryaev@gmail.com
Applied Mathematics, St.Petersburg State University,
St.Petersburg, Russian Federation
Shajari, Seyedeh Hoda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-36
shajar.shd@gmail.com
Mathematics, Iran University of Science and Technology,
Iran, Islamic Republic Of
Shcherbanin, Yury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-05
shcherbaninya@mail.ru
Transport and Logistics Analyses and Forecasting, Russian
Academy of Sciences, Institute of Economic Forecasting,
Moscow, Russian Federation
Shakeel, Muhammad Bilal . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-24
shakeem2@lsbu.ac.uk
Business Studies, London South Bank University, London,
United Kingdom
Shen, Yindong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-20
yindong@hust.edu.cn
School of Automation, Huazhong University of Science and
Technology, Wuhan, China
Shamir, Noam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-19
nshamir@tau.ac.il
Recanati School of Business, Tel-Aviv University, Tel-Aviv,
Israel
Sheopuri, Anshul . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-15
sheopuri@us.ibm.com
IBM Research, Yorktown Heights, NY, United States
Shamma, Jeff . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-06
shamma@gatech.edu
Electrical and Computer Engineering, Georgia Institute of
Technology, Atlanta, GA, United States
Shang, Kevin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-20
khshang@duke.edu
Duke University, Durham, NC, United States
Shang, Weixin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-27
shangwx@ln.edu.hk
Computing and Decision Sciences, Lingnan University, Hong
Kong, Hong Kong
Shao, Yufen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-29
yufen.shao@exxonmobil.com
ExxonMobil, Houston, Tx, United States
Shi, Yutong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-43
sytsx_1@163.com
Management Science, Xiamen University, Xiamen, Fujian,
China
Shi, Zhenyu (Edwin) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-32
zhenyushi2013@u.northwestern.edu
Northwestern University, Evanston, IL, United States
Shim, Woohyun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-31
woohyun@disi.unitn.it
Information Engineering & Computer Science, University of
Trento, Trento, TN, Italy
Shimakawa, Yoichi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-30
simakawa@salesio-sp.ac.jp
Computer Science & Technology, Salesian Polytechnic,
Machida, Tokyo, Japan
403
AUTHOR INDEX
IFORS 2014 - Barcelona
Shin, Hyo-Sang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-40
h.shin@cranfield.ac.uk
Cranfield University, Cranfield, United Kingdom
Shin, Hyoduk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-19
hshin@rady.ucsd.edu
Rady School of Management, University of California SanDiego, La Jolla, California, United States
Shiraga, Takeharu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-09
te108137@gmail.com
Kyushu University, Japan
Shnaiderman, Matan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-10
shnidem@biu.ac.il
Management, Bar-Ilan University, Ramat-Gan, Israel
Shone, Rob . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-09
shonerw@cardiff.ac.uk
Mathematics, Cardiff University, United Kingdom
Shorgin, Sergey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-31
sshorgin@ipiran.ru
Institute of Informatics Problems of RAS, Moscow, Russian
Federation
Shugan, Steven . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-15
steven.shugan@warrington.ufl.edu
Marketing, University of Florida, Gainesville, Florida,
United States
Shvydun, Sergey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-27
shvydun@mail.ru
Hse, Ics Ras, Russian Federation
Shylo, Oleg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-11
oshylo@utk.edu
Industrial and Systems Engineering, University of Tennessee,
Knoxville, Tennessee, United States
Shylo, Vladimir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-11
v.shylo@gmail.com
V.M. Glushkov Institute of Cybernetics, Kiev, Ukraine
Siarry, Patrick . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-40
siarry@univ-paris12.fr
LERISS, Université de Paris 12, CRETEIL, France
Sibanda, Wilbert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-22
Wilbert.sibanda@nwu.ac.za
Information Technology, North-West University, Vanderbijlpark, Gauteng, South Africa
Siddiqui, Afzal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-10
afzal.siddiqui@ucl.ac.uk
Statistical Science, University College London, London,
United Kingdom
Siddiqui, Sauleh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-07
siddiqui@jhu.edu
Johns Hopkins University, Baltimore, MD, United States
Siebert, Xavier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-24
Xavier.SIEBERT@umons.ac.be
MathRO, UMONS, Mons, Belgium
Sierra, David . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-38
innova@innovaccio.net
Innova Institute, Barcelona, Spain
Sierra, Evelyn . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-20
404
vlyn_sierra@yahoo.com
DSWD, Quezon City, Philippines
Siface, Dario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-09
dario.siface@rse-web.it
Energy Systems Development, RSE SpA, Milano, Italy
Sigurd, Mikkel M. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-05
msigurd@gmail.com
IBM, Copenhagen, Denmark
Sigurdardottir, Gudridur Lilla . . . . . . . . . . . . . . . . . . . . . . HE-10
gudridurs06@ru.is
Engineering, Reykjavik University, Reykjavik, Iceland
Silalahi, Meslin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-17
meslin_silalahi@yahoo.com
Mathematics, University of Sisingamangaraja-Tapanuli/Grad
School of Mathematics USU, Medan, North Sumatera
Province, Indonesia
Siluk, Julio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-20
jsiluk@ufsm.br
Federal University of Santa Maria, Santa Maria, Brazil
Silva, Elsa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-19, FA-21
emsilva@inescporto.pt
Inesc Tec, Porto, Portugal
Silva, Francisco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-40
fsilva@uac.pt
Economics and Business, University of the Azores, Ponta
Delgada, Portugal
Silva, Juliana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-23
juliananascente@gmail.com
Universidade Federal Rural do Rio de Janeiro, Brazil
Silva, Lino . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-17
ra108980@ime.unicamp.br
Applied Mathematics, UNICAMP/UNIVASF, Petrolina, Pernambuco, Brazil
Silva, Ricardo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-39
rmas@cin.ufpe.br
Centro de Informatica, Universidade Federal de Pernambuco,
Recife, Pernambuco, Brazil
Silva, Sofia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-14
srsilva@porto.ucp.pt
Universidade Católica Portuguesa no Porto, Porto, Portugal
Silva, Thiago . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-28
thiagolims@gmail.com
Automation Engineering Department, Federal University of
Santa Catarina, Florianopolis, Santa Catarina, Brazil
Silveira, João . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-20
joaotusi@hotmail.com
Applied Social Sciences - Master’s Programme in Strategic
Management of Organizations, Regional Integrated University of High Uruguay and Missions, Santo Ângelo, RS, Brazil
Silvente, Javier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-41
javier.silvente@upc.edu
Chemical Engineering Deparment, Universitat Politecnica de
Catalunya, Barcelona, Spain
Simangunsong, Sampe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-17
sampe_simangunsong@yahoo.com
Graduate School of Mat. University Sumatera Utara, Indonesia
IFORS 2014 - Barcelona
Simão Kaveski, Itzhak David . . . . . . . . . . . . . . . . . . . . . . . . HB-34
itzhak.konoha@gmail.com
Ciências Contábeis, Universidade Federal de Mato Grosso do
Sul - UFMS, Campo Grande, Mato Grosso do Sul, Brazil
Simchi-Levi, David . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-32
dslevi@mit.edu
Civil Eng, MIT, Cambridge, MA, United States
Simeonova, Lina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-45
ls444@kent.ac.uk
Kent Business School, University of Kent, Canterbury, Kent,
United Kingdom
Simonetti, Luidi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-06
luidi@ic.uff.br
Institute of Computing, Fluminense Federal University,
Niterói, Rio de Janeiro, Brazil
Sindhya, Karthik . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-18, TD-18
karthik.sindhya@jyu.fi
Dept. of Mathematical Information Technology, University
of Jyväskylä, Finland
Singh, Gaurav . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-12, MB-13
Gaurav.Singh@csiro.au
Mathematics, Informatics & Statistics, Commonwealth Scientific and Industrial Research Organisation (CSIRO), South
Clayton, Victoria, Australia
Singh, Sarbjit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-41
sarbjitoberoi@gmail.com
Operations Management, Institute of Management Technology, Nagpur, Maharastra, India
Singh, Vivek . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-03
singhv@mit.edu
Media Lab, Massachusetts Institute of Technology, Cambridge, MA, United States
Singla, Adish . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-22
adish.singla@inf.ethz.ch
ETH Zurich, Zurich, Switzerland
Sinha, Ankur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-18
ankur.sinha@aalto.fi
Department of Information and Service Economy, Aalto University School of Business, Helsinki, Finland
AUTHOR INDEX
Portsmouth, England, United Kingdom
Siskos, Eleftherios . . . . . . . . . . . . . . . . . . . . TB-18, TD-29, TB-31
lsiskos@epu.ntua.gr
School of Electrical & Computer Engineering, National
Technical University of Athens, Athens, Greece
Siskos, Pelopidas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-10
pelsiskos@gmail.com
School of Electrical and Computer Engineering, National
Technical University of Athens, Athens, Attiki, Greece
Siskos, Yannis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-18, TD-29
ysiskos@unipi.gr
Department of Informatics, University of Piraeus, Piraeus,
Greece
Sitepu, Suryati . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-17
suryati.sitepu@yahoo.com
Mathematics, University Sisingamangaraja/Grad School of
Math. USU, Medan, Indonesia
Sithipolvanichgul, Juthamon . . . . . . . . . . . . . . . . . . . . . . . . TD-34
juthamon@hotmail.com
Business School, The University of Edinburgh, Edinburgh,
United Kingdom
Sivrikaya, Nevin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-22
nevin.sivrikaya@metu.edu.tr
Statistics, METU, Turkey
Sjöland, Erik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-16
esjoland@kth.se
Mathematics, Aalto University, Aalto, Finland
Skar, Christian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-07
christian.skar@ntnu.no
Department of Electric Power Engineering, Norwegian University of Science and Technology, Trondheim, Norway
Škedelj, Franc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-42
franc.skedelj@result.si
Result d.o.o., Ljubljana, Slovenia
Slijepcevic-Manger, Tatjana . . . . . . . . . . . . . . . . . . . . . . . . . HA-34
tmanger@grad.hr
Faculty of Civil Engineering, University of Zagreb, Zagreb,
Croatia
Sinn, Mathieu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-35
mathsinn@ie.ibm.com
IBM Research, Dublin, Ireland
Slikker, Marco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-22, TD-22
m.slikker@tue.nl
Department of Industrial Engineering, Eindhoven University
of Technology, Eindhoven, Netherlands
Sinnl, Markus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-31
markus.sinnl@univie.ac.at
Department of Statistics and Operations Research, University
of Vienna, Vienna, Austria
Slimani, Hachem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-26
haslimani@gmail.com
LaMOS Research Unit, Computer Science Department, University of Bejaia, Algeria, Bejaia, Algeria
Sinuany-Stern, Zilla . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-29
zilla@bgu.ac.il
Industrial Engineering and Management, Ben Gurion University, Beer-Sheva, Israel
Slowinski, Roman . . . . . . . . . . . . . . . . . . . . . . . . . . MA-24, MB-24
roman.slowinski@cs.put.poznan.pl
Institute of Computing Science, Poznan University of Technology, Poznan, Poland
Sipahioglu, Aydin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-21
asipahi@ogu.edu.tr
Industrial Engineering, Osmangazi University, Eskisehir,
Turkey
Slusky, Marla . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-29
mslusky@andrew.cmu.edu
Carnegie Mellon University, Pittsburgh, United States
Siraj, Sajid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-15, MA-37
sajid.siraj@port.ac.uk
Portsmouth Business School, University of Portsmouth,
Smeers, Yves . . . . . . . . . . . . . . . . . . . . . . . . TA-07, HA-09, MB-43
Yves.Smeers@uclouvain.be
CORE, Université catholique de Louvain, Louvain-la-Neuve,
Belgium
405
AUTHOR INDEX
IFORS 2014 - Barcelona
Smidla, József . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-21, HE-33
smidla@dcs.uni-pannon.hu
Department of Computer Science and Systems Technology,
University of Pannonia, Hungary
Smilgins, Aleksandrs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-10
alsm@ifro.ku.dk
University of Copenhagen, Denmark
Smilowitz, Karen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-32
ksmilowitz@northwestern.edu
Industrial Engineering and Management Sciences, Northwestern University, Evanston, Illinois, United States
Smirlis, Yannis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-10
smirlis@unipi.gr
University of Piraeus, Piraeus, Greece
Smirnov, Sergey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-21
sasmir@gmail.com
Centre of distributed computing, Institute for Information
Transmission Problems (Kharkevich Institute), Russian Federation
Smit, Laurens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-19
lsmit@math.leidenuniv.nl
Leiden University, Netherlands
Smith, Honora . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-39
honora.smith@soton.ac.uk
Academic Unit of Mathematics, University of Southampton,
Southampton, Hampshire, United Kingdom
Sobieraj Richard, Sonia . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-01
sonia.sobieraj@ifsttar.fr
COYS/ESTAS, IFSTTAR, Villeneuve d’Ascq Cedex, France
Sobrie, Olivier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-24
olivier.sobrie@gmail.com
Université de Mons, Mons, Belgium
Sofer, Ariela . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-44
asofer@gmu.edu
SEOR, George Mason University, Fairfax, VA, United States
Sohoni, Milind . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-03
milind_sohoni@isb.edu
Indian School of Business, Hyderabad, India
Sola, José Miguel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-41
jmsola@repsol.com
Advanced Control, Petronor, Repsol, Muskiz, Spain
Solan, Eilon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-24
eilons@post.tau.ac.il
Tel Aviv University, Tel Aviv, Israel
Solano, Jaime . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-29
jaimesolanonoriega@hotmail.com
Universidad Autónoma de Ciudad Juárez, Mexico
Solar, Mauricio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-25
mauricio.solar@usm.cl
Informatica, Universidad Tecnica Federico Santa Maria, Valparaiso, Valparaiso, Chile
Smith-Miles, Kate . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-18, FC-50
kate.smith-miles@sci.monash.edu.au
Monash University, Melbourne, Australia
Soldatyuk, Nataliya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-42
nsoldatyuk@gmail.com
Department of Econometrics, University of Economics,
Prague, Prague, Czech Republic
Snelder, Maaike . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-25
maaike.snelder@tno.nl
Civil Engineering, Delft University of Technology, Delft,
Zuid Holland, Netherlands
Soler, Edilaine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-10, MD-43
edilaine@fc.unesp.br
Departamento de Matemática, Faculdade de Ciências, UNESP - Univ Estadual Paulista, Bauru, SP, Brazil
Snyman, Dirk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-16
dirk.snyman@nwu.ac.za
School of Computer, Statistical and Mathematical Sciences,
North-West University, South Africa
Solsona, Francesc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-45
francesc@diei.udl.cat
Computer Science, University of Lleida, Lleida, Catalunya,
Spain
So, Mee Chi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-40, FB-43
M.So@soton.ac.uk
Southampton Management School, University of Southampton, Southampton, United Kingdom
Solymosi, Tamás . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-44
tamas.solymosi@uni-corvinus.hu
Operations Research, Corvinus University of Budapest, Budapest, Hungary
Soares Boaventura, Ricardo . . . . . . . . . . . . . . . . . . . . . . . . . FB-10
ricardoboaventura@iftm.edu.br
Informática, Instituto Federal do Triângulo Mineiro - Campus Uberlândia Centro, Uberlandia, Minas Gerais, Brazil
Somervuori, Outi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-18
Outi.Somervuori@Aalto.fi
Aalto University School of Business, Helsinki, Finland
Soares de Mello, João Carlos . . . . . . . . . . HD-10, TB-14, TD-14
jcsmello@pesquisador.cnpq.br
Engenharia de Produção, Universidade Federal Fluminense,
Rio de Janeiro, RJ, Brazil
Soares Junior, Pedro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-26
pedroasoaresjr@gmail.com
Mathematics, State University of Piaui, Teresina, Piauí,
Brazil
Soares, Ana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-09
argsoares@gmail.com
INESC Coimbra, Coimbra, Portugal
406
Sommersguter-Reichmann, Margit. . . . . . . . . . . . . . . . . . MA-39
margit.sommersguter@uni-graz.at
Department of Finance, University of Graz, Graz, Austria
Son, Jiyoon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-09
imangela@snu.ac.kr
Business Administration, Seoul National University, Korea,
Republic Of
Son, Jung-Ryoul . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-13
jlson@dsme.co.kr
DSME R&D Institute, Daewoo Shipbuilding & Marine Engineering, Geoje-si, Gyeongsangnam-do, Korea, Republic Of
Sonetti, Giulia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-08
IFORS 2014 - Barcelona
giulia.sonetti@polito.it
DIST - Interuniversity Department of Regional & Urban
Studies and Planning, Politecnico di Torino, Turin, Italy, Italy
Song, Jeannette . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-27
jssong@duke.edu
Fuqua School of Business, Duke University, Durham, NC,
United States
Song, Yanan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-23
syn_413@163.com
Industrial Engineering, Tsinghua University, Beijing, China
Song, Yongjia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-02
ysong3@vcu.edu
Statistical Sciences and Operations Research, Virginia Commonwealth University, Richmond, VA, United States
Sönmezer, Serkan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-12
serkansonmezer@gmail.com
Institute of Sciences of Selçuk University, Selçuk Universty,
Konya, Turkey
Sopko, Stanislav . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-16
rabdelfakin@gmail.com
Department of Econometrics, University of Economics,
Prague, Praha 3, Prague, Czech Republic
Sörensen, Kenneth . . . . . . . . . . . . . . . . . . . . FA-23, FB-23, HD-44
kenneth.sorensen@uantwerpen.be
Faculty of Applied Economics, University of Antwerp,
Antwerpen, Belgium
Soriano, Patrick. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-18
patrick.soriano@hec.ca
Management Sciences, HEC Montreal, Montreal, Québec,
Canada
Soriguera, Francesc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-04
francesc.soriguera@upc.edu
Transport and Regional Planning, BarcelonaTech, Barcelona,
Barcelona, Spain
Sorin, Sylvain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-28
sorin@math.jussieu.fr
Université Paris 6, Institut de Mathématiques de Jussieu,
Paris, France
Sorkun, Metehan Feridun . . . . . . . . . . . . . . . . . . . . . . . . . . MD-40
metehansorkun@gmail.com
Management, Ca Foscari University of Venice, Venice, Italy
Sorrentino, Gregorio . . . . . . . . . . . . . . . . . . . . . . . . HB-05, HE-05
gsorrentino@deis.unical.it
DEIS-Dipartimento di Elettronica, Informatica e Sistemistica, Università della Calabria, Rende (CS), Italy
Sosevic, Uros . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-34
sosevic.uros@fon.bg.ac.rs
Laboratory for multimedia communications, University of
Belgrade, Faculty of Organizational Sciences, Belgrade, Serbia
Sosic, Greys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-22
sosic@marshall.usc.edu
Marshall School of Business, University of Southern California, Los Angeles, CA, United States
Sotiros, Dimitrios-Georgios . . . . . . . . . . . . . . . . . . . . . . . . . HB-10
dsotiros@unipi.gr
Department of Informatics, University of Piraeus, Piraeus,
Greece
AUTHOR INDEX
Soto, Ricardo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-25
ricardo.soto@ucv.cl
Computer Science, Pontificia Universidad Católica de Valparaíso, Valparaíso, Chile
Soto-Silva, Wladimir E. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-36
soto.wladimir@gmail.com
Programa de Doctorado en Ingeniería y Tecnologías de la
Información, Universidad de Lleida, Lleida, Spain
Sotomayor Alzamora, Guina . . . . . . . . . . . . . . . . . . . . . . . . FB-03
guinas@gmail.com
Eng. Industrial, PUC-Rio, Rio de Janeiro, Rio de Janeiro,
Brazil
Soubeyran, Antoine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-14
antoine.soubeyran@univ-amu.fr
GREQAM, Université de Aix-Marseille, Marseille, France
Soufivand, Mona . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-09
m.soufivand@gmail.com
University of Palermo, Italy
Soumis, Francois . . . . . . . . . . . . TA-02, MA-03, MD-03, MA-43
francois.soumis@gerad.ca
GERAD, Montreal, Québec, Canada
Sousa, Vanusa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-43
vanusa@ufscar.br
Universidade Federal de São Carlos, São Carlos, Brazil
Souyris, Sebastian. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-20
sebastian.souyris@utexas.edu
McCombs School of Business, University of Texas at Austin,
Austin, United States
Souza, Reinaldo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-29
reinaldo@ele.puc-rio.br
Departamento de Engenharia Elétrica, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
Sowlati, Taraneh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-38
taraneh.sowlati@ubc.ca
Wood Science, University of British Columbia, Vancouver,
BC, Canada
Soyertem, Mustafa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-18
mustafa.soyertem@usak.edu.tr
Mathematics, Uşak University, Uşak, Turkey
Soysal, Mehmet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-41, MA-42
mehmet.soysal@wur.nl
Operations Research and Logistics, Wageningen University,
Wageningen, Netherlands
Sparkes, Imogen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-12
I.Sparkes@exeter.ac.uk
Biosciences, University of Exeter, Exeter, United Kingdom
Speksma, Flora . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-19
spieksma@math.leidenuniv.nl
Leiden University, Leiden, Netherlands
Spengler, Thomas . . . . . . . . . . . . . . . . . . . . . TD-08, FB-13, TA-27
t.spengler@tu-bs.de
Institute of Automotive Management and Industrial Production, Technische Universität Braunschweig, Braunschweig,
Germany
Speranza, M. Grazia . . . . . . . . . . . . . . . . . . . . . . . . . FA-06, HB-45
speranza@eco.unibs.it
407
AUTHOR INDEX
IFORS 2014 - Barcelona
Dept. of Quantitative Methods, University of Brescia, Brescia, Italy
Quantitative Methods for Economics and Business Sciences,
Università Milano Bicocca, Milano, Italy
Spiers, Gregoire . . . . . . . . . . . . . . . . . . . . . ME-03, TB-03, MA-28
gregoire.spiers@amadeus.com
Amadeus, France
Štefánik, Miroslav . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-23
miroslav.stefanik@savba.sk
Institute of Economic Research, Slovak Academy of Sciences, Bratislava, Slovakia
Spiliotis, Evangelos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-09
vangspiliot@gmail.com
School of Electrical and Computer Engineering, National
Technical University of Athens, Athens, Greece
Spinler, Stefan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-09
stefan.spinler@whu.edu
Kuehne Foundation Endowed Chair in Logistics Management, WHU - Otto Beisheim School of Management, Vallendar, Germany
Springael, Johan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-23
johan.springael@ua.ac.be
Faculty of Applied Economics, University of Antwerp,
Antwerp, Belgium
Spyridakos, Athanasios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-18
tspyr@teipir.gr
Mathematics, TEI of Piraeus, Aigaleo, Athens, Greece
Stahel, Werner . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-38
stahel@stat.math.ethz.ch
Eidgenössische Technische Hochschule Zürich, Zurich,
Switzerland
Stangl, Claudia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-28
claudia.stangl@uni-due.de
Mathematics, University of Duisburg-Essen, duisburg, Germany
Stankovic, Jelena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-29
jelena.stankovic@eknfak.ni.ac.rs
Department of Accounting, Mathematics and Informatics,
University of Nis, Faculty of Economics, Nis, Serbia
Starcevic, Dusan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-32
starcev@fon.rs
Faculty of Organizational Sciences, University of Belgrade,
Belgrade, Serbia
Stasinakis, Charalampos . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-26
stasinakis.charalampos@gmail.com
University of Glasgow, Glasgow, United Kingdom
Staudigl, Mathias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-24
mathias.staudigl@uni-bielefeld.de
Center for Mathematical Economics, Bielefeld University,
Bielefeld, Germany
Støer Ødegård, Stian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-03
stiancid@gmail.com
University of Oslo, Oslo, Oslo, Norway
Stålhane, Magnus . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-05, TE-05
magnus.stalhane@marintek.sintef.no
Industrial Economics and Technology Management, NTNU,
Trondheim, Norway
Steenmans, Ine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-38
ine.steenmans.09@ucl.ac.uk
Civil Engineering, University College London, LONDON,
United Kingdom
Stefani, Silvana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-08
silvana.stefani@unimib.it
408
Stefánsdóttir, Bryndís . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-08
bryndis.stefansdottir@tum.de
TUM School of Management, Technische Universität
München, München, Germany
Steglich, Mike . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-30
mike.steglich@th-wildau.de
Technical University of Applied Sciences Wildau, Germany
Steiner Neto, Pedro . . . . . . . . . . . . . . . . . . . . . . . . . MA-08, MB-32
pedrosteiner@ufpr.br
Business, Federal University at Paraná, Curitiba, Pr., Brazil
Steiner, Winfried . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-19
winfried.steiner@tu-clausthal.de
Marketing, Clausthal University of Technology, Institute of
Management and Economics, Clausthal-Zellerfeld, Germany
Steinker, Sebastian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-19
Sebastian.Steinker@the-klu.org
Supply Chain and Operations Strategy, Kühne Logistics University, Hamburg, Hamburg, Germany
Steinshamn, Stein Ivar . . . . . . . . . . . . . . . . . . . . . . TE-07, MA-36
stein.steinshamn@nhh.no
Department of Business and Management Science, Norwegian School of Economics (NHH), Bergen, Norway
Stepanova, Natalia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-13
natalia0410@rambler.ru
Tomsk Polytechnic University, Tomsk, Russian Federation
Steponavice, Ingrida . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-18
ingrida.steponavice@monash.edu
School of Mathematical Sciences, Monash University, Clayton, Vic, Australia
Sterna, Malgorzata . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-13
Malgorzata.Sterna@cs.put.poznan.pl
Institute of Computing Science, Poznan University of Technology, Poznan, Poland
Sternbeck, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-19
Michael.Sternbeck@ku-eichstaett.de
Supply Chain Management and Operations, Catholic University of Eichstaett-Ingolstadt, Ingolstadt/Donau, Germany
Steuer, Ralph E. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-08, TA-34
rsteuer@uga.edu
Terry College of Business, University of Georgia, Athens,
GA, United States
Stevanato, Elisa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-36
elisa.stevanato@gmail.com
University of Brescia, Brescia, Italy
Stewart, Theodor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-31
Theodor.Stewart@uct.ac.za
Statistical Sciences, University of Cape Town, Rondebosch,
South Africa
Stieber, Anke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-33
anke.stieber@hsu-hh.de
Helmut Schmidt University, Germany
IFORS 2014 - Barcelona
Stier-Moses, Nicolas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-28
nstier@utdt.edu
UTDT, Argentina
Stoikov, Sasha . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-34
sashastoikov@gmail.com
Cornell University, Ithaca, United States
Stokic, Dejan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-34
sdeyan@gmail.com
DataMain, Frankfurt, Germany
AUTHOR INDEX
Stützle, Thomas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-33
stuetzle@ulb.ac.be
IRIDIA, Université Libre de Bruxelles, Brussels, Belgium
Su, Zhonghua . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-07
zhonghuasu@iot.ntnu.no
Department of Industrial Economics and Technology Management, NTNU, Norway
Suñagua-Salgado, Porfirio. . . . . . . . . . . . . . . . . . . . . . . . . . . TD-17
porfirio@ime.unicamp.br
Applied Mathematics, University of Campinas, Campinas,
Bolivia
Stoklasa, Jan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-26
jan.stoklasa@upol.cz
Dept. of Mathematical Analysis and Applications of Mathematics, Faculty of Science, Palacky University Olomouc,
Olomouc, Czech Republic
Subramanian, Anand . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-02
anandsubraman@gmail.com
Departamento de Engenharia de Produção, Universidade
Federal da Paraíba, João Pessoa, Paraíba, Brazil
Stolletz, Raik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-03, FA-13
stolletz@bwl.uni-mannheim.de
Chair of Production Management, University of Mannheim,
Mannheim, Germany
Subulan, Kemal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-15
kemal.subulan@deu.edu.tr
Industrial Engineering, Dokuz Eylül University, Izmir,
Turkey
Strasdat, Nico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-14
nico.strasdat@tu-dresden.de
Department of Mathematics, Technische Universität Dresden, Dresden, Germany
Sucha, Premysl . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-08
suchap@fel.cvut.cz
Department of Control Engineering, Czech Technical University, Faculty of Electrical Engineering, Prague, Czech
Republic
Strazzeri, Roberto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-09
strarobypa@gmail.com
Via placido mandanici 14, Palermo, Italy
Street, Alexandre. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-10
street@ele.puc-rio.br
Electrical Engineering, Pontifical Catholic University of Rio
de Janeiro (PUC-Rio), Rio de Janeiro, Rio de Janeiro, Brazil
Suhl, Leena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-04, HA-12
suhl@upb.de
Int. Graduate School of Dynamic Intelligent Systems, University of Paderborn, Paderborn, Germany
Strehler, Martin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-04
strehler@math.tu-cottbus.de
BTU Cottbus, Cottbus, Germany
Sukhov, Pavel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-39
pavelandreevith@gmail.com
Laboratory of Algorithms and Technologies for Networks
Analysis, National Research University Higher School of
Economics, Bogorodsk, Nizhny Novgorod region, Russian
Federation
Streitferdt, Felix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-43
felix.streitferdt@th-nuernberg.de
Business School, Nuremberg Institute of Technology, Nuremberg, Germany
Sullivan, Kelly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-40
ksulliv@uark.edu
Industrial Engineering, University of Arkansas, Fayetteville,
AR, United States
Strijov, Vadim . . . . . . . . . . FA-16, HA-16, HB-16, TB-16, TE-16
strijov@ccas.ru
Russian Academy of Sciences, Computing Center, Moscow,
Russia, Russian Federation
Suman, Ravi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-44
ravisuman2008@gmail.com
Industrial & Systems Engineering, Indian Institute of Technology, Kharagpur, Kharagpur, West Bengal, India
Strohhecker, Jürgen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-15
j.strohhecker@frankfurt-school.de
Management Research Centre, Frankfurt School of Finance
& Management, Frankfurt am Main, Germany, Germany
Sumper, Andreas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-10
asumper@irec.cat
IREC, Sant Adria de Besos, Spain
Strugnell, Dave . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-34
dave.strugnell@uct.ac.za
Actuarial Science, University of Cape Town, Rondebosch,
Western Cape, South Africa
Studenikina, Liudmila . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-05
las_engin@mail333.com
International Business, Russian State University Oil and Gas,
Moscow, Russian Federation
Stummer, Christian . . . . . . . . . . . . . . . . . . . . . . . . . HB-35, MA-44
christian.stummer@uni-bielefeld.de
Department of Business Administration and Economics,
Bielefeld University, Bielefeld, Germany
Sun, Bo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-20
bo-sun-1@uiowa.edu
Mechanical and Industrial Engineering, University of Iowa,
Iowa City, Iowa, United States
Sun, Cong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-14
suncong86@bupt.edu.cn
School of Science, Beijing University of Posts and Telecommunications, Beijing, China
Sun, Wei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-15
sunw@us.ibm.com
Service Science, IBM Watson Research Center, Yorktown,
NY, United States
Sunjerga, Snjezana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-28
409
AUTHOR INDEX
IFORS 2014 - Barcelona
snjezana@petrostreamz.com
PERA, Trondheim, Norway
Süss, Philipp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-18
philipp.suess@itwm.fraunhofer.de
Optimization, Fraunhofer Institute for Industrial Mathematics ITWM, Kaiserslautern, Germany
Sustersic, Olga . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-42
olga.sustersic@gmail.com
Faculty of Health Sciences, University of Ljubljana, Ljubljana, Slovenia
Suzuki, Atsuo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-30
atsuo@urban.meijo-u.ac.jp
Meijo University, Japan
Suzuki, Teruyoshi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-30
suzuki@econ.hokudai.ac.jp
Graduate School of Economics, Hokkaido University, Sapporo, Hokkaido, Japan
Suzuki, Tsutomu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-03
tsutomu@risk.tsukuba.ac.jp
Faculty of Engineeing, Information and Systems, University
of Tsukuba, Tsukuba, Ibaraki, Japan
Swaminathan, Jayashankar . . . . . . . . . . . . . . . . . . . . . . . . MD-19
msj@unc.edu
The Kenan-Flagler Business School, The University of North
Carolina, Chapel Hill, North Carolina, United States
Swaroop, Prem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-03
pswaroop@rhsmith.umd.edu
RH Smith School of Business and Institute for Systems Research, University of Maryland, College Park, MD, United
States
Swendgaard, Hans Erik . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-03
Hans.E.Swendgaard@sintef.no
Sintef Ict, Trondheim, Norway
Syafari, Syafari . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-17
syafari_aman@yahoo.com
Mathematics, University Negeri Medan, Indonesia
Syed Ali, Sharifah Aishah . . . . . . . . . . . . . . . . . . . . . . . . . . MB-41
sharifah-aishah-binti-syed-ali@strath.ac.uk
Management Science, University of Strathclyde, Glasgow,
Scotland, United Kingdom
Szabo, Jacint . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-01
jsz@zurich.ibm.com
Business Optimization, IBM Research Lab, Zurich, Rüschlikon, Switzerland
Szałucka, Małgorzata . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-37
m.szalucka@umk.pl
The Department of Investment and Real Estate, Nicolaus
Copernicus University in Toruń, The Faculty of Economic
Sciences and Management, Toruń, Poland
Szmerekovsky, Joseph . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-12
Joseph.Szmerekovsky@ndsu.edu
Management and Marketing, North Dakota State University,
Fargo, North Dakota, United States
caner.taskin@boun.edu.tr
Department of Industrial Engineering, Boğaziçi University,
İstanbul, Turkey
Tabatabaei, Seyed Mohammad Mehdi . . . . . . . . . . . . . . . MD-18
mohammad.tabatabaei@jyu.fi
Dept. of Mathematical Information Technology, University
of Jyväskylä, Jyväskylä, Finland
Tachibana, Vilma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-42
vilma@fct.unesp.br
Statistics, UNESP, Presidente Prudente, São Paulo, Brazil
Tadj, Lotfi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-30
ltadj@fdu.edu
Information Systems and Decision Sciences, Fairleigh Dickinson University Information Systems and Decision Sciences
„ Vancouver, BC, Canada
Tae-Eog, Lee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-13
telee@kaist.ac.kr
Industrial Engineering, KAIST, Daejon, Korea, Republic Of
Taghipour, Atour . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-41
atour.taghipour@univ-lehavre.fr
Faculty of International Business, University of Le Havre, Le
Havre, France
Taguchi, Masashi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-30
taguchi@adk.jp
Marketing Science Division, Asatsu- Dk Inc., Tokyo, Japan
Tahar, Mehenni . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-14
tmehenni@gmail.com
Computer Science, University of M’sila, Algeria
Tahbaz-Salehi, Alireza . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-06
alirezat@columbia.edu
Columbia Business School, Columbia University, New York,
NY, United States
Taheri, Nicole . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-35, MA-43
nicole.taheri@ie.ibm.com
IBM Research Ireland, Dublin, Ireland
Tai, Yu-Ting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-27
yttai@mail.knu.edu.tw
Kainan University, Taiwan
Takafumi, Katakai . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-30
mf13024@shibaura-it.ac.jp
Systems Engineering and Sciencemathmatical, Shibaura Institute of Technology, Graduate School of Engineering and
Science, Saitama-shi, Saitama-ken, Japan
Takahashi, Hirotaka . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-30
hirotaka@kjs.nagapkaut.ac.jp
Department of Management and Information System Science, Nagaoka University of Technology, Nagaoka, Niigata,
Japan
Takehara, Hitoshi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-30
takehara@waseda.jp
Graduate School of Finance, Accounting and Law, Waseda
University, Chuo-ku, Tokyo, Japan
Szomolányi, Karol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-15
szomolan@euba.sk
University of Economics in Bratislava, Bratislava, Slovakia
Takeuchi, Satoshi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-27
takeuchi-satoshi_3to4@hotmail.co.jp
Promotion Department, Kyoto College of Graduate School
for Informatics, Kyoto, Japan
Taşkın, Z. Caner . . . . . . . . . . . . . . . . . . . . . HE-11, HD-31, HB-43
Tako, Antuela . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-23
410
IFORS 2014 - Barcelona
a.takou@lboro.ac.uk
School of Business and Economics, Loughborough University, Loughborough, United Kingdom
Takumi, Tomatsu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-30
mf14035@shibaura-it.ac.jp
Mathematical Sciences, Shibaura Institute of Technology,
Ssitama-city, Saitama, Japan
Talafuse, Thomas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-45
tptalafu@email.uark.edu
Industrial Engineering, University of Arkansas, Fayetteville,
AR, United States
Talarico, Luca . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-23, HD-44
luca.talarico@ua.ac.be
Faculty of Applied Economics, University of Antwerp,
Antwerp, Belgium
Talasova, Jana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-26, TD-26
jana.talasova@seznam.cz
Dept. of Mathematical Analysis and Applications of Mathematics, Faculty of Science, Palacky University Olomouc,
Olomouc, Czech Republic
Talbi, El-ghazali . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-06
El-ghazali.Talbi@lifl.fr
University of Lille - INRIA - CNRS, Lille, France
Talias, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-10
michael.talias@ouc.ac.cy
Healthcare Management, Open University of Cyprus,
Nicosia, Cyprus
Talis, Vadim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-41
talisv@yahoo.com
Jerusalem College of Technology, Jerusalem, Israel
Talla Nobibon, Fabrice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-35
fabrice.tallanobibon@kuleuven.be
Decision Sciences and Information Management, KU Leuven, Leuven, Belgium
Talluri, Kalyan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-15
kalyan.talluri@upf.edu
University of Pompeu Fabra, Barcelona, Spain
Talssi, Samir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-09
samirtalssi@gmail.com
Department of Mathematics and Computer Science, Faculty
of Sciences Ben M’sik Hassan II University Mohammedia
Morocco, Casablanca, Morocco
Tamarit, Jose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-21, HD-21
jose.tamarit@uv.es
Dpt. Statistics and Operations Research, University of Valencia, Burjassot, Spain
Tamber, Jighjigh Abraham . . . . . . . . . . . . . . . . . . . . . . . . . . FB-04
tjighjigh@yahoo.com
Mathematics Department„ Nigerian Defence Academy
Kaduna, Kaduna Nigeria, Kaduna, Kaduna, Nigeria
AUTHOR INDEX
Tanaka, Mario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-38
tanakafi@gmail.com
Federal University of the Wets of Para, Santarém, Para, Brazil
Tanaka, Tamaki . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-37, ME-37
tamaki@math.sc.niigata-u.ac.jp
Mathematics, Niigata University, Niigata, Niigata, Japan
Tanaka, Yuma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-09, TB-39
ytanaka@st.seikei.ac.jp
Seikei University, Japan
Tanasescu, Cerasela . . . . . . . . . . . . . . . . . . . . . . . . . MA-12, TB-32
tanasescu@essec.edu
ESSEC Business School, Cergy, France
Tanash, Moayad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-31
tanash25@yahoo.com
Mechanical and Industrial Engineering, Concordia university, Montreal, Canada
Tancrez, Jean-Sébastien . . . . . . . . . . . . . . . . . . . . . MD-04, HA-07
js.tancrez@uclouvain.be
Louvain School of Management, Université catholique de
Louvain, Mons, Belgium
Taneri, Niyazi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-22
niyazitaneri@sutd.edu.sg
ESD, SUTD, Singapore, Singapore
Tang, Bo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-22
botang1@liv.av.uk
University of Liverpool, Liverpool, United Kingdom
Tang, Christopher. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-24
ctang@anderson.ucla.edu
UCLA Anderson School, Los Angeles, CA, United States
Tang, Lixin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-20
lixintang@mail.neu.edu.cn
The Logistics Institute, Northeastern University, Shenyang,
China
Tang, Victor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-34
victor.w.tang@gmail.com
i3nsight, Pleasantville, New York, United States
Tang, Xijin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-23
xjtang@iss.ac.cn
Lab on Management, Decision and Information Systems,
CAS Academy of Mathematics & Systems Science, Beijing,
China
Tang, Xin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-04
tangxinwh@hotmail.fr
Ecole des Mines de Nantes, IRCCyN UMR CNRS 6597,
Nantes, France
Tangian, Andranik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-24
andranik-tangian@boeckler.de
WSI, Hans Boeckler Foundation, Duesseldorf, Germany
Tammer, Christiane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-18
christiane.tammer@mathematik.uni-halle.de
Mathematics and Computer Science, Martin-LutherUniversity Halle-Wittenberg, Halle, Germany
Taniguchi, Eiichi . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-06, ME-42
taniguchi@kiban.kuciv.kyoto-u.ac.jp
Department of Urban Management, Kyoto University, Kyoto,
Japan
Tanaka, Keiichi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-30
tanaka-keiichi@tmu.ac.jp
Graduate School of Social Sciences, Tokyo Metropolitan
University, Hachiouji, Tokyo, Japan
Tanino, Tetsuzo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-35, ME-37
tanino@eei.eng.osaka-u.ac.jp
Division of Electrical, Electronic and Information Engineering, Osaka University, Suita, Osaka, Japan
411
AUTHOR INDEX
IFORS 2014 - Barcelona
Tanrisever, Fehmi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-24
tanrisever@bilkent.edu.tr
Faculty of Business Administration, Bilkent University,
Ankara, Turkey
Tanrıverdi, Aydın . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-22
atanriverdi@dogus.edu.tr
Industrial Engineering, Doğuş University, İstanbul, Turkey
Tar, Péter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-21, HE-33
tar@dcs.uni-pannon.hu
Department of Computer Science and Systems Technology,
University of Pannonia, Veszprém, Hungary, Hungary
Tarantilis, Christos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-14
tarantil@aueb.gr
Department of Management Science & Technology, Athens
University of Economics and Business, Athens, Greece
Tarim, Armagan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-13
armtar@yahoo.com
Management, Hacettepe University, Ankara, Turkey
Tatsumi, Keiji . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-37
tatsumi@eei.eng.osaka-u.ac.jp
Division of Electrical, Electronic and Information Engineering, Osaka University, Suita, Osaka, Japan
Tauchnitz, Nico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-07
tauchnitz@math.tu-cottbus.de
Mathematisches Institut, BTU Cottbus-Senftenberg, Cottbus,
Germany
Tavanti, Luca . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-11
luca.tavanti@iet.unipi.it
Dip. Ingegneria dell’Informazione, Università di Pisa, Pisa,
Italy
Tavasszy, Lorant . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-04, MB-06
lori.tavasszy@tno.nl
TU Delft / TNO, Netherlands
Tavella, Elena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-23, HA-38
eta@ifro.ku.dk
Department of Food and Resource Economics, University of
Copenhagen, Denmark
Taylan, Pakize . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-43
pakizetaylan@yahoo.com
Mathematics, Dicle University, Diyarbakır, Turkey
Taylor, Nicholas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-33
ntaylor@dstl.gov.uk
Policy & Capability Studies, Dstl, Fareham, Hants, United
Kingdom
Teboulle, Marc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-38
teboulle@math.tau.ac.il
School of Mathematical Sciences, Tel Aviv University, TelAviv, Israel
Teghem, Jacques . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-14, TE-41
jacques.teghem@umons.ac.be
MathRO, Faculté Polytechnique/UMonss, Mons, Belgium
Teixeira de Almeida, Adiel . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-42
almeidaatd@gmail.com
Management Engineering, Universidade Federal de Pernambuco - UFPE, Recife, PE, Brazil
Teixeira, Leandro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-33
412
ldteixeira@fc.ul.pt
CIO-FCUL, University of Lisbon, Lisboa, Portugal
Tekin, Mahmut . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-18
mahtekin@selcuk.edu.tr
Business Administration, Selcuk University, Turkey
Tekin, Salih . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-35
stekin@etu.edu.tr
Industrial Engineering, TOBB University of Economics and
Technology, Turkey
Telelis, Orestis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-22
telelis@gmail.com
Department of Informatics, Athens University of Economics
and Business, Athens, Greece
Telemsani, Mehdi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-18
mehdi.telemsani@uclouvain-mons.be
Ois, Université Catholique de Louvain - Mons, Maurage,
Belgium
Telha, Claudio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-41
claudio.telha@uclouvain.be
Université catholique de Louvain, Louvain-La-Neuve, Belgium
Temiz, İzzettin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-14
itemiz@gazi.edu.tr
Faculty of Engineering Industrial Engineering Department,
Gazi University, Ankara, Turkey
Teo, Chung Piaw . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-16
bizteocp@nus.edu.sg
National University of Singapore, Singapore, Singapore
Teo, Joel S-E . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-06
joel.teo@kiban.kuciv.kyoto-u.ac.jp
Urban Management, Kyoto University, Kyoto, Kyoto, Japan
Teo, Kwong Meng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-16
kwongmeng@alum.mit.edu
Industrial & Systems Engineering, National University of
Singapore, Singapore
Terlaky, Tamás . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-17
terlaky@lehigh.edu
Industrial and Systems Engineering, Lehigh University, Bethlehem, Pennsylvania, United States
Tervonen, Tommi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-24
tervonen@ese.eur.nl
Econometric Institute, Erasmus University Rotterdam, Rotterdam, Netherlands
Testuri, Carlos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-35
ctesturi@fing.edu.uy
Investigación Operativa, Facultad de Ingeniería. Universidad
de la República, Montevideo, Uruguay
Teunter, Ruud . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-32
r.h.teunter@rug.nl
Operations, University of Groningen, Groningen, Netherlands
Teytelboym, Alex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-06
t8el@mit.edu
EECS, MIT, Cambridge, MA, United States
Tezcaner Ozturk, Diclehan . . . . . . . . . . . . . . . . . . . HE-18, TE-20
diclehantezcaner@gmail.com
University of Strathclyde, Glasgow, United Kingdom
IFORS 2014 - Barcelona
Thaller, Carina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-06
thaller@itl.tu-dortmund.de
Institute of Transport Logistics, TU Dortmund, Dortmund,
Nordrhein-Westfalia, Germany
Thanassoulis, Emmanuel . . . . . . . . . . . . . . . . . . . . HB-10, ME-14
e.thanassoulis@aston.ac.uk
Aston Business School, Aston University, Birmingham,
United Kingdom
Theobald, Thorsten . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-16
theobald@math.uni-frankfurt.de
Goethe University Frankfurt, Frankfurt am Main, Germany
Theofilatos, Konstantinos A. . . . . . . . . . . . . . . . . . . . . . . . . MD-26
theofilk@ceid.upatras.gr
University of Patras, Patras, Greece
Thiard, Florence . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-13, MB-28
florence.thiard@grenoble-inp.org
G-SCOP, Grenoble, Grenoble, France
Thiel, Daniel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-08
daniel.thiel@univ-paris13.fr
Université Paris 13, Sorbonne Paris Cité, Paris, France
Thiele, Aurelie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-15
aurelie.thiele@lehigh.edu
Industrial and Systems Engineering, Lehigh University, Bethlehem, PA, United States
AUTHOR INDEX
sity of Denmark, Lyngby, Denmark
Thorne, Alan. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-03
ajt@eng.cam.ac.uk
Engineering Department, University of Cambridge, Cambridge, United Kingdom
Thun, Kristian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-05
kristian.thun@iot.ntnu.no
Department of industrial economics and technology management, Norwegian University of Science and Technology,
Trondheim, Norway
Thunig, Theresa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-04
thunig@vsp.tu-berlin.de
TU Berlin, Berlin, Germany
Tian, Fang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-22
tianfang@usc.edu
University of Southern California, Los Angeles, United
States
Tiapo, Napoleon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-12
Napoleon.Tiapo@oneonta.edu
Upper Great Plains Transportation Institute, Fargo, North
Dakota, United States
Tiddi, Daniele . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-41
daniele.tiddi@uniroma1.it
DITS, University of Rome "Sapienza", Rome, Italy
Thies, Thorsten . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-14
thorsten.thies@cognitec.com
Cognitec Systems GmbH, Dresden, Germany
Tierney, Kevin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-05, HE-05
kevin.tierney@upb.de
Business Information Systems, University of Paderborn,
Paderborn, Germany
Thom, Elmien . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-11
16036115@sun.ac.za
Department of Logistics, Stellenbosch University, Paarl,
South Africa
Tieves, Martin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-11
tieves@math2.rwth-aachen.de
Lehrstuhl II für Mathematik, RWTH Aachen University, Germany
Thom, Lisa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-01
lisa.thom.kassel@googlemail.com
Georg-August University Goettingen, Goettingen, Germany
Tilson, Vera . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-12, HA-43
vera.tilson@simon.rochester.edu
University of Rochester, Rochester, United States
Thomas, Barrett . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-41
barrett-thomas@uiowa.edu
Management Sciences, University of Iowa, Iowa City, IA,
United States
Timmermans, Harry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-32
H.J.P.Timmermans@tue.nl
TU/e, Eindhoven, Netherlands
Thomas, Lyn . . . . . . . . . . . . . . . . . . . . . . . . . HA-27, HE-40, FB-43
l.thomas@soton.ac.uk
School of Managemento, University of Southampton,
Southampton, Hants, United Kingdom
Thomas, Valerie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-20, TA-20
valerie.thomas@isye.gatech.edu
Industrial and Systems Engineering, Georgia Institute of
Technology, Atlanta, GA, United States
Thorbjornsson, Agust . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-19
agust@framsaekni.is
School of Science and Engineering, Reykjavik University,
Reykjavik, Iceland
Thorlacius, Per . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-01
pthorlacius@s-tog.dsb.dk
Production Development, DSB S-tog, Taastrup, Denmark
Thorlund Haahr, Jørgen . . . . . . . . . . . . . . . . . . . . HB-01, MA-28
jhaa@dtu.dk
Department of Management Engineering, Technical Univer-
Tindle, John . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-42
TindleAnalytics@gmail.com
Tindle Analytics LLC, Monument, Colorado, United States
Tinga, Tiedo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-32
t.tinga@nlda.nl
Netherlands Defence Academy, Den Helder, Netherlands
Tingting, Cong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-27
727638139@qq.com
Applied Information Technology, The Kyoto College of
Graduate School for Informatics, Kyoto, Kyoto, Japan
Tirado, Gregorio . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-11, TD-37
gregoriotd@mat.ucm.es
Estadistica e Investigacion Operativa I, Universidad Complutense de Madrid, Madrid, Spain
Tiwari, Manoj . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-44
mkt09@hotmail.com
Indian Institute of Technology, Kharagpur, Kharagpur, Westbengal, India
413
AUTHOR INDEX
IFORS 2014 - Barcelona
Tobin, Roger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-23
roger.tobin@verizon.com
Business Analytics Group, Verizon Communications,
Waltham, MA, United States
Topaloglu, Seyda . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-02, HB-19
seyda.topaloglu@deu.edu.tr
Industrial Engineering, Dokuz Eylul University, Izmir,
Turkey
Tocoche, Yasmin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-32
ystocoche@alimentoscarnicos.com.co
Universidad San Buenaventura de Cali, Cali, Colombia
Topcu, Y. Ilker . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-33
ilker.topcu@itu.edu.tr
Industrial Engineering, Istanbul Technical University, Istanbul, Turkey
Todosijevic, Raca . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-11
Raca.Todosijevic@univ-valenciennes.fr
LAMIH, Univerisity of Valenciennes, Valenciennes, France
Tofallis, Chris . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-32
c.tofallis@herts.ac.uk
Business School, University of Hertfordshire, Hatfield,
Herts., United Kingdom
Tohidi, Yaser . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-07
tohi@kth.se
EPS, KTH, Stockholm, Outside Canada / US, Sweden
Toledo, Franklina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-21
fran@icmc.usp.br
Applied Mathematics and Statistic, Icmc - Usp, Sao Carlos,
Sao Paulo, Brazil
Tolordava, Zhana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-29
tolordava@hotmail.com
Head of the University Educational and Research Center for
Simulation and Interactive Learning Methods, Tbilisi Ivane
Javakhishvili State Univesity, Tbilisi, Georgia
Toppur, Badri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-11
badri.t@greatlakes.edu.in
Operations Management, Great Lakes Institute of Management, Chennai, Tamil Nadu, India
Topuk, Nihan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-29
n.topuk@iku.edu.tr
İndustrial Engineering, İstanbul Kültür Üniversity, İstanbul,
Turkey
Toriumi, Shigeki . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-03
toriumi@ise.chuo-u.ac.jp
Information and Systems Engineering, Chuo University,
Tokyo, Japan
Törmänen, Juha . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-23
juha.tormanen@aalto.fi
Aalto University School of Science, Espoo, Finland
Torne, Josep Maria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-04
josep.maria.torne@upc.edu
BarcelonaTech-UPC, Barcelona, Catalonia, Spain
Tomala, Tristan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-24
tomala@hec.fr
Economics and Decision Sciences, HEC Paris, Jouy en Josas,
France
Torres, Luis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-02
luis.torres@epn.edu.ec
Mathematics, Escuela Politécnica Nacional, Quito, Pichincha, Ecuador
Tomasella, Maurizio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-03
Maurizio.Tomasella@ed.ac.uk
Business School, University of Edinburgh, Edinburgh, United
Kingdom
Torres, Ramiro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-02
ramiro.torres@epn.edu.ec
Escuela Politécnica Nacional, Quito, Ecuador
Tomasgard, Asgeir . . . . MA-07, HB-09, TD-10, TD-20, HE-29,
MB-45
asgeir.tomasgard@sintef.no
Applied economics and operations research, Sintef Technology and society, Trondheim, Norway
Tomita, Kyohei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-30
mf13051@shibaura-it.ac.jp
Mathematical Sciences, Shibaura Institute of Technology,
Saitama-shi, Saitama-ken, Japan
Tone, Kaoru . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-10
tone@grips.ac.jp
National Graduate Institute for Policy Studies, Tokyo, Japan
Torrico, Alfredo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-28
atorrico@dim.uchile.cl
Universidad de Chile, Santiago, Chile
Torta, Valentina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-31
valentina.torta@gmail.com
Planning, Piemont Region, Torino, Italy
Toth, Paolo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-01
paolo.toth@unibo.it
DEI, University of Bologna, Bologna, Italy
Totic, Selena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-26
selena@fon.rs
Operational Management and Statistics, Faculty of Organizational Sciences, Belgrade University, Belgrade, Serbia
Tong, Chunyang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-27
tong.chunyang@mail.shufe.edu.cn
Operations Management, Shanghai University of Finance
and Economics, Shanghai, Shanghai, China
Touati, Salima . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-31
touati_salima@yahoo.fr
University of Bejaia, Bejaia, Algeria
Tong, Chunyang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-22
tongchunyang@gmail.com
SHUFE, Shanghai, China
Toulouse, Sophie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-11
sophie.toulouse@lipn.univ-paris13.fr
LIPN, University Paris 13, France
Tönissen, Denise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-11
d.d.tonissen@tue.nl
School of Industrial Engineering, Eindhoven University of
Technology, Netherlands
Touri, Behrouz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-06
touri@gatech.edu
Georgia Institute of Technology, Atlanta, GA, United States
414
Tournamille, Jean-François . . . . . . . . . . . . . . . . . . . . . . . . . HA-12
IFORS 2014 - Barcelona
jf.tournamille@chu-tours.fr
CHRU Bretonneau, Tours, France
Toy, Ozgur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-41
ozgur.toy@bilgi.edu.tr
Industrial Engineering, Bilgi University, Istanbul, Turkey
Toyasaki, Fuminori . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-33
toyasaki@yorku.ca
York University, Toronto, Canada
Toyoda, Masashi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-30
mf13053@shibaura-it.ac.jp
Mathematical Finance, Shibaura Institute of Technology
Graduate School, Hasuda, Saitama, Japan
Toyoizumi, Hiroshi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-35
toyoizumi@waseda.jp
Waseda University, Tokyo, Japan
Trabandt, Christian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-16
trabandt@math.uni-frankfurt.de
Discrete Math, Goethe University Frankfurt, Frankfurt am
Main, Germany
Tragler, Gernot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-07
tragler@eos.tuwien.ac.at
OR and Control Systems, Vienna University of Technology,
Vienna, Austria
Tran, Thi Thuy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-17
thuytt@fpt.edu.vn
Lorraine University, France
Tran, Trung Hieu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-03
T.H.Tran@kent.ac.uk
Kent Business School, University of Kent, Canterbury, Kent,
United Kingdom
Traversi, Emiliano . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-28
emiliano.traversi@gmail.com
Fakultät für Mathematik, Technische Universität Dortmund,
Germany
Trdin, Nejc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-42, FB-42
nejc.trdin@ijs.si
Knowledge Management, Jozef Stefan Institute, Ljubljana,
Slovenia
Tresoldi, Emanuele . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-09
emanuele.tresoldi@unimi.it
Università Statale di Milano, Milano, Italy
Trespalacios, Francisco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-29
ftrespal@andrew.cmu.edu
Chemical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Trichakis, Nikos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-18
nikos@hbs.edu
Harvard Business School, United States
Trigeorgis, Lenos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-43
lenos@ucy.ac.cy
Public and Business Administration, University of Cyprus,
Nicosia, Cyprus
Trinks, Christian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-38
christian.trinks@umsicht.fraunhofer.de
Fraunhofer UMSICHT, Germany
Troncoso, Fredy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-25
AUTHOR INDEX
fredytroncoso@gmail.com
Industrial Engineering, University of Bio-Bio, Concepcion,
Región del bio bio, Chile
Troncoso, Juan José . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-36
jtroncot@uc.cl
Department of Industrial Engineering, University of Chile,
Santiago, Chile
Tseng, Hwai-En . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-29
hwai_en@seed.net.tw
Department of Industrial Engineering and Management,
National Chin-Yi University of Technology, Taiping City,
Taichung County, Taiwan
Tsigaridas, Elias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-24
elias.tsigaridas@inria.fr
Team PolSys, Inria - UPMC - LIP6, PARIS, France
Tsitsiklis, John . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-06
jnt@mit.edu
MIT, Cambridge, MA, United States
Tsolakis, Naoum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-35
ntsolaki@auth.gr
Mechanical Engineering, Aristotle University of Thessaloniki, Thessaloniki, Greece
Tsotsolas, Nikos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-18, TD-29
ntsotsol@unipi.gr
Department of Informatics, University of Piraeus, Penteli,
Greece
Tsourdos, Antonios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-40
a.tsourdos@cranfield.ac.uk
Cranfield University, Cranfield, United Kingdom
Tsubaki, Hiroe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-26
tsubaki@ism.ac.jp
The Institute of Statistical Science, Tachikawa, Tokyo, Japan
Tsuji, Akira . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-35
akiratsuji30@gmail.com
Canon Inc., Tokyo, Japan
Tsur, Yacov . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-25
yacov.tsur@mail.huji.ac.il
Agricultural Economics and Management, Hebrew University of Jerusalem, Rehovot, Israel
Tsuzuki, Marcos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-21
mtsuzuki@usp.br
USP - Universidade de Sao Paulo, Sao Paolo, Brazil
Tuncer Sakar, Ceren . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-18
cerents@hacettepe.edu.tr
Industrial Engineering, Hacettepe University, Ankara, Turkey
Turbay, Gabriel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-25
gt.gabrielturbay@gmail.com
Pensamiento Sistemico y Teoria de Juegos, Sociedad Colombiana de Economistas, Bogotá., Cundinamarca, Colombia
Turhan, İlkem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-12
ilkem.turhan@dpu.edu.tr
Art-Science Faculty,
Department of Mathematics,
Dumlupinar University, Kutahya, Turkey
Turkay, Metin . . . . . . . . . . . . . . . . . . . . . . . . HE-28, HB-29, FB-37
mturkay@ku.edu.tr
Department of Industrial Engineering, Koc University, Istanbul, Turkey
415
AUTHOR INDEX
IFORS 2014 - Barcelona
Turner, John . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-15
john.turner@uci.edu
Paul Merage School of Business, UC-Irvine, Irvine, CA,
United States
Ulas, Efehan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-35
ef_ulas@hotmail.com
Statistics, Cankiri Karatekin University, Cankiri, Ballica,
Turkey
Turrini, Laura . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-32
laura.turrini@the-klu.org
Logistics, Kühne Logistics University, Hamburg, Germany
Ulku, Ilayda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-16, FB-16
ilaydakarabulut@gmail.com
Department of Industrial Engineering, Istanbul Kültür University, Istanbul, Turkey
Türsel Eliiyi, Deniz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-25
deniz.eliiyi@ieu.edu.tr
Department of Industrial Engineering, Izmir University of
Economics, Izmir, Turkey, Turkey
Ullrich, Reinhard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-16
reinhard.ullrich@univie.ac.at
Dept. of Statistics and OR, University of Vienna, Wien, Austria
Turskis, Zenonas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-45
zenonas.turskis@vgtu.lt
Construction Technology and Management, Vilnius Gediminas Technical University, Vilnius, Lithuania
Umetani, Shunji . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-40
umetani@ist.osaka-u.ac.jp
Osaka University, Japan
Tüshaus, Ulrich . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-28
ulrich.tueshaus@hsu-hh.de
Operations Research Department, Helmut Schmidt University, Hamburg, Germany
Umezawa, Masashi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-35
umezawa@rs.tus.ac.jp
School of Management, Tokyo University of Science, Kuki,
Saitama, Japan
Tuyttens, Daniel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-21
daniel.tuyttens@umons.ac.be
Mathematics and Operations Research, University of Mons,
Mons, Europe, Belgium
Unal, Ali Tamer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-13
unaltam@boun.edu.tr
Industrial Engineering, Bogazici University, Istanbul, Turkey
Tüzemen, Adem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-43
atuzemen@gmail.com
Business Administration, Tokat Gaziosmanpaşa University,
Faculty of Economics and Administrative Sciences, TOKAT,
Turkey
Tyler, Nick. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-04
n.tyler@ucl.ac.uk
Civil Engineering, UCL, London, United Kingdom
Tzur, Michal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-22
tzur@eng.tau.ac.il
Industrial Engineering, Tel Aviv University, Tel Aviv, Israel
Uchoa, Eduardo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-34
uchoa@producao.uff.br
Engenharia de Produção, Universidade Federal Fluminense,
Niterói, Rio de Janeiro, Brazil
Uckun, Canan . . . . . . . . . . . . . . . . . . . . . . . . HB-15, FB-20, HA-20
canan@anl.gov
Decision and Information Sciences Division, Argonne National Laboratory, United States
Uctug, Gorkem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-08
gorkem.uctug@bahcesehir.edu.tr
Bahceselhir University, Istanbu, Turkey
Udo, Aniefiok . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-44
aniefiok.benedict@gmail.com
Economics, university of calabar, Nigeria, Uyo, Akwa Ibom,
Nigeria
Ueno, Takayuki . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-09
ueno@sun.ac.jp
Department of Economics, University of Nagasaki, Sasebo,
Japan
Ugurlu, Seda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-03
sedayanik@itu.edu.tr
Industrial Engineering, Istanbul Technical University, Istanbul, Turkey
416
Üney-Yüksektepe, Fadime . . . . . FA-11, FA-16, FB-16, ME-21,
TD-21, TE-30, HB-43, HD-43
f.yuksektepe@iku.edu.tr
Industrial Engineering Department, İstanbul Kültür University, İstanbul, Turkey
Ungchittrakool, Kasamsuk . . . . . . . . . . . . . . . . . . . . . . . . . . TA-37
kasamsuku@nu.ac.th
Department of Mathematics, Naresuan University, Phitsanulok, Mueang Phitsanulok, Thailand
Ünlüyurt, Tonguc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-39
tonguc@sabanciuniv.edu
Manufacturing Systems/Industrial Engineering, Sabanci University, Ýstanbul, Turkey
Unuvar, Merve . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-30
munuvar@us.ibm.com
IBM T. J. Watson Research Center, Yorktown Heights, NY,
United States
Upadhyay, Amit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-01
amitupadhyay85@gmail.com
Mechanical Engineering, IIT Delhi, New Delhi, New Delhi,
India
Uratani, Tadashi . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-24, MB-30
uratani@k.hosei.ac.jp
Industrial and System Engineerig, Hosei University, Tokyo,
Japan
Urgo, Marcello . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-13
marcello.urgo@polimi.it
Mechanical Engineering, Politecnico di Milano, Milano,
Italy, Italy
Ursavas, Evrim . . . . . . . . . . . . . . . . . . . . . . . FA-05, FB-05, HB-05
e.ursavas@rug.nl
Operations, University of Groningen, Netherlands
Urzúa, Carolina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-32
curzua@ceap.cl
Centro
de
Estudios
en
Alimentos
Procesados
IFORS 2014 - Barcelona
(CEAP_R09I2001), Curicó, Región del Maule, Chile
Usaola, Julio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-10
jusaola@ing.uc3m.es
Electrical Engineering, University Carlos III, Leganés, Spain
Usberti, Fábio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-09
fusberti@yahoo.com
DENSIS, Universidade Estadual de Campinas, Campinas,
SP, Brazil
Usui, Yuki . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-30
mf13015@shibaura-it.ac.jp
Systems Engineering and Science, Shibaura Institute of Technology, Japan
Vaagen, Hajnalka . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-23
hajnalka.vaagen@sintef.no
Applied Economics and Operations Research, SINTEF,
Trondheim, Norway
Vaez-Ghasemi, Mohsen . . . . . . . . . . . . . . . . . . . . . . HD-10, TE-14
mohsen.vaez@gmail.com
Mathematics, Islamic Azad University, Science and Research
Branch, Tehran, Iran, Islamic Republic Of
Vaidya, Omkarprasad S . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-44
osv@iiml.ac.in
Operations Management, Indian Institute of Management,
Lucknow, Lucknow, India
AUTHOR INDEX
Valls, Vicente . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-12, MA-39
Vicente.Valls@uv.es
Departamento de Estadística e Investigación Operativa, University of Valencia, Valencia, Spain
Valls-Donderis, Pablo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-36
pabvaldo@etsia.upv.es
Universitat Politècnica de València (UPV), Spain
Valton, Pierre-Marie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-29
pierremarie.valton@airliquide.com
Applied Mathematiques, Air Liquide, Les Loges en Josas,
France
van Ackere, Ann . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-15
ann.vanackere@unil.ch
HEC, University of Lausanne, Switzerland
van Ackooij, Wim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-26
wim.van-ackooij@edf.fr
OSIRIS, Edf R&d, Clamart, France
van Arem, Bart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-25
B.vanArem@tudelft.nl
Delft University of Technology, Delft, Zuid Holland, Netherlands
van Dalen, Hans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-33
JA.v.Dalen@mindef.nl
Ministry of Defence, Utrecht, Netherlands
Vainer, Aleksander . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-39
alevai@tx.technion.ac.il
Industrial Engineering and Management, Technion - Israel
Institute of Technology, Haifa, Haifa, Israel
van Dalen, Jan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-19, FA-40
jdalen@rsm.nl
Dept. of Decision and Informatiion Sciences, RSM Erasmus
University, Rotterdam, Netherlands
Valencia Arroyave, Daniela . . . . . . . . . . . . . . . . . . . . . . . . . . TB-40
dany_v.a@hotmail.com
Facultad de arquitectura e ingenieria, Institucion Universitaria Colegio Mayor de Antioquia, Medellin, Antioquia,
Colombia
van de Vrugt, Maartje. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-39
n.m.vandevrugt@utwente.nl
Centre for Healthcare Operations Improvement and Research
(CHOIR), University of Twente, Enschede, Netherlands
Valencia Cárdenas, Marisol . . . . . . . . . . . . . . . . . . . . . . . . . ME-09
mvalencia@unal.edu.co
Ingenierías, Universidad Nacional de Colombia, Medellín,
Antioquia, Colombia
van den Akker, Marjan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-11
J.M.vandenAkker@uu.nl
Information and Computing Sciences, Utrecht University,
Utrecht, Netherlands
Valente, Christian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-21
christian@optirisk-systems.com
OptiRisk Systems, Uxbridge, Middlesex, United Kingdom
Van den Broeke, Maud . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-32
maud.vandenbroeke@vlerick.com
Operations and Supply Chain Management, Vlerick Business
School, Gent, Belgium
Valenzuela, Jorge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-09
valenjo@auburn.edu
Auburn University, United States
van den Heever, Susara . . . . . . . . . . . . . . . . . . . . . . FB-01, MA-43
svdheever@fr.ibm.com
IBM, France
Valet, Lionel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-31
lionel.valet@univ-savoie.fr
LISTIC, University of Savoie, France
Van der Hurk, Evelien . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-01
EHurk@rsm.nl
Department of Technology & Operations Management, Erasmus University, Rotterdam, Netherlands
Vallada, Eva . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-14
evallada@eio.upv.es
Estadística e Investigación Operativa Aplicadas y Calidad,
Universidad Politécnica de Valencia, Valencia, Spain
Valladão, Davi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-27
davimv@puc-rio.br
Industrial Engineering Department, PUC-Rio, Brazil
Vallés, María C. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-36
convalpl@agf.upv.es
Universitat Politècnica de València (UPV), Valencia, Spain
Van der Meer, Robert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-41
yupinr@hotmail.com
Department of Management Science, University of Starthclyde, Glasgow
van der Vecht, Bob . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-33
bob.vandervecht@tno.nl
Networked Organisations, TNO, The Hague, Netherlands
van der Vorst, Jack . . . . . . . . . . . . . . . . . . . . . . . . . . HB-08, HA-41
Jack.vanderVorst@wur.nl
Operations Research and Logistics, Wageningen University,
417
AUTHOR INDEX
IFORS 2014 - Barcelona
Wageningen, Netherlands
van Essen, Theresia . . . . . . . . . . . . . . . . . . . . . . . . . TD-06, ME-39
essen@cwi.nl
Centrum Wiskunde & Informatica, Netherlands
Van Hentenryck, Pascal . . . . . . . . . . . . . . . . . . . . . . FB-25, HE-33
pvh@nicta.com.au
NICTA and ANU, Canberra, ACT, Australia
van Hoeve, Willem-Jan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-29
vanhoeve@andrew.cmu.edu
Tepper School of Business, Carnegie Mellon University,
Pittsburgh, PA, United States
van Lint, Hans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-04
J.W.C.vanLint@tudelft.nl
Traffic and Transport, Delft University of Technology, Delft,
Netherlands
Van Mieghem, Jan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-22
vanmieghem@kellogg.northwestern.edu
Kellogg School of Management, Northwestern University,
Evanston, IL, United States
Van Nieuwenhuyse, Inneke . . . . . . . . . . . . . . . . . . . . . . . . . MD-09
inneke.vannieuwenhuyse@econ.kuleuven.be
Research Centre for Operations Management, K.U.Leuven,
Leuven, Belgium
Van Riessen, Bart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-05
vanriessen@ese.eur.nl
Econometric Institute, Erasmus University Rotterdam,
Netherlands
Van Vlasselaer, Véronique . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-25
Veronique.VanVlasselaer@kuleuven.be
Decision Sciences and Information Management, KU Leuven, Leuven, Belgium
van Vuuren, Jan . . . . . . . . . . . . . . . . . . . . . HA-07, HA-11, HE-17
vuuren@sun.ac.za
Department of Industrial Engineering, Stellenbosch University, Stellenbosch, Western Cape, South Africa
Van Vyve, Mathieu . . . . . . . . . . . . . . . . . . . . . . . . . MA-19, MB-41
mathieu.vanvyve@uclouvain.be
CORE, UCL, Louvain-la-neuve, – Select –, Belgium
van Wageningen-Kessels, Femke . . . . . . . . . . . . . . . . . . . . . TD-04
f.l.m.vanwageningen-kessels@tudelft.nl
Transport & Planning, Delft University of Technology,
Netherlands
Van Wassenhove, Luk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-08
luk.van-wassenhove@insead.edu
Technology and Operations Management Area, INSEAD,
Fontainebleau cedex, France
van Westen, Cees . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-27, FA-40
c.j.vanwesten@utwente.nl
ITC, Enschede, Netherlands
Van Woensel, Tom . . . MD-02, TB-22, MB-33, MA-42, MD-42
t.v.woensel@tm.tue.nl
Technische Universiteit Eindhoven, Eindhoven, Netherlands
van Zuylen, Henk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-25
h.j.vanzuylen@tudelft.nl
Delft University of Technology, Delft, Zuid Holland, Netherlands
418
Vandaele, Arnaud . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-21
arnaud.vandaele@gmail.com
Mathematics and Operations Research, University of Mons,
Mons, Belgium
Vandaele, Nico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-06
nico.vandaele@kuleuven.be
Operations Management Dept., Katholieke Universiteit Leuven, Leuven, Belgium
Vanden Berghe, Greet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-05
greet.vandenberghe@cs.kuleuven.be
Computer Science, KU Leuven, Gent, Belgium
Vandenheede, Len . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-12
len.vandenheede@ugent.be
EB08, Ghent University, Gent, Belgium
Vandyshev, Konstantin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-09
k.vandyshev@tudelft.nl
Delft Institute of Applied Mathematics, Delft University of
Technology, Netherlands
Vanhoucke, Mario . . . . . . . . . . . . . . . . . . . . . . . . . . HD-12, MB-39
mario.vanhoucke@ugent.be
Faculty of Economics and Business Administration, Ghent
University, Vlerick Business School, University College London, Ghent, Belgium
Vansteenwegen, Pieter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-01
Pieter.Vansteenwegen@cib.kuleuven.be
Centre of Industrial Management, Traffic and Infrastructure,
KU Leuven, Leuven, Belgium
Vanthienen, Jan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-25
jan.vanthienen@econ.kuleuven.be
Decision Sciences and Information Management, Katholieke
Universiteit Leuven, Leuven, Belgium
Varas, Mauricio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-40
mauriciano@gmail.com
Pontificia Universidad Católica de Chile, Santiago, Chile
Vardanyan, Yelena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-07
yelenav@kth.se
Electric Power Systems, KTH, Royal Institute of Technology,
Stockholm, Sweden
Vargas, Francisco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-14
fvargas@guaymas.uson.mx
Economia, Universidad de Sonora, Hermosillo, Sonora, Mexico
Vargas, Ignacio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-40
ignacio.vargaso@udp.cl
Industrial Engineering, Universidad Diego Portales, Santiago, Region Metropolitana, Chile
Vargas, José . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-42
donjmvargas@gmail.com
Matemática y Estadística, Facultad de Ciencias Económicas
UNC, Córdoba, Córdoba, Argentina
Vargas, Luis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-06, ME-32
lgvargas@pitt.edu
Katz Graduate School of Business, University of Pittsburgh,
Pittsburgh, PA, United States
Vargas-Parra, M. Violeta . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-14
mariavioleta.vargas@uab.cat
Institute of Environmental Science and Technology (ICTA),
Universitat Autonoma de Barcelona, Barcelona, Barcelona,
IFORS 2014 - Barcelona
Spain
Varnas, Nerijus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-45
nerijus.varnas@ktu.lt
Kaunas University of Technology, Kaunas, Lithuania
Varoneckas, Audrius . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-18
audrius.varoneckas@mii.vu.lt
Institute of Mathematics and Informatics, Vilnius University,
Vilnius, Lithuania
Varzgani, Nilofar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-19
nilofarv@pegasus.rutgers.edu
Rutgers Business School, Department of Management Science and Information Systems, Rutgers University, Newark,
NJ, United States
Vasilieva, Diana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-16
bitsharp@gmail.com
Nyurbinsky Technical Lyceum, Russian Federation
Vasin, Alexander . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-08
vasin@cs.msu.su
Operations Research, Lomonosov Moscow State University,
Moscow, Russian Federation
Vasquez, Michel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-28, TE-40
michel.vasquez@mines-ales.fr
LGI2P, Ecole des Mines d’Ales, Nîmes, Gard, France
Vasselle, Bathilde . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-01
bvasselle@hotmail.fr
Innovation & Research, SNCF, France
Vassilakopoulos, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-40
mvasilako@ucg.gr
Department of Computer Science & Biomedical Informatics,
University of Central Greece, Lamia, Greece
Vatsa, Amit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-03
amit.vatsa@gmail.com
Production and Quantitative methods, IIM Ahmedabad,
Ahmedabad, Gujarat, India
Váncza, József . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-13
vancza@sztaki.mta.hu
Fraunhofer Project Center for Production Management and
Informatics Computer and Automation Research Institute,
(SZTAKI), Hungarian Academy of Sciences (MTA), Budapest, Hungary
Vaz, Clara . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-14
clvaz@ipb.pt
School of Technology and Management, Polytechnic Institute of Bragança, Bragança, Portugal
Vaze, Vikrant . . . . . . . . . . . . . . . . MB-03, MD-03, ME-03, TE-35
vikrant.s.vaze@dartmouth.edu
Department of Engineering Sciences, Thayer School of Engineering, Dartmouth, Hanover, NH, United States
Vazquez-Abad, Felisa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-45
fvazquez-abad@gc.cuny.edu
Computer Science, Hunter College, New York, United States
Veelenturf, Lucas . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-01, ME-01
LVeelenturf@rsm.nl
Department of Technology & Operations Management, Rotterdam School of Management, Erasmus University, Rotterdam, Netherlands
Veiga, Alvaro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-27
AUTHOR INDEX
alvf@ele.puc-rio.br
Electrical Engineering, Pontifical Catholic University of Rio
de Janeiro, Rio de Janeiro, Rio de Janeiro, Brazil
Veiga, Geraldo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-27
gveiga@gmail.com
Rn Ciência e Tecnologia, Rio de Janeiro, Brazil
Veiga, Germano . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-36, MB-36
germano.veiga@inescporto.pt
Robotics and Intelligent Systems, INESC Porto, Porto, Portugal
Velásquez Henao, Juan David . . . . . . . . . . . . . . . . . . . . . . . HE-23
jdvelasq@unal.edu.co
Universidad Nacional de Colombia, Medellín, Colombia
Velez-Gallego, Mario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-40
marvelez@eafit.edu.co
Departamento de Ingeniería de Producción, Universidad
EAFIT, Medellin, Colombia
Veliov, Vladimir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-25
veliov@tuwien.ac.at
Institute of Mathematical Methods in Economics, Vienna
University of Technology, Vienna, Austria
Venceslau, Helder . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-11, MA-17
helder.venceslau@gmail.com
Federal University Rio de Janeiro - UFRJ, Brazil
Venceslau, Marilis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-17
marilisbkv@cos.ufrj.br
Federal University Rio de Janeiro - UFRJ and Colégio Pedro
II, Rio de Janeiro, Rio de Janeiro, Brazil
Venel, Xavier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-24
xavier.venel@gmail.com
Department of Statistics and Operations Research, Tel aviv
University, Tel aviv, Israel
Ventre, Carmine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-22
carmine.ventre@gmail.com
Teesside University, United Kingdom
Ventresca, Mario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-25
mventresca@gmail.com
Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada
Ventresque, Anthony . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-29
anthony.ventresque@ucd.ie
Computer Science and Informatics, Lero@University College Dublin, Ireland
Vera, Jorge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-40
jvera@ing.puc.cl
Pontificia Universidad Católica de Chile, santiago, Chile
Vera-Montenegro, Lenin . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-36
lveram@espam.edu.ec
Escuela Superior Politécnica Agropecuaria de Manabí,
"Manuel Félix López", Calceta, Manabi, Ecuador
Verago, Rudi. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-35, MA-43
rudi.verago@ie.ibm.com
IBM, Dublin, Ireland
Verleye, Derek . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-43
derek.verleye@ugent.be
Industrial Management, Ghent University, Zwijnaarde, Belgium
419
AUTHOR INDEX
IFORS 2014 - Barcelona
Verlinde, Sara . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-37
sara.verlinde@ugent.be
Universiteit Gent, Gent, Belgium
Verma, Manish . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-32
mverma@mcmaster.ca
DeGroote School of Business, McMaster University, Hamilton, Ontario, Canada
VerSchure, Zachary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-06
zakv@umich.edu
University of Michigan, Ann Arbor, United States
Verstichel, Jannes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-05
jannes.verstichel@cs.kuleuven.be
Computer Science, KU Leuven campus Gent, Gent, Belgium
Verstraeten, Geert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-40
geert.verstraeten@pythonpredictions.com
Python Predictions, Brussels, Belgium
Verter, Vedat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-03
Vedat.Verter@mcgill.ca
Faculty of Management, McGill University, Montreal, Quebec, Canada
Vertinsky, Ilan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-42
ilan.vertinsky@ubc.ca
Sauder School of Business, University of British Columbia,
Vancouver, B.C., Canada
Verwer, Sicco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-41
S.E.Verwer@tudelft.nl
Delft University of Technology, Delft, Netherlands
Veselova, Yuliya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-29
yul-r@mail.ru
Department of Higher Mathematics, National Research University Higher School of Economics, Russian Federation
Vidal, Carlos J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-40
carlos.vidal@correounivalle.edu.co
School of Industrial Engineering, Universidad del Valle, Cali,
Valle, Colombia
Vidal-Puga, Juan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-44
vidalpuga@uvigo.es
Estadística e IO, Universidade de Vigo, Pontevedra, Pontevedra, Spain
Vidali, Angelina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-22
vidali@cs.duke.edu
Computer Science, Duke University, Duke, United States
Vidovic, Milorad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-41
m.vidovic@sf.bg.ac.rs
Logistics, University of Belgrade, Faculty of transport and
traffic engineering, Serbia
Vidyarthi, Navneet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-22
navneet.vidyarthi@gmail.com
Supply Chain and Business Technology Management, Concordia University, Montreal, Quebec, Canada
Vidyarthi, Navneet . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-03, HE-31
navneetv@jmsb.concordia.ca
Concordia University, Montreal, Canada
Vieille, Nicolas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-24
vieille@hec.fr
ESD, HEC Paris, Jouy en Josas, France
Vieira, Douglas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-14
douglas.vieira@enacom.com.br
ENACOM, Brazil
Vierhaus, Ingmar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-43
vierhaus@zib.de
Optimization, Zuse Institute Berlin, Berlin, Germany
Vespucci, Maria Teresa . . . . . . . . . . . . . . . HB-09, HD-09, HE-09
maria-teresa.vespucci@unibg.it
Dept. of Management, Economics and Quantitative Methods,
University of Bergamo, Bergamo, Italy
Vigo, Daniele . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-02, TB-37
daniele.vigo@unibo.it
DEI "Guglielmo Marconi", University of Bologna, Bologna,
Italy
Vetschera, Rudolf . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-24
rudolf.vetschera@univie.ac.at
Dept. of Business Administration, University of Vienna, Vienna, Austria
Vila Bonilla, Mariona . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-13
mariona.vila.bonilla@upc.edu
Departament d’Organització d’Empreses, Escola Universitària d’Enginyeria Tècnica Industrial de Barcelona, Consorci Escola Industrial de Barcelona, Universitat Politècnica
de Catalunya, Spain
Vianna, Andréa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-21
vianna@fc.unesp.br
Computation, UNESP - Bauru, Bauru, São Paulo, Brazil
Vicente, Eloy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-31
e.vicentecestero@upm.es
Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Boadilla del Monte, Madrid, Spain
Vicente, Luis Nunes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-14
lnv@mat.uc.pt
University of Coimbra, Coimbra, Portugal
Vicente, Manuel António . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-37
vicente@mat.uc.pt
University of Coimbra, Coimbra, Portugal
Vicente-Molina, Azucena . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-08
azucena.vicente@ehu.es
Economía de la Empresa y Comercialización, Universidad
del País Vasco, Bilbao, Spain
420
Villalobos, Rene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-37, TE-43
rene.villalobos@asu.edu
School of Computing, Informatics and Decision Systems
Engineering, Arizona State University, Tempe, AZ, United
States
Villanova, Laura . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-18
laura.villanova@cfcl.com.au
Ceramic Fuel Cells Limited, Noble Park, VIC, Australia
Villanueva, Arlyn . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-04, TB-40
brian.gozun@dlsu.edu.ph
Accountancy, Holy Angel University, Angeles City, Philippines
Villas-Boas, Sergio B. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-11
sbvb@sbvb.com.br
PESC, Ufrj / Coppe, Rio de Janeiro, Rio de Janeiro, Brazil
IFORS 2014 - Barcelona
Villegas, Juan G. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-27
jvillega@udea.edu.co
Industrial Engineering, Universidad de Antioquia, Medellin,
Antioquia, Colombia
Villumsen, Jonas Christoffer . . . . . . . . . . . . . . . . . . . . . . . . . FA-35
jonasvil@ie.ibm.com
IBM Research, Dublin, Ireland
Vilutiene, Tatjana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-45
tatjana.vilutiene@vgtu.lt
Department of Construction Technology and Management,
Vilnius Gediminas Technical University, Vilnius, Lithuania
Vinals, Guillem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-09
guillemvinyals91@live.com
CITCEAUPC, Barcelona, Spain
Violin, Alessia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-15
aviolin@ulb.ac.be
Computer Science, Université Libre de Bruxelles, Bruxelles,
Belgium
Vis, Iris F.A. . . . . . . . . . . . . . . . . . . . . . . . . . . TB-02, FA-05, HB-05
i.f.a.vis@rug.nl
Faculty of Economics and Business, Dep. of Operations,
University of Groningen, Groningen, Netherlands
Visagie, Stephan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-11
svisagie@sun.ac.za
Department of Logistics, University of Stellenbosch, Stellenbosch, South Africa
Vitoriano, Begoña. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-37
bvitoriano@mat.ucm.es
Estadística e Investigación Operativa I, Fac. Matemáticas,
Universidad Complutense de Madrid, Madrid, Spain
Vizcaino, José Federico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-09
jfvg@densis.fee.unicamp.br
DENSIS, UNICAMP, Campinas, Sao Paulo, Brazil
Vlach, Milan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-26
mvlach@ksi.ms.mff.cuni.cz
Theoretical Computer Science and Mathematical Logic,
Charles University, Prague, Czech Republic
Vlachos, Dimitrios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-35
vlachos1@auth.gr
Mechanical Engineering, Aristotle University of Thessaloniki, Thessaloniki, Greece
AUTHOR INDEX
vojtas@ksi.mff.cuni.cz
Software Engineering, Charles University, Prague, Czech Republic
Volcic, Mark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-01
mvolcic@auto.tuwien.ac.at
TU Vienna, Austria
Volling, Thomas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-27
t.volling@tu-braunschweig.de
Institute of Automotive Management and Industrial Production, Technische Universität Braunschweig, Braunschweig,
Germany
Voloshinov, Vladimir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-21
vladimir.voloshinov@gmail.com
Centre of distributed computing, Institute for Information
Transmission Problems (Kharkevich Institute), Moscow, -,
Russian Federation
von Winterfeldt, Detlof . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-23
detlof@aol.com
University of Southern California, Los Angeles, CA, United
States
Vortisch, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-04
peter.vortisch@kit.edu
Institute for Transport Studies, Karlsruhe Institute of Technlogy, Karlsruhe, BW, Germany
Voss, Stefan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-05, HE-40
stefan.voss@uni-hamburg.de
Wirtschaftsinformatik/Information Systems, University of
Hamburg, Hamburg, Germany
Voyvoda, Ebru . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-18
voyvoda@metu.edu.tr
Department of Economics, Middle East Technical University,
Ankara, Turkey
Vujosevic, Mirko . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-04
mirkov@fon.bg.ac.rs
Faculty of Organizational Sciences, University of Belgrade,
Belgrade, Serbia
Vulevic, Tijana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-36
tijana.andrijanic@sfb.bg.ac.rs
Ecological engineering for soil and water resources protection, University of Belgrade, Faculty of Forestry, Belgrade,
Serbia, Belgrade, Serbia
Vo, Xuan Thanh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-17
xuan-thanh.vo@univ-lorraine.fr
University of Lorraine, France
Wachowicz, Tomasz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-23
tomasz.wachowicz@ae.katowice.pl
Operations Research, Karol Adamiecki University of Economics in Katowice, Katowice, Poland
Vocaturo, Francesca . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-45
vocaturo@unical.it
Department of Economics, Statistics and Finance, University
of Calabria, Arcavacata di Rende (CS), Italy
Wagenaar, Joris . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-01, ME-01
jwagenaar@rsm.nl
Rotterdam School of Management, Erasmus University Rotterdam, Rotterdam, Netherlands
Vock, Sebastian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-03
sebastian.vock@fu-berlin.de
Information Systems, Freie Universität Berlin, Rimbach,
Germany
Wahid, Faisal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-20
f.wahid@auckland.ac.nz
Engineering Science, University of Auckland, Auckland,
New Zealand
Voigt, Guido . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-23
guido.voigt@ovgu.de
Operations Management, Otto-von-Guericke University
Magdeburg, Magdeburg, Germany
Wahlberg, Olof . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-36
Olof.Wahlberg@miun.se
Department of Social Sciences, Mid Sweden University,
Sundsvall, Sweden
Vojtas, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-24
Waitz, Martin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-27
421
AUTHOR INDEX
IFORS 2014 - Barcelona
mwaitz@wu.ac.at
WU Vienna, Austria
Waizinger, Gottfried . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-33
g.waizinger@waizinger.at
Waizinger Ges.mbH & Co KG, Dietach, Austria
Wakolbinger, Tina . . . . . . . . . . . . . . . . . . . . . . . . . . MD-31, MD-33
tina.wakolbinger@wu.ac.at
WU (Vienna University of Economics and Business), Vienna,
Austria
Walczak, Darius . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-15
dwalczak@pros.com
PROS, Houston, United States
Waligora, Grzegorz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-12
grzegorz.waligora@cs.put.poznan.pl
Institute of Computing Science, Poznan University of Technology, Poznan, Wielkopolska, Poland
Wall, Friederike . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-27, MA-44
friederike.wall@uni-klu.ac.at
Dept. for Controlling and Strategic Management, AlpenAdria-Universitaet Klagenfurt, Klagenfurt, Austria
Walle-Hansen, Thomas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-07
thomas@walle-hansen.no
NTNU, Trondheim, Norway
Wallenius, Jyrki . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-18
jyrki.wallenius@aalto.fi
Information and Service Economy, Aalto University School
of Business, Helsinki, Uusimaa, Finland
Walther, Ursula . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-30
ursula.walther@hwr-berlin.de
Fb 1, Berlin School of Economics and Law, Berlin, Germany
Wan, Cheng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-28
cheng.wan@economics.ox.ac.uk
Economics, University of Oxford, Oxford, United Kingdom
Wan, Xiangwei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-29
xwwan@sjtu.edu.cn
Antai College of Economics and Management, Shanghai Jiao
Tong University, Shanghai, China
Wang, Cara . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-06
wangx18@rpi.edu
Civil and Environmental Engineering, Rensselaer Polytechnic Institute, Troy, New York, United States
Wang, Changjun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-11
wcj@amss.ac.cn
Chinese Academy of Sciences, Beijing, China
Wang, Chengjing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-38
renascencewang@hotmail.com
School of Mathematics, Southwest Jiaotong University,
Chengdu, Sichuan, China
Wang, Chenlan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-04
phd10cw@mail.wbs.ac.uk
Warwick Business School & DIMAP, The University of Warwick, United Kingdom
Wang, Chi-Ying . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-23
z2472426@yahoo.com.tw
Department of Industrial Engineering & Management, National Chin-Yi University of Technology, Taichung, Taiwan
422
Wang, Chia-Hung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-26
93751502@nccu.edu.tw
Department of Mathematical Sciences, National Chengchi
University, Taipei, Taiwan
Wang, Dongpeng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-27
deppwang@gmail.com
School of Management, Hefei University of Technology,
Hefei, Anhui, China
Wang, Gongshu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-20
wanggongshu@ise.neu.edu.cn
The Logistics institute, Northeastern University, Shenyang,
China
Wang, Guoqing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-19
tgqwang@jnu.edu.cn
Department of Business Administration, Jinan University,
Guangzhou, China
Wang, Haibo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-40
hwang@tamiu.edu
Texas A&M International University, United States
Wang, Huei Chun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-27
whc@tust.edu.tw
Ta Hwa University of Science and Technology, Taiwan
Wang, Jianhui . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-09
jianhui.wang@anl.gov
Argonne National Laboratory, Argonne, IL, United States
Wang, Judith Y. T. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-04
J.Y.T.Wang@leeds.ac.uk
School of Civil Engineering & Institute for Transport Studies,
University of Leeds, Leeds, United Kingdom
Wang, Jue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-15
12jw89@queensu.ca
Queens University, Kingston, Canada
Wang, Pengyuan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-15
pengyuan@yahoo-inc.com
Yahoo Labs, Sunnyvale, United States
Wang, Shin-Yun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-34
gracew@mail.ndhu.edu.tw
Department of Finance, National Dong Hwa University, Taiwan
Wang, Shuangyu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-20
sw2756@columbia.edu
Columbia University, New York, NY, United States
Wang, Xiaojun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-24
xiaojun.wang@bristol.ac.uk
School of Economics, Finance and Management, University
of Bristol, Bristol, United Kingdom
Wang, Xiaoqing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-25
xiaoqinw@usc.edu
Daniel J. Epstein Department of Industrial and Systems Engineering, University of Southern California, Los Angeles,
California, United States
Wang, Yanfei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-38
yfwang@mail.iggcas.ac.cn
Institute of Geology and Geophysics, Chinese Academy of
Sciences, Beijing, China
Wang, Yang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-11
sparkle.wy@gmail.com
IFORS 2014 - Barcelona
Department of Mathematics, Simon Fraser University,
Canada
Wang, Yu-Lin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-44
ywang@mail.ncku.edu.tw
National Cheng Kung University, Taiwan
Wang, Yucan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-38
wscancan@hotmail.com
Operation Information Management, Aston University, Birmingham, United Kingdom
Wang, Yulan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-22
yulan.wang@polyu.edu.hk
Dept. of Logistics and Maritime Studies, The Hong Kong
Polytechnic Univ., Hong Kong, Hong Kong
Wang, Zhouhong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-17
wangzhhng@163.com
Beijing Jiaotong University, China
Wang, Zizhuo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-15
zwang@umn.edu
Industrial and Systems Engineering, University of Minnesota,
Minneapolis, MINNESOTA, United States
Wangkeeree, Rabian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-37
rabianw@nu.ac.th
Mathematics, Naresuan University, Phitsanulok, Thailand
Wanke, Egon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-39
E.Wanke@hhu.de
Computer Sciences, Heinrich-Heine Universität, Düsseldorf,
Germany
Wanke, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-02
peter@coppead.ufrj.br
COPPEAD Graduate Busines School, Rio de Janeiro, Brazil
Warmer, Cornelia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-04
CorneliaMargarete.Warmer@de.bosch.com
Robert Bosch (CP/LOG-T), University of Hohenheim,
Stuttgart, 70435, Germany
Warrington, Joseph . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-20
warrington@control.ee.ethz.ch
Automatic Control Laboratory, ETH Zurich, Switzerland
Warwick, Jon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-44
warwick@lsbu.ac.uk
Faculty of Business, London South Bank University, London,
United Kingdom
Wasik, Szymon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-28
szymon.wasik@cs.put.poznan.pl
Institute of Computing Science, Poznan University of Technology, Poznan, Poland
Wassan, Naveed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-45
naw30@kent.ac.uk
Kent Business School, University of Kent, Canterbury, Kent,
United Kingdom
Wassan, Niaz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-45
N.A.Wassan@kent.ac.uk
Kent Business School, University of Kent, United Kingdom
Watanabe, Takahiro. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-35
contact_nabe08@nabenavi.net
Graduate School of Social Sciences, Tokyo Metropolitan
University, Tokyo, Japan
AUTHOR INDEX
Weber, Christoph . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-07, FA-20
christoph.weber@uni-duisburg-essen.de
University Duisburg-Essen, Essen, Germany
Weber, Christoph . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-07
Christoph_Weber@uni-duisburg-essen.de
Universität Essen, Essen, Germany
Weber, Gerhard-Wilhelm . . . . . . . . . . . . . TE-09, HA-30, TB-44
gweber@metu.edu.tr
Institute of Applied Mathematics, Middle East Technical
University, Ankara, Turkey
Weber, Richard . . . . . . . . . . . . . . . . . . . . . . HD-08, HB-25, TD-25
rweber@dii.uchile.cl
Department of Industrial Engineering, University of Chile,
Santiago, Chile
Weber, Thomas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-07
thomas.weber@epfl.ch
EPFL, Switzerland
Weber, Valentin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-03
valentin.weber@amadeus.com
Operations Research, Amadeus sas, Sophia Antipolis Cedex,
France, France
Webster, Scott . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-24
scott.webster@asu.edu
Arizona State University, United States
Webster, Scott . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-19
stwebste@syr.edu
Syracuse University, Syracuse, NY, United States
Wedley, William . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-29
wedley@sfu.ca
Faculty of Business Administration, Simon Fraser University,
Burnaby, BC, Canada
Wegryn, Glenn . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-23
Gwegryn@gmail.com
Analytic Impact LLC, Cincinnati, OH, United States
Wei, Ying . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-19
yingwei@jnu.edu.cn
Department of Business Administration, Jinan University,
Guangzhou, China
Weidmann, Ulrich . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-01
weidmann@ivt.baug.ethz.ch
Institute for Transport Planning and Systems, ETH Zurich,
Zürich, Zurich, Switzerland
Weilemann, Kristina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-45
kweilemann@uniss.it
University Language Centre, Università degli Studi di Sassari, Sassari, Italy
Weilemann, Mitja Stefan . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-45
mitja.weilemann@hs-neu-ulm.de
Information Management, Hochschule Neu-Ulm, Neu-Ulm,
Bayern, Germany
Weintraub, Andrés . . . . . . . . . . . . . . . . . . . HB-11, ME-36, TA-36
aweintra@dii.uchile.cl
Industrial engineering, University of Chile, Santiago, Chile
Welling, Andreas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-08
andreas.welling@ovgu.de
Faculty of Economics and Management, LS Financial Management and Innovation Finance, Otto-von-Guericke Univer-
423
AUTHOR INDEX
IFORS 2014 - Barcelona
sity Magdeburg, Magdeburg, Germany
Wen, Min . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-05, MB-42
mw@transport.dtu.dk
DTU Transport, Technical University of Denmark, lyngby,
Copenhagen, Denmark
Weninger, Dieter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-39
dieter.weninger@math.uni-erlangen.de
Mathematics, University Erlangen-Nürnberg, Erlangen, Germany
Wensing, Thomas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-19
wensingt@web.de
INFORM GmbH, Aachen, NRW, Germany
Wenstøp, Fred . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-24
fred.wenstop@bi.no
Strategy and Logistics, BI Norwegian Business School, Oslo,
Norway
Wenstøp, Søren . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-24
soren.wenstop@gmail.com
Oslo Business School, Oslo, Oslo, Norway
Werners, Brigitte . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-01, ME-39
or@rub.de
Fac. of Management and Economics, Ruhr University
Bochum, Bochum, Germany
Westphal, Stephan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-39
s.westphal@math.uni-goettingen.de
Institute for Numerical and Applied Mathematics, University
of Goettingen, Göttingen, Germany
Wevers, Jeroen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-33
jeroen.wevers@tno.nl
Military Operations, TNO, The Hague, Netherlands
Whinston, Andrew . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-15
abw@uts.cc.utexas.edu
University of Texas at Austin, Austin, United States
White, Leroy . . . . . . . . . . . . . . . . . TA-23, MD-24, HB-38, HD-38
leroy.white@bris.ac.uk
Management Department, University of Bristol, Bristol,
United Kingdom
White, Preston . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-39
kpwhite@virginia.edu
Systems and Information Engineering, University of Virginia,
Charlottesville, VA, United States
Wichmann, Matthias Gerhard . . . . . . . . . . . . . . . . . . . . . . . FB-13
ma.wichmann@tu-braunschweig.de
Institute of Automotive Management and Industrial Production, Technische Universität Braunschweig, Braunschweig,
Germany
Wiegele, Angelika . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-17
angelika.wiegele@aau.at
Mathematik, Alpen-Adria-Universitaet Klagenfurt, Klagenfurt, Austria
Wierman, Adam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-20
adamw@caltech.edu
California Institute of Technology, Pasadena, United States
Wiesche, Lara . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-39
lara.wiesche@rub.de
Faculty of Management and Economics, Ruhr University
Bochum, Bochum, Germany
424
Wijnmalen, Diederik J.D. . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-29
diederik.wijnmalen@tno.nl
Dept. for Behavioural and Societal Sciences, TNO Organisation for Applied Scientific Research, The Hague, Netherlands
Wikström, Patrik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-06
patrik.wikstrom@qut.edu.au
Centre for Creative Industries and Innovation, Queensland
University of Technology, Kelvin Grove, QLD, Australia
Wilhelm, Volmir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-25
volmirw@gmail.com
PPGMNE, UFPR, Curitiba, Paraná, Brazil
Williams, Janet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-09
WilliamsJE@cf.ac.uk
Cardiff School of Mathematics, Cardiff University, Wales,
United Kingdom
Williams, Julian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-31
julian.williams@durham.ac.uk
Accounting and Finance, Durham University, Durham,
United Kingdom
Wilppu, Outi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-26
outi.wilppu@utu.fi
University of Turku, Finland
Wilson, John . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-15
jwilson@ivey.uwo.ca
Ivey School of Business, Western University, London, Ontario, Canada
Wilson, Nigel H.M. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-01
nhmw@mit.edu
Massachusetts Institute of Technology, Boston, United States
Wimmer, Maximilian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-08
maximilian.wimmer@ur.de
Department of Finance, University of Regensburg, Regensburg, Germany
Winer, Zvi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-25
ZvikaV@wgalil.ac.il
Economics, Western Galilee College, Yokneam, Israel
Winter, Thomas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-15
thomas.winter@beuth-hochschule.de
Department of Mathematics, Physics, and Chemistry, Beuth
Hochschule für Technik Berlin, Berlin, Germany
Witt, Jonas Timon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-39
jonas.witt@rwth-aachen.de
Operations Research, RWTH Aachen University, Germany
Witteveen, Cees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-01
C.Witteveen@tudelft.nl
Software Technology, Delft University of Technology, Delft,
Netherlands
Wogrin, Sonja . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-10
Sonja.Wogrin@iit.upcomillas.es
Univ. Pontificia Comillas, Madrid, Spain
Wojciechowski, Piotr . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-43
piotrw@utep.edu
Mathematical Sciences, The University of Texas at El Paso,
El Paso, TX, United States
Wolfler-Calvo, Roberto . . . . . . . . . . . . . . . . . . . . . . HB-11, TA-28
roberto.wolfler@lipn.univ-paris13.fr
IFORS 2014 - Barcelona
LIPN, Université Paris Nord, Villetaneuse, France
Wollenberg, Nadine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-41
nadine.wollenberg@uni-due.de
Mathematic, Universitiy of Duisburg-Essen, Germany
Wong, Eugene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-35
eugenewong@hsmc.edu.hk
Supply Chain Management, School of Business, Hang Seng
Management College, Hong Kong
AUTHOR INDEX
Federal University of Rio de Janeiro, Rio de Janeiro, RJ,
Brazil
Xia, Yusen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-15
ysxia@gsu.edu
Georgia State University, Atlanta, GA, United States
Xianping, Wu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-34
xianping.wu@connect.polyu.hk
The Hong Kong Polytechnic University, Hong Kong
Wood, Kevin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-09
kwood@nps.edu
Operations Research Dept., Naval Postgraduate School,
Monterey, CA, United States
Xiao, Di . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-29
dx2125@columbia.edu
IEOR, Columbia University, New York, New York, United
States
Wozabal, David . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-20
david.wozabal@tum.de
TUM School of Management, Technische Universität
München, Munich, Germany
Xiaoxue, Zhang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-32
snowing1124@126.com
National University of Defense Technology, Information System Engineering Lab, Changsha, Hunan, China
Wright, Mike . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-10
m.wright@lancaster.ac.uk
The Management School, Lancaster University, Lancaster,
Lancashire, United Kingdom
Xie, Yangyang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-15
xie-089@163.com
Automation/Management Sci., Tsinghua Univ./CityU of HK,
China
Wu, Cheng-Lung . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-03, TB-03
c.l.wu@unsw.edu.au
Aviation, UNSW Australia, Sydney, NSW, Australia
Xiong, Yu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-44
y.xiong@uea.ac.uk
Norwich Business School, University of East Anglia, Norwich, United Kingdom
Wu, Chien-Wei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-27
cweiwu@ie.nthu.edu.tw
Department of Industrial Engineering and Engineering Management, National Tsing Hua University, HsinChu, Taiwan
Wu, Jing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-24
jwu7@chicagobooth.edu
Booth School of Business, University of Chicago, Chicago,
IL, United States
Wu, Qi. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-29
qwu@se.cuhk.edu.hk
The Chinese University of Hong Kong, Hong Kong, Hong
Kong
Wu, Shining . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-15
shiningwu@ust.hk
Department of Industrial Engineering and Logistics Management, The Hong Kong University of Science and Technology,
Hong Kong, Hong Kong
Wu, Wei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-39
wwu3@utk.edu
Statistics, Operations and Management Science, The University of Tennessee, Knoxville, TN, United States
Wu, Yue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-39
Y.Wu@soton.ac.uk
School of Management, University of Southampton,
Southampton, United Kingdom
Wu, Yue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-15
yue.wu@insead.edu
INSEAD, Singapore, Singapore
Wu, Yuwen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-12
wuyuwen@amss.ac.cn
Department of Math, Beijing Wuzi University, Beijing, China
Xavier, Adilson Elias . . . . . . . . . . . . . . . . . . FB-11, HE-11, TA-17
adilson@cos.ufrj.br
Systems Engineering and Computer Sciences Department,
Xiu, Baoxin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-18, ME-44
bxxiunudt@163.com
Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology,
Changsha, China
Xiu, Naihua . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-38
nhxiu@bjtu.edu.cn
Department of Applied Mathematics, Operations Research
Society of China, Beijing, China
Xu, Di . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-27, TE-43
dxu@xmu.edu.cn
Management Science, Xiamen University, Xiamen, China
Xu, Dong-Ling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-27
ling.xu@mbs.ac.uk
Manchester Business School, Manchester, United Kingdom
Xu, Haoxuan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-19
juwan.hsu@gmail.com
School of Management, Huazhong University of Science and
Technology, Wuhan, China
Xu, Jianjun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-37
jxu@zlc.edu.es
Zaragoza Logistics Center(ESG50985993), Zaragoza,
Zaragoza, Spain
Xu, Jiuping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-20
xujiuping@scu.edu.cn
State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu, China
Xu, Peide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-04
xupeide2014@163.com
Science and Technology on Information System Engineering Laboratory, National University of Defense Technology,
Changsha, Hunan, China
Xu, Yan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-25
425
AUTHOR INDEX
IFORS 2014 - Barcelona
yan.xu@sas.com
SAS Institute, Inc., Cary, NC, United States
Xu, Yi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-06
yxu@rshmith.umd.edu
University of Maryland, College Park, MD, United States
Xu, Zuo Quan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-29
maxu@polyu.edu.hk
Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong
Xufre, Patricia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-34
pxufre@novasbe.pt
CIO-FCUL and NovaSBE, Lisboa, Portugal
Yadav, Prashant . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-24
yadavp@umich.edu
William Davidson Institute, University of Michigan, Ann Arbor, Michigan, United States
Yagiura, Mutsunori . . . . . . . . . . . . . . . . . . . . . . . . . . FA-21, TE-40
yagiura@nagoya-u.jp
Graduate School of Information Science, Nagoya University,
Nagoya, Aichi, Japan
Yahi, Zahra . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-39
zahrayahi@yahoo.fr
SEGC-LMD, Béjaia University, Algeria
Yaici, Malika . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-35
yaici_m@hotmail.com
Dept. of Computer Science, University of Bejaia, Bejaia,
Algeria
Yağci, Ceren . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-43
cerenavci@selcuk.edu.tr
Selcuk Unİversİty, Konya, Selcuklu, Turkey
Yakıt Ongun, Mevlüde . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-12
mevludeyakit@sdu.edu.tr
Mathematics, Süleyman Demirel University, Isparta, Turkey
Yalaoui, Alice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-40
alice.yalaoui@utt.fr
ROSAS, UTT, Troyes, France
Yalcindag, Semih . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-11
semih.yalcindaag@polimi.it
Politecnico di Milano/ Ecole Centrale Paris, Italy
Yalçınkaya, İbrahim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-12
iyalcinkaya42@gmail.com
Mathematics, Necmettin Erbakan University, Konya, Turkey
Yamada, Syuuji . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-37, ME-37
yamada@math.sc.niigata-u.ac.jp
Graduate School of Science and Technology, Niigata University, Niigata, Japan
Yamada, Takako . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-30
takakoyamada@kwansei.ac.jp
School of Policy Studies, Kwansei Gakuin University, Sandashi, Hyougo, Japan
Yamak, Didem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-42
DYamak@devry.edu
College of Engineering and Information Sciences, DeVry
University, Phoenix, AZ, United States
Yaman, Hande . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-11
hyaman@bilkent.edu.tr
426
Bilkent University, Ankara, Turkey
Yamanaka, Keiji . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-10
keiji@ufu.br
Engenharia Elétrica, Universidade Federal de Uberlândia,
Uberlândia, Minas Gerais, Brazil
Yamashita, Masafumi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-09
mak@inf.kyushu-u.ac.jp
Kyushu University, Japan
Yamauchi, Yukiko . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-09
yamauchi@inf.kyushu-u.ac.jp
Kyushu University, Japan
Yan, Chiwei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-03
yan.cw08@gmail.com
Massachusetts Institute of Technology, Cambridge, MA,
United States
Yan, Guiying. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-12
yangy@amt.ac.cn
Academy od Math & Systems Sciences, CAS, Beijing, China
Yan, Houmin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-15
cbhyan@cityu.edu.hk
City University of HongKong, HongKong, China
Yanagi, Shigeru . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-27, MD-35
shigeru@nda.ac.jp
Dept. of Electrical and Electronics, National Defense
Academy, Japan
Yanasse, Horacio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-13
horacioyanasse@gmail.com
DCT, UNIFESP, São José dos Campos, São Paulo, Brazil
Yang, Dan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-10
1007928714@qq.com
Southwestern University of Finance and Economics, China
Yang, Hao . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-04
hyang@vtti.vt.edu
Civil and Environmental Engineering, Virginia Tech Transportation Institute, Blacksburg, VA, United States
Yang, Hongsuk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-09
hongsuk@snu.ac.kr
Seoul National University, Korea, Republic Of
Yang, Jian-Bo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-27
jian-bo.yang@manchester.ac.uk
Manchester Business School, Manchester, United Kingdom
Yang, Jian-Bo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-02, HD-27
jian-bo.yang@mbs.ac.uk
Manchester Business School, Manchester, United Kingdom
Yang, Jian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-15
jianyang@yahoo-inc.com
Yahoo Labs, Sunnyvale, CA, United States
Yang, Liu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-19
amyangliu@gmail.com
Business School, University of International Business and
Economics, Beijing, China
Yang, Liu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-22, ME-23
yangliu@sem.tsinghua.edu.cn
Tsinghua University, China
Yang, Nian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-29
IFORS 2014 - Barcelona
yangnian@nju.edu.cn
Department of Finance and Insurance, School of Business,
Nanjing University, Nanjing, Jiangsu, China
Yang, Qingyu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-35
qyang@wayne.edu
Wayne State University, Detroit, Michigan, United States
Yang, Shun-Chieh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-40
pengyengyin@gmail.com
National Chi Nan University, Nantou, Taiwan
Yang, Taho . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-42
taho.yang@gmail.com
Institute of Manufacturing Information and Systems, National Cheng Kung University, Tainan, Taiwan
Yang, Wenguo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-35
yangwg@ucas.ac.cn
Mathematics, University of Chinese Academy of Sciences,
Beijing, China
Yang, Xianfeng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-04
xyang125@umd.edu
Department of Civil & Environmental Engineering, University of Maryland, College Park, MD, United States
Yang, Yongsuk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-42
cnc4ever@gmail.com
Seoul National University, Korea, Republic Of
Yang, Zhengfeng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-16
zfyang@sei.ecnu.edu.cn
Shanghai Key Laboratory of Trustworthy Computing, East
China Normal University, China
Yannacopoulos, Denis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-18
dgian@teipir.gr
Department of Business Administration, Technological Educational Institute of Piraeus, Egaleo, Greece
Yano, Candace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-27
yano@ieor.berkeley.edu
IEOR Dept. and Haas School of Business, University of California, Berkeley, Berkeley, CA, United States
Yao, Xiao . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-34
X.YAO-2@sms.ed.ac.uk
University of Edinburgh Business School, University of Edinburgh, China
AUTHOR INDEX
Ye, Yinyu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-26
yinyu-ye@stanford.edu
Management Science and Engineering, Stanford University,
Stanford, CA, United States
Yearworth, Mike . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-38, HD-38
mike.yearworth@bristol.ac.uk
Faculty of Engineering, University of Bristol, Bristol, United
Kingdom
Yelbay, Belma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-17
byelbay@sabanciuniv.edu
Sabanci University, Istanbul, Turkey
Yeo, Wee Meng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-32
weemeng_yeo@hotmail.com
OM, Scheller College of Business, Georgia Institute of Technology, Atlanta, Georgia, United States
Yeomans, Julian Scott . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-23
syeomans@schulich.yorku.ca
OMIS, Schulich School of Business, York University,
Toronto, Ontario, Canada
Yerlikaya Ozkurt, Fatma . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-43
fatmayerlikaya@gmail.com
Scientific Computing, Institute of Applied Mathematics,
Ankara, Turkey
Yildirim, E. Alper . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-16
alperyildirim@ku.edu.tr
Industrial Engineering, Koc University, Sariyer, Istanbul,
Turkey
Yildiz, Gokalp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-15, TE-27
gokalp.yildiz@deu.edu.tr
Industrial Engineering, Dokuz Eylul University, izmir,
Turkey
Yin, Peng-Yeng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-40
pyyin@ncnu.edu.tw
Department of Information Management, National Chi Nan
University, Puli, Nantou, Taiwan
Yıldırım, Miray Hanım . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-09
e160106@metu.edu.tr
Institute of Applied Mathematics, Middle East Technical
University, Ankara, Turkey
Yapıcı Pehlivan, Nimet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-39
nimet@selcuk.edu.tr
Statistics, Selcuk University, Konya, Turkey
Yıldız, Şahan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-18
ysahan@metu.edu.tr
Industrial Engineering, Middle East Technical University,
Ankara, Turkey, Turkey
Yasui, Yuichiro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-09
yasui@indsys.chuo-u.ac.jp
Research and Development Initiative, Chuo university,
Tokyo, Japan
Yıldızbaşı, Abdullah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-39
abdullahyildizbasi@gmail.com
Industrial Engineering, Engineering and Natural Sciences,
Ankara, Turkey
Yau, Kelvin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-22
mskyau@cityu.edu.hk
Department of Management Sciences, City University of
Hong Kong, Hong Kong
Yılmaz Balaman, Şebnem . . . . . . . . . . . . . . . . . . . . . . . . . . MA-38
s.yilmaz@deu.edu.tr
Industrial Engineering, Dokuz Eylul University, Izmir,
Turkey
Yavuz, V. Alpagut . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-29
vyavuz@mku.edu.tr
Business Administration, Mustafa Kemal University, Turkey
Yılmaz, Hafize . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-27
hafizeyilmaz@halic.edu.tr
Industrial Engineering, Halic University, İstanbul, Turkey
Yazici, Ceyda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-17, ME-22
cyazici@metu.edu.tr
Statistics, Middle East Technical University, Turkey
Yılmaz, Hamid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-07
hamidyilmaz@gmail.com
Industrial Engineering, Ataturk University, Erzurum, Turkey
427
AUTHOR INDEX
IFORS 2014 - Barcelona
Yılmaz, Mustafa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-07
yilmaz.mustafay@gmail.com
Industrial Engineering, Ataturk University, Erzurum, Turkey
safak.yucel@duke.edu
The Fuqua School of Business, Duke University, Durham,
North Carolina, United States
Yılmaz, Şerife . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-07
serifeyilmaz@anadolu.edu.tr
Mathematics, Anadolu University, Eskisehir, Turkey
Yuge, Tetsushi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-27, MD-35
yuge@nda.ac.jp
Dept. of Electrical and Electronics, National Defense
Academy Japan, Yokosuka, Japan
Yoo, Youngji . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-16
kakiro@korea.ac.kr
Industrial and Management Engineering, Korea University,
Korea, Republic Of
Yumusak, Nejat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-09
nyumusak@sakarya.edu.tr
Computer Engineering, University of Sakarya, Serdivan,
Sakarya, Turkey
Yoon, Min . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-37
myoon@pknu.ac.kr
Pukyong National University, Busan, Korea, Republic Of
Yun, Yeboon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-37
yeboon@kansai-u.ac.jp
Kansai University, Suita-shi, Osaka, Japan
York, Grady S. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-06
stan.york@belmont.edu
College of Business Administration, Belmont University,
Nashville, Tennessee, United States
Yunusoglu, Mualla Gonca . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-27
gonca.yunusoglu@deu.edu.tr
Industrial Engineering, Dokuz Eylul University, Turkey
Yousfi, Naouel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-25
yousfi_na@hotmail.com
Operational Research, University of Bejaia. LAMOS, Algeria
Yozgatligil, Ceylan . . . . . . . . . . . . . . . . . . . . . . . . . . MA-17, ME-22
ceylan@metu.edu.tr
Statistics, Middle East Technical University, Ankara,
Cankaya, Turkey
Ypsilantis, Panagiotis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-15
pypsilantis@rsm.nl
Technology & Operations Management, RSM, Erasmus University of Rotterdam, Rotterdam, Netherlands
Yu, Chaowen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-25
yu-chaowen@a7.keio.jp
Economics, Keio University, Tokyo, Japan
Yu, Jiun-Yu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-39
jyyu@ntu.edu.tw
Business Administration, National Taiwan University, Taipei,
Taiwan
Yu, Taesun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-13
taesunyu@simlab.kaist.ac.kr
Industrial and Systems Engineering, KAIST, Daejeon, Korea,
Republic Of
Yu-Jun, Zheng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-20
yujun.zheng@computer.org
College of Computer Science & Technology, Zhejiang University of Technology, Hangzhou, China
Yuan, Xiaoming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-38
xmyuan@hkbu.edu.hk
Department of Mathematics, Hong Kong Baptist University,
Kowloon Tong, Hong Kong
Yuan, Yaxiang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-14, TB-38
yyx@lsec.cc.ac.cn
Institute of Computational Mathematics, Chinese Academy
of Sciences, Beijing, China
Yuan, Yuan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-20
yyuan.tli@gmail.com
The Logistics Institute, Northeastern University, China
Yucel, Safak . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-20
428
Yurtkuran, Alkin. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-17
alkin@uludag.edu.tr
Industrial Engineering Department, Uludag University,
Bursa, Turkey
Yusufoğlu, Elçin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-12
elcin.yusufoglu@usak.edu.tr
Department of Mathematics, Science and Art Faculty, Usak
University, Usak, Turkey
Yüzügüllü, Nihat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-39
nyuzugul@ogu.edu.tr
Industial Engineering Department, Osmangazi University,
Turkey
Zaarour, Nizar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-37
n.zaarour@neu.edu
Supply Chain And Information Management, Northeastern
University, Boston, MA, United States
Zacchino, Sandro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-13
sandro.zacchino@unisalento.it
D.I.I., Università del Salento, Lecce, Italy
Zadnik Stirn, Lidija . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-08
lidija.zadnik@bf.uni-lj.si
Biotechnical Faculty, University of Ljubljana, Ljubljana,
Slovenia
Zagorc-Kontic, Sonja . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-42
sonja.zagorc@ijs.si
Environmental Sciences, Jozef Stefan Institute, Ljubljana,
Slovenia
Zahedi, Zahedi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-17
zahedi911@yahoo.com
Medan Institute of Technology, Indonesia
Zak, Jacek . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-37
jacek.zak@put.poznan.pl
Department of Logistics, Poznan University of Technology,
Poznan, Wielkopolska, Poland
Zakharov, Victor . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-02, HE-04
mcvictor@mail.ru
Faculty of Applied Mathematics, Saint-Petersburg state university, Saint-Petersburg, Russian Federation
Zaki, Sari . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-35, MB-44
z_sari@mail.univ-tlemcen.dz
IFORS 2014 - Barcelona
Faculty of Technology, University of Tlemcen, Tlemcen, Algeria
Zamarripa, Miguel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-13
miguel.angel.zamarripa@upc.edu
Departamento de Ingenieria Quimica, Universitat Politècnica
de Catalunya, Spain
AUTHOR INDEX
Cyprus, Nicosia, Cyprus
Zgurovsky, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-19
zgurovsm@hotmail.com
National Technical University of Ukraine "Kyiv Polytechnic
Institute, Kyiv, Ukraine
Zamoner, Ismael Peruzzo . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-14
ipzamoner@gmail.com
Catalitica Consultoria de Gestão, São Paulo, SP, Brazil
Zhan, Shuguang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-01
shuguangzhan@my.swjtu.edu.cn
Transportation and Logistics, South-West Jiaotong University, Chengdu, Sichuan, China
Zamora-Mata, Juan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-39
jmzm@xanum.uam.mx
Process Engineering, Universidad Autónoma MetropolitanaIztapalapa, México, D.F., Mexico
Zhang, Abraham . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-16
abrahamz@waikato.ac.nz
Waikato Management School, University of Waikato, Hamilton, New Zealand
Zanela, Olivo Omar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-35
ozanela@its.jnj.com
Johnson & Johnson Medical Mexico, Mexico City, Distrito
Federal, Mexico
Zhang, Heng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-11
hengzhang24@gmail.com
ESE19104, University of Pennsylvania, Philadelphia, Pennsylvania, United States
Zank, Jennifer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-06
jennshin@med.umich.edu
Pediatrics, University of Michigan, Ann Arbor, United States
Zhang, Huizhen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-08
zhzzywz@163.com
University of Shanghai for Science and Technology, Shanghai, China
Zaras, Kazimierz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-31
Kazimierz.Zaras@uqat.ca
Université du Québec en Abitibi-Témiscamingue, RouynNoranda, Canada
Zarzo, Alejandro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-01
alejandro.zarzo@upm.es
Matematica Aplicada, ETS. Ingenieros Industriales, Universidad Politecnica de Madrid, Madrid, Spain
Zaslavski, Alexander . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-25
ajzasl@techunix.technion.ac.il
Technion, Haifa, Israel
Zavadskas, Edmundas Kazimieras . . . . . . . . . . . . . . . . . . . TD-45
edmundas.zavadskas@vgtu.lt
Department of Construction Technology and Management,
Vilnius Gediminas Technical University, Vilnius, Lithuania
Zeimpekis, Vasileios . . . . . . . . . . . . . . . . . . . . . . . . . MB-06, HE-44
vzeimp@fme.aegean.gr
Financial & Management Engineering, University of the
Aegean, Chios Island, Greece
Zhang, Jinlong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-19
prozhangjl@gmail.com
School of Management, Huazhong University of Science and
Technology, Wuhan, China
Zhang, Meng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-10
zhangmeng@amss.ac.cn
Institute of Applied Mathematics, University of Chinese
Academy of Sciences, Beijing, Beijing, China
Zhang, Qiang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-25
qiangzhang@bit.edu.cn
Beijing Institute of Technology, School of Management and
Economics, Beijing, Beijing, China
Zhang, Qun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-21
zq@ustb.edu.cn
University of Science and Technology Beijing, China
Zhang, Rachel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-15
rzhang@ust.hk
IELM, Hong Kong UST, Kowloon, Hong Kong
Zeise, Philipp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-04
philipp.zeise@uni-siegen.de
Lehrstuhl für Quantitative Planung, Universität Siegen,
Siegen, NRW, Germany
Zhang, Rui . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-15
ruizhang@umd.edu
Smith School of Business, University of Maryland, College
park, MD, United States
Zekic-Susac, Marijana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TD-19
marijana@efos.hr
Faculty of Economics in Osijek, University of Osijek, Osijek,
Croatia
Zhang, Shu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-41
shu-zhang-1@uiowa.edu
Management Science, University of Iowa, Iowa City, IA,
United States
Zemel, Amos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-25
amos@bgu.ac.il
Solar Energy & Environmental Physics, Ben Gurion University, Sde Boker Campus, Israel
Zhang, Weiming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-18, ME-44
zhangweimingnudt@163.com
Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology,
changsha, China
Zendehzaban, Sonia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-38
pasonda@hotmail.com
Universidad Carlos III, Spain
Zervopoulos, Panagiotis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-45
pzervopoulos@hotmail.com
Faculty of Economics and Management, Open University of
Zhang, Xubing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-19
msxubing@polyu.edu.hk
Marketing and Management, HK Polytechnic University,
Hung Hom, Hong Kong
Zhang, Yanru . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-04
429
AUTHOR INDEX
IFORS 2014 - Barcelona
yrzhang@umd.edu
Civil and Environmental Engineering, University of Maryland, College Park, MD, United States
Zhang, Yingqian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-41
yqzhang@ese.eur.nl
Econometrics, Erasmus University Rotterdam, Rotterdam,
Select U.S. States, Netherlands
Zhang, Yin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-38
yzhang@rice.edu
Dept. of CAAM, Rice University, Houston, Texas, United
States
Zhang, Zaikun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HB-14
zhang@mat.uc.pt
Department of Mathematics, University of Coimbra, Coimbra, Coimbra, Portugal
Zhao, Lingqi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-39
zlqlmjzt@163.com
College of Computer Science and Technology, Inner Mongolian University for the Nationalities„ Tongliao, China
Zhao, Qingjie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-11
xiaoxiaozhiqi@163.com
School of Computer Science &Technology HUST, Huazhong
University of Science & Technology, Wuhan, Hubei, China
Zhao, Xiaobo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-23
xbzhao@tsinghua.edu.cn
Industrial Engineering, Tsinghua University, Beijing, China
Zhen, Lu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-05
lzhen.sh@gmail.com
School of Management, Shanghai University, Shanghai,
China
Zheng, Karen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-15
yanchong@MIT.EDU
MIT, United States
Zheng, Nan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-04
nan.zheng@epfl.ch
LUTS, EPFL, Lausanne, Switzerland
Zheng, Zhichao . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-16, TA-16
danielzheng@smu.edu.sg
Singapore Management University, Singapore, Singapore
Zhu, Bo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-03
acoustic.zhu@gmail.com
College of Civil Aviation, Nanjing University of Aeronautics
and Astronautics, Nanjing, Jiangsu Province, China
Zhu, Cheng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-18, ME-44
zhuchengnudt@163.com
Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology,
China
Zhu, Jinfu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-03
zhujf@nuaa.edu.cn
College of Cicil Aviation, Nanjing University of Aeronautics
and Astronautics, Nanjing, Jiangsu Province, China
Zhu, Wanshan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-09
zhuws@umich.edu
Industrial Engineering, Tsinghua University, Beijing, China
Zhu, Weidong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HD-27
zhuwd@hfut.edu.cn
Hefei University of Technology, Hefei, China
Zhu, Xiang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-05
x.zhu@rug.nl
Operations, University of Groningen, Groningen, Groningen,
Netherlands
Zhuang, Weifen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-39
wfzhuang@xmu.edu.cn
School of Management, Xiamen University, Xiamen, Fujian,
China
Zhukova, Ksenia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-16
kz@pisem.net
OOO "Rus-Telecom", Russian Federation
Zhupanska, Olesya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HE-14
olesya-zhupanska@uiowa.edu
Mechanical and Industrial Engineering, University of Iowa,
Iowa City, IA, United States
Zilinskas, Antanas . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-18, TE-18
antanas.zilinskas@mii.vu.lt
Institute of Mathematics and Informatics, Vilnius University,
Vilnius, Lithuania
Zhou, Chifei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-33
zhou_cf@sina.cn
Academy of Military Science, Beijing, China
Zilinskas, Julius . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-18, TE-18
julius.zilinskas@mii.vu.lt
Institute of Mathematics and Informatics, Vilnius University,
Vilnius, Lithuania
Zhou, Taoqing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-11
qqis@163.com
school of Science & Technology, Huazhong University of
Science & Technology, Wuhan, China
Zimberg, Bernardo . . . . . . . . . . . . . . . . . . . . . . . . . . FB-13, HD-35
bzimberg@ancap.com.uy
Planning - LNG Project, ANCAP, Refining & Universidad
Católica del Uruguay, Montevideo, Uruguay
Zhou, Xuesong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-01
lymeng@bjtu.edu.cn
School of Sustainable Engineering and the Built Environment, Phoenix, Arizna, United States
Zimmermann, Jürgen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TE-12
juergen.zimmermann@tu-clausthal.de
Operations Research, TU Clausthal, Clausthal-Zellerfeld,
Germany
Zhou, Yiwei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-06
zhouy7@rpi.edu
Rensselaer Polytechnic Institute, Troy, United States
Zimmermann, Uwe T. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-01
u.zimmermann@tu-bs.de
Institute of Mathematical Optimization, TU Braunschweig,
Braunschweig, Germany
Zhou, Zhili . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-31
zhili@sg.ibm.com
IBM Research Collaboratory, Singapore, IBM Research, Singapore
430
Zimmermann, Wolf . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-43
zimmer@informatik.uni-halle.de
University Halle, Halle (Saale), Germany
IFORS 2014 - Barcelona
Zinder, Yakov . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-12
yakov.zinder@uts.edu.au
Department of Mathematical Sciences, University of Technology, Sydney, Sydney, NSW, Australia
Ziya, Serhan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TB-06
ziya@unc.edu
University of North Carolina, Chapel Hill, NC, United States
Zlicar, Blaz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-25
blaz.zlicar.11@ucl.ac.uk
Computer Science, University College London, London,
United Kingdom
Zografidou, Eleni . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ME-08
ezografi@fmenr.duth.gr
Forestry and Management of the Environment and Natural Resourses, Democritus University of Thrace, Orestiada,
Greece
Zolfaghari, Saeed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-19
zolfaghari@ryerson.ca
Ryerson University, Toronto, Canada
Zopounidis, Constantin . . . . . . . . . . . . . . . . . . . . . . HA-16, TA-29
kostas@dpem.tuc.gr
Dept. of Production Engineering and Management, Technical University of Crete, Chania, Greece
AUTHOR INDEX
Zubov, Vladimir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-09
zubov@ccas.ru
Mechanics of continuum media, Institution of Russian
Academy of Sciences Dorodnicyn Computing Centre of
RAS, Moscow, Russian Federation
Zuddas, Paola . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-05, FA-43
zuddas@unica.it
Dep. of Land Engineering, University of Cagliari, Cagliari,
Sardinia, Italy
Zugno, Marco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HA-09
mazu@dtu.dk
Applied Mathematics and Computer Science, Technical University of Denmark (DTU), Kgs. Lyngby, Denmark
Zuidwijk, Rob . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA-15
rzuidwijk@rsm.nl
Decision and Information Sciences, RSM Erasmus University, Rotterdam, Netherlands
Zuluaga, Luis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TA-16
lzuluagag@gmail.com
Industrial and Systems Engineering, Lehigh University,
United States
Zouweyna, Mordji . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FB-31
m.zouweyna@gmail.com
Laboratory LAMOS, 06000, Bejaia, Algeria
Zurheide, Sebastian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FA-10
zurheide@tu-harburg.de
Institute for Operations Research and Information Systems,
Hamburg University of Technology (TUHH), Hamburg,
Hamburg, Germany
Zsifkovits, Martin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD-44
martin.zsifkovits@univie.ac.at
Department of Business Administration, University of Vienna, Vienna, Vienna, Austria
Zurkowski, Piotr . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MB-28
kareth92@gmail.com
Poznan University of Technology, Kostrzyn, Wielkopolska,
Poland
431
S ESSION I NDEX
Sunday, 16.00-17.30
SA-50: Opening Session (Plenaries room) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Monday, 8:30-10:00
MA-01:
MA-02:
MA-03:
MA-04:
MA-05:
MA-06:
MA-07:
MA-08:
MA-09:
MA-10:
MA-11:
MA-12:
MA-13:
MA-14:
MA-15:
MA-16:
MA-17:
MA-18:
MA-19:
MA-20:
MA-21:
MA-22:
MA-23:
MA-24:
MA-25:
MA-26:
MA-27:
MA-28:
MA-29:
MA-30:
MA-31:
MA-32:
MA-33:
MA-34:
MA-35:
MA-36:
MA-37:
MA-38:
MA-39:
MA-40:
MA-41:
MA-42:
MA-43:
MA-44:
MA-45:
Railway Scheduling Problems (Room 118) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
Routing Problems with Profits and Other Applications (Room 111 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
Airline/Airport Optimisation in Operations and Scheduling (Room 001 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
Supply Chain Planning 1 (Room 119) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Offshore Upstream Logistics (Room 002 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
City Logistic Operations (Room 211) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Models for Gas and Electricity Markets (Room 003 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Energy and Environmental Management (Room 120) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Dynamical Systems and Mathematical Modelling (Room 121) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Optimization Methods for Smartgrid Management (Room 122) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Optimization Methods in Transportation Systems (Room 113) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
Graphs and Networks I (Room 004 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
Scheduling Cluster Tools (Room 123) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
Realistic Production Scheduling (Room 124) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
Network Pricing (Room 125) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
Copositive and Polynomial Optimization I (Room 127) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
Global Optimization, Modelling and Data Mining (Room 005 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
Multiobjective Optimization in Practice (Room 112) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
Retail Shelf and Inventory Planning (Room 128) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
IFORS Prize for OR in Development 2014 - 1 (Room 129) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
Optimization Modeling Software & Systems 1 (Room 006 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
Stochastic Models (Room 007) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
Perspectives on Behavioural Operations Research (Room 008) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Preference Learning I (Room 212) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Infinite-Horizon Problems of Mathematical Economics (Room 009) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Fuzzy Goal Programming (Room 010) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
OR in Quality Management I (Room 213) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Challenge ROADEF/EURO 1 (Room 130) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
Behavioral Economics and Finance (Room 011 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
Advances in Financial Mathematics, Economics and OR (Room 012 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
Elicitation (Room 013) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
Decision Analysis and Intelligence Processing (Room 014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
Stochastic Inventory Models with Environmental Constraints (Room 015) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
Big Data and Network Methods (Room 016) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
Stochastic Modeling and Simulation (Room 131) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
Fisheries (Room 132) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
AHP (Room 017) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Biomass-Based Supply Chains I (Room 214) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
ORAHS I - Effectiveness & Performance (Room 018) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Scheduling and Lot Sizing Problems (Room 019) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
Lot-Sizing and Related Topics 1 (Room 216) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
Green Freight Transportation 1 (Room 215) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
Algorithms and Applications - 1 (Room 217) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
Simulation in Management Accounting and Management Control I (Room 218) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
Computational Stochastic Programming (Room 219) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
Monday, 10:30-12:00
MB-01: Train Timetabling and Dispatching (Room 118) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
MB-02: Models and Algorithms for Arc Routing Problems (Room 111 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
432
IFORS 2014 - Barcelona
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SESSION INDEX
Air Traffic Management (Room 001 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Supply Chain Planning 2 (Room 119) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
Oil and Gas Transportation (Room 002 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
Strategic Freight Demand Models (Room 211) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Complementarity Models in Natural Gas and Renewable Markets (Room 003 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Electricity Markets and Smart Grids (Room 120) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Dynamical Systems and Mathematical Modelling 2 (Room 121) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
Integration of Distributed Energy Resources in Electricity Systems (Room 122) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
Advances in Specialized Zero-One Optimization (Room 113) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
Graphs and Networks II (Room 004 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
Scheduling Theory and Applications (Room 123) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
Parallel Machines Problems (Room 124) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Dynamic and Competitive Pricing Models (Room 125) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Copositive and Polynomial Optimization II (Room 127) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Global Optimization and Applications in Development I (Room 005 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
Applications of Goal Programming (Room 112) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
Business Analytics Methods for Demand and Supply Planning and Control (Room 128) . . . . . . . . . . . . . . . . . . . . . . . . . . 28
IFORS Prize for OR in Development 2014 - 2 (Room 129) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
Optimization Modeling Software & Systems 2 (Room 006 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
OR and Health Care Management (Room 007) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
Behavioural Issues in Decision Making and Negotiation (Room 008) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
Preference Learning II (Room 212) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
Mathematical Economics and Optimal Control (Room 009) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
Fuzzy Multiobjective Programming (Room 010) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
OR in Quality Management II (Room 213) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
Challenge ROADEF/EURO 2 (Room 130) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
Stochastic Models and Finance (Room 011 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
Financial Mathematics and OR (Room 012 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
Decision Processes under a Life-cycle Perspective (Room 013) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
Health Care Analytics (Room 014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
Environmental Sustainability in Global Operations (Room 015) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
Large-Scale Risk Systems (Room 016) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
Stochastic Sports Analysis (Room 131) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
Integrated Forest Planning (Room 132) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
AHP Application (Room 017) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
Biomass-Based Supply Chains II (Room 214) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
ORAHS V - Outpatient Scheduling (Room 018) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
Production and Supply Chain Design (Room 019) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
Lot-Sizing and Related Topics 2 (Room 216) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
Electric Vehicles (Room 215) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
Algorithms and Applications - 2 (Room 217) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
Simulation in Management Accounting and Management Control II (Room 218) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
Stochastic Programming Models and Algorithms (Room 219) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
Monday, 12:15-13:45
MC-50: Plenary Session M. Brandeau (Plenaries room) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
Monday, 14:00-15:30
MD-01:
MD-02:
MD-03:
MD-04:
MD-05:
MD-06:
MD-07:
MD-08:
MD-09:
MD-10:
MD-11:
Delays and Disruptions (Room 118) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Urban Logistics Problems (Room 111 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Robust and Integrated Models for Airline Scheduling (Room 001 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Supply Chain Design 1 (Room 119) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Supply Chain Management in Petroleum Industry (Room 002 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Behavioral Research on City Logistics (Room 211) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Modelling the German "Energiewende" (Energy Transformation) (Room 003 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Sustainable Management and Climate Change (Room 120) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Stochastic and Deterministic Dynamic Programming and its Applications 1 (Room 121) . . . . . . . . . . . . . . . . . . . . . . . . .
Robust and Stochastic Models for Electricity Systems (Room 122) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Impact of Combinatorial Optimization on Solving Challenging Applications (Room 113) . . . . . . . . . . . . . . . . . . . . . . . .
40
40
40
41
41
42
42
42
43
43
44
433
SESSION INDEX
MD-12:
MD-13:
MD-14:
MD-15:
MD-16:
MD-17:
MD-18:
MD-19:
MD-20:
MD-21:
MD-22:
MD-23:
MD-24:
MD-25:
MD-26:
MD-27:
MD-28:
MD-29:
MD-30:
MD-31:
MD-32:
MD-33:
MD-34:
MD-35:
MD-36:
MD-37:
MD-38:
MD-39:
MD-40:
MD-41:
MD-42:
MD-43:
MD-44:
MD-45:
IFORS 2014 - Barcelona
Graphs and Networks III (Room 004 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
Single Machine Scheduling (Room 123) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
Other Real and General Problems in Production Scheduling (Room 124) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
Novel Models and Applications in Revenue Management (Room 125) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
Copositive and Polynomial Optimization III (Room 127) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
Global Optimization and Applications in Development II (Room 005 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
Surrogate-Assisted Multiobjective Optimization I (Room 112) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
Retail Labor Scheduling (Room 128) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
IFORS Prize for OR in Development 2014 - 3 (Room 129) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
Optimization-Related Modeling & Software (Room 006 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
DEA, AHP and Statistical Analysis (Room 007) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
Emotions and Human Behaviour in Interactions (Room 008) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
Preference Learning III (Room 212) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
Mathematical Methods of the Economic Theory (Room 009) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
Neural Networks and Applications (Room 010) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
OR in Quality Management III (Room 213) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
Optimal Project Investment Sequencing (Palisade) (Room 130) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
Volatility Modeling and Investment Strategies (Room 011 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
Financial Mathematics 1 (Room 012 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
Public Sector Networks and Applications (Room 013) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
Humanitarian Operations Research for Developing Countries (Room 014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
Closed-loop Supply Chains and Reverse Logistics (Room 015) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
Energy Analytics (Room 016) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
Stochastic Models (Room 131) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
Forestry Industry Production Planning and Management (Room 132) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
Fuzzy AHP and ANP (Room 017) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
Biomass-Based Supply Chains III (Room 214) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
ORAHS II - Quality Improvement (Room 018) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
Supply Chain Optimization (Room 019) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
Lot-Sizing and Related Topics 3 (Room 216) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
Green Freight Transportation 2 (Room 215) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
Algorithms and Applications - 3 (Room 217) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
Simulation in Management Accounting and Management Control III (Room 218) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
Stochastic Programming in Logistics and Transportation (Room 219) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
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Delays and Disruptions II (Room 118) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
Maps, Zones and Routing (Room 111 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
Addressing Uncertainty in Passenger Aviation (Room 001 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
Supply Chain Design 2 (Room 119) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
Fuel Logistics (Room 002 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
Passenger Transportation in Cities (Room 211) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
Multi-Level Programming and Equilibrium Models in Electricity Markets (Room 003 ) . . . . . . . . . . . . . . . . . . . . . . . . . . 61
Optimal Design in Environmental Management (Room 120) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
Stochastic and Deterministic Dynamic Programming and its Applications 2 (Room 121) . . . . . . . . . . . . . . . . . . . . . . . . . . 62
Optimization Methods for Offshore and Onshore Wind Farms (Room 122) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
Miscellaneous Topics in Combinatorial Optimization (Room 113) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
Graphs and Networks IV (Room 004 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
Project Scheduling 1 (Room 123) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
DEA in Health and Education (Room 124) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
Pricing and Strategic Consumer Behavior in Revenue Management (Room 125) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
Copositive and Polynomial Optimization IV (Room 127) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
Global Optimization and Applications in Development III (Room 005 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
Surrogate-Assisted Multiobjective Optimization II (Room 112) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
Retail Distribution and Replenishment (Room 128) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
Managing Risk in Energy Storage and Trading (Room 129) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
Optimization Modeling Applications in Air Transportation (Room 006 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
Machine Learning in Healthcare (Room 007) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
Behavioural Issues in Modeling and Simulation (Room 008) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
Preference Learning IV (Room 212) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
Optimization and Mathematical Economics (Room 009) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
Fuzzy Decision Making 1 (Room 010) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
Simulation and Numerical Methods in Finance (Room 213) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
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SESSION INDEX
Multiple Criteria Decision Making and Optimization 1 (Room 011 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
Financial Mathematics 2 (Room 012 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
Recent Advances on Decision Processes (Room 013) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
Network Decision Support (Room 014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
Measuring and Optimizing Sustainable Behavior in Existing Systems (Room 015) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
Power Systems Economics (Room 016) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
Simulation and Advanced Optimization, in Aviation Management and Manufacturing (Room 131) . . . . . . . . . . . . . . . . 72
Forest Planning under Risk (Room 132) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
Multiobjective Optimization in Asia (I) (Room 017) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
Optimization Techniques for Some Statistics Models (Room 214) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
ORAHS III - Emergency Services (Room 018) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
Advances in Production and the Link with Supply Chain (Room 019) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
Lot-Sizing and Related Topics 4 (Room 216) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
Human Aspects in Transportation and Logistics (Room 215) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
Accounting, Corporate Governance and Valuation (Room 217) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
Game Theory (Room 218) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
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(Integrated) Planning Models (Room 118) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
Routing and Scheduling (Room 111 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
Aviation Management and Processes (Room 001 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
Contracting (Room 119) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
Stochastic Programming in Maritime Transportation (Room 002 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
Health Care System Design (Room 211) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
Planning and Operation in Electric Power System (Room 003 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
Electric Mobility (Room 120) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
Enumeration and Discrete Structures (Room 121) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
Decision Support Models for the Energy Industry I (Room 122) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
Mixed-Combinatorial Methods in Distance Geometry (Room 113) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
Graphs and Networks V (Room 004 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
Project Scheduling 2 (Room 123) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
DEA in Transportation and Logistics (Room 124) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
Behavioral Research in Pricing and Revenue Management (Room 125) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
Copositive and Polynomial Optimization V (Room 127) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
Nonconvex Programming: Local and Global Approaches I (Room 005 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
Robustness in Multiobjective Optimization I (Room 112) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
Retail Forecasting (Room 128) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
From the Old to the New: Managing the Transformation of our Energy System (Room 129) . . . . . . . . . . . . . . . . . . . . . . . 84
Optimization Modeling Applications in Manufacturing 1 (Room 006 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
Cooperation in Operations Management (Room 007) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
Behavioural Issues in Problem Structuring (Room 008) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
Ethics and OR I (Room 212) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
Applications of Game Theory (Room 009) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
Fuzzy Decision Making 2 (Room 010) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
Advances in Operations/Marketing Interface (Room 213) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
Challenge ROADEF/EURO 3 (Room 130) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
Multiple Criteria Decision Making and Optimization 2 (Room 011 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
Financial Mathematics 3 (Room 012 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
Processes of Applying MCDA (Room 013) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
Disaster Management (Room 014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
Defence and Security Applicatons (Room 015) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
Portfolio Optimization 1 (Room 016) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
Game Theory with Applications I (Room 131) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
Forest Management to Reduce Fire Risk (Room 132) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
Multiobjective Optimization in Asia (II) (Room 017) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
Optimality Conditions and Algorithms: From Convex to Nonconvex Optimization (Room 214) . . . . . . . . . . . . . . . . . . . . 92
ORAHS VI - Treatment Optimization (Room 018) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
Production Planning (Room 019) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
Green Logistics in Rich Vehicle Routing Problems (Room 216) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
Big Data Analytics for Quality Improvement (Room 215) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
Accounting and Financial Crisis (Room 217) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
OR in Regular Study Programs (Room 218) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
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TA-45: International Aspects of OR History and Education (Room 219) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
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Railway Timetabling (Room 118) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
Inventory-Routing Problems (Room 111 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
Airline and Airport Operations (Room 001 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
Warehousing (Room 119) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
Sustainability in Maritime Transportation (Room 002 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
Translation of Health Systems Engineering Research into Clinical Practice (Room 211) . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
Convex and Complementarity Models for Electricity Market Analysis (Room 003 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
Power Management and Decision Analysis in Sustainable Development (Room 120) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98
Control Theory & System Dynamics (Room 121) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98
Decision Support Models for the Energy Industry II (Room 122) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
Network Routing (Room 113) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
Nonstandard Numerical Methods for Differential Equations (Room 004 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
Advances in Scheduling (Room 123) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
DEA in Services (Room 124) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
Pricing and Consumer Behavior: Modeling and Estimation (Room 125) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
Structure Learning and Applications (Room 127) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
Nonconvex Programming: Local and Global Approaches II (Room 005 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
Robustness in Multiobjective Optimization II (Room 112) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
Inventory Planning I (Room 128) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
Managing Smart Energy Grids under Uncertainty - I (Room 129) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
Optimization Modeling Applications in Manufacturing 2 (Room 006 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
Cooperation in Manufacturing and Service Systems (Room 007) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
Behavioural Economics and Games (Room 008) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
Applications of Analytics to Strategy (Room 212) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
Numerical Methods in Data Mining (Room 009) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
Fuzzy Decision Making 3 (Room 010) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
Pricing, Bundling, and Strategic Consumers in Supply Chain Management (Room 213) . . . . . . . . . . . . . . . . . . . . . . . . . . 106
Turnkey Optimization on the Cloud (FICO) (Room 130) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
Multiple Criteria Decision Making and Optimization 3 (Room 011 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
Advances in Financial Decisions and Their Long-Term Horizon (Room 012 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
Portfolio Decision Processes (Room 013) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
Crisis and Disaster Management (Room 014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
Defence and Security Applications II (Room 015) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
Portfolio Optimization 2 (Room 016) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
Game Theory with Applications II (Room 131) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
Forest Fire Suppression (Room 132) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
Metaheuristics for Multiobjective Optimization (Room 017) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
Sparse Optimization Methods (Room 214) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
ORAHS VII - Healthcare Systems (Room 018) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
Educational Planning and Development (Room 019) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
Metaheuristics and Simheuristics in Logistics and Production (Room 216) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
Efficient Big Data Algorithms (Room 215) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
Accounting and Management Decisions (Room 217) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
Additional Educational Activities for OR (Room 218) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
Geometric Clustering (Room 219) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
Tuesday, 12:15-13:45
TC-50: Plenary Session J. Barceló (Plenaries room) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
Tuesday, 14:00-15:30
TD-01: Railway Scheduling (Room 118) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
TD-02: Cross-docking and Warehouse Operations Optimtization (Room 111 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
TD-03: Airline Planning (Room 001 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
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SESSION INDEX
Best Practices in Traffic Simulation (Room 119) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
Maritime Routing and Scheduling 1 (Room 002 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
Health Care Operations Management (Room 211) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
Challenges in Electricity Systems (Room 003 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
Green Design and Risk Pooling (Room 120) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
Modeling and Optimizing Electricity Markets (Room 121) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
Decision Support Models for the Energy Industry III (Room 122) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
Various New Advances in Combinatorial Optimization (Room 113) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
Difference Equations and Discrete Dynamical Systems (Room 004 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
Scheduling and Logistics (Room 123) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
DEA in Energy and Water services (Room 124) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
Strategic Consumer Behavior, Pricing and Customer Choice (Room 125) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
Machine Learning Applications in Web Technology (Room 127) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
Interior Point Methods for Large-Scale Optimization (Room 005 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
New Trends in Evolutionary Multiobjective Optimization (Room 112) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
Retail Demand Planning (Room 128) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
Power System Design and Operation (Room 129) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
ORCCS1 (Room 006 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
Game Theory Applications in Supply Chains (Room 007) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
Behavioural Operations and Supply-Chain Management (Room 008) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
Operations Finance Interface 1 (Room 212) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
Patterns Detection in Very Large Datasets (Room 009) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
Fuzzy Systems (Room 010) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
Contracts, Auctions, Upgrade Timing, and Reverse Supply Chain Management (Room 213) . . . . . . . . . . . . . . . . . . . . . 124
International Outreach and Implicit Expectations in OR (Room 130) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
Multiple Criteria Decision Making and Optimization 4 (Room 011 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
Location-Allocation Models (Room 012 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
Security Decision Processes (Room 013) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
Information Systems (Room 014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
Defence and Security Applications III (Room 015) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
Risk Analysis and Assessment (Room 016) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
Game Theory with Applications III (Room 131) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
Forest Management for Biodiversity (Room 132) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
Multicriteria Decision Making in Humanitarian Logistics (Room 017) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
Proximal and Splitting Algorithms (Room 214) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
Algorithms for Large-Scale 0-1 Linear and Quadratic Programming Problems (Room 018) . . . . . . . . . . . . . . . . . . . . . . . 129
Innovations in Meta-Analytics I (Room 019) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
Enterprise-wide Optimization (Room 216) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
OR in Systemic Risk, Credit Risk and Rating (Room 215) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
Data Mining, Statistics and Reliability Theory (Room 217) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
OR Promotion among Academia, Businesses, Governments, etc. (Room 218) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
Sustainable Development (Room 219) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132
Tuesday, 16:00-17:30
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Robustness and Maintenance of Vehicles and Infra (Room 118) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132
Vehicle Routing Applications (Room 111 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132
Continuous Location (contributed) (Room 001 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
Urban Traffic Control (Room 119) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
Optimization in Liner Shipping 1 (Room 002 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134
Stochastic Modeling in Health Care (Room 211) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134
Dynamical Models in Sustainable Development I (Room 003 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134
Carbon Footprint and Climate (Room 120) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
Decision Dependent Stochastic Problems and Day-Ahead Forecasting in Energy (Room 121) . . . . . . . . . . . . . . . . . . . . . 135
Energy Management and Modelling (Room 122) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136
Advances in Combinatorial Optimization (Room 113) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136
Preemptive Project Scheduling and Resource Leveling (Room 004 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136
Handling Uncertainty in Scheduling and Lot-Sizing 1 (Room 123) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
DEA Developments (Room 124) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
Revenue Management with Advertising Applications (Room 125) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138
Model Selection Methods (Room 127) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138
Conic Optimization and Applications (Room 005 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138
Nonconvex Multiobjective Optimization I (Room 112) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
Inventory Planning II (Room 128) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
437
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Stochastic Optimization in Energy Infrastructure Planning (Room 129) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140
Lessons from Industrial Collaboration (Room 006 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140
Cooperation and Competition in Operations Management (Room 007) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140
Analysis of Human Behavioural Data and Knowledge (Room 008) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
Operations Finance Interface 2 (Room 212) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
Data Mining via Pattern Analysis and Recognition (Room 009) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142
Nonconvex Nonsmooth Optimization Methods (Room 010) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142
Pricing Decisions (Room 213) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142
Congestion Games: Dynamics and Algorithms (Room 130) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
Multiple Criteria Decision Making and Optimization 5 (Room 011 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
Recent Models on Emerging Optimization Problems (Room 012 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
Topics in Decision Processes (Room 013) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
Data Mining Applications and Applied Probability (Room 014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
Defence and Security Applications IV (Room 015) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145
Risk Analysis and Management (Room 016) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145
Airline Optimization (Room 131) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
Agrifood Industry (Room 132) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
Indoor Localization (Room 017) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
Regularization Methods (Room 214) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147
Fuzzy Optimization in Supply Chain Management (Room 018) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147
Innovations in Meta-Analytics II (Room 019) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148
Simulation-Optimization in Logistics & Production (Room 216) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148
Applications in Decision Making & Decision Analysis (Room 215) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148
Data Mining, Economic Models and Games (Room 217) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
Multiobjective Linear Programming (Room 218) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
Analysis of Customer-Based Data (Room 219) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150
Thursday, 8:30-10:00
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438
Scheduling and Rescheduling Railways under a Dynamic Environment (Room 118) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
Time-dependent Vehicle Routing and Scheduling (Room 111 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
Discrete Location and Routing (Room 001 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
Network Traffic Modelling I (Room 119) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152
Maritime Routing and Scheduling 2 (Room 002 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152
Network Economics (Room 211) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153
Dynamical Models in Sustainable Development II (Room 003 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153
Carbon Emissions and Remanufacturing Problems (Room 120) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154
Dealing with Uncertainty and Renewable Sources in Electricity Markets (Room 121) . . . . . . . . . . . . . . . . . . . . . . . . . . . 154
DEA Theory I (Room 122) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154
Combinatorial Optimization: Applications (Room 113) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
Project Scheduling: Applications and Generalizations (Room 004 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
Handling Uncertainty in Scheduling and Lot-Sizing 2 (Room 123) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156
Advances in Nonlinear Optimization: Theory and Applications I (Room 124) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156
Revenue Management Application and Theory (Room 125) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
Categorical Data Analysis and Preference Aggregation (Room 127) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
Second-Order Conic Optimization (Room 005 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
Nonconvex Multiobjective Optimization II (Room 112) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158
Advances on Demand and Supply Planning in Consumer Goods and Retailing (Room 128) . . . . . . . . . . . . . . . . . . . . . . 158
Demand Response and Smart Grid Infrastructure (Room 129) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
Cutting and Packing 1 (Room 006 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
Competitive and Cooperative Games (Room 007) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
Applying Analytics to Big Data for Driving Big Outcomes (Room 008) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160
Dynamics and Learning in Games (Room 212) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160
Structuring Big Data (Room 009) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
Nondifferentiable Optimization: Theory, Algorithms and Applications I (Room 010) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
Emerging Applications of Decision Support Systems (Room 213) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
OR in Mining (Room 011 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
Recent Models on Cooperative Games and Integer Programming (Room 012 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
Network Design (Room 013) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
Supply Chain Concepts (Room 014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163
Defence and Security Applications V (Room 015) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163
Financial Modeling 1 (Room 016) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
Analysis and Management on Risk and Security (Room 131) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
Sustainability and Environmental Management (Room 132) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165
IFORS 2014 - Barcelona
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SESSION INDEX
Multiobjective Optimization in Asia, and Related Subjects (Room 017) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Soft OR / Systems Practice (Room 214) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Recent Developments in the SCIP Optimization Suite (Room 018) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Innovations in Meta-Analytics III (Room 019) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Stochastic/Robust Routing and Inventory Routing (Room 216) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Business Intelligence, Knowledge Management & Decision Systems (Room 215) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Various Advances on Optimisation in Health Care (Room 217) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Managing Risk in Supply Chains I (Room 218) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Business Analytics Optimization and Big Data (Room 219) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
165
165
166
166
167
167
168
168
168
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Robustness in Railway Operations (RobustRailS) (Room 118) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169
Variants of the Vehicle Routing Problem 1 (Room 111 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169
Network Location (Room 001 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170
Network Traffic Modeling II (Room 119) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170
Stowage Planning (Room 002 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171
Learning and Games in Networks (Room 211) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171
Dynamical Models in Sustainable Development III (Room 003 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172
Sustainable Supply Chains (Room 120) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172
Models for Electricity Production and Distribution (Room 121) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172
DEA Theory II (Room 122) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173
Combinatorial Optimization (Room 113) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173
Decentralized Multi-Project Scheduling (Room 004 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174
Process Planning and Task Scheduling under Uncertainties (Room 123) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174
Advances in Nonlinear Optimization: Theory and Applications II (Room 124) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174
Contemporary Issues in Revenue Management (Room 125) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175
Topic Modeling and Information Retrieval with Applications (Room 127) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175
Conic Optimization and IPMs (contributed) (Room 005 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176
Behavioral Aspects in Multiple Criteria Decision Making (Room 112) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176
Retail Inventory Management (Room 128) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176
Optimizing Generation with Wind and Hydro (Room 129) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
Cutting and Packing 2 (Room 006 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
Auctions and Algorithmic Mechanism Design (Room 007) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178
How Corporations Use Analytics to Impact the Bottom Line (Room 008) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178
Dynamic Mechanism Design (Room 212) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178
Advanced OR Methods for Data Mining (Room 009) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
Nondifferentiable Optimization: Theory, Algorithms and Applications II (Room 010) . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
Decision Analysis and Performance Measurement (Room 213) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180
Planning and Scheduling in Petrochemicals (Room 011 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180
Teaching OR/MS 1 (Room 012 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180
Survivability and Vulnerability (Room 013) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181
Supply Chain Management - Assembly Lines and Maintainance (Room 014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181
Hyperheuristics: Interfaces, Implementations and Applications (Room 015) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182
Financial Modeling 2 (Room 016) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182
Stochastic Modeling (Room 131) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182
Sustainable Forest Management (Room 132) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
Multi-Actor Multi-Criteria Analysis (Room 017) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
Soft OR / Systems and Multimethodology 1 (Room 214) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184
Advances on TSP and Related Subjects (Room 018) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184
Innovations in Meta-Analytics IV (Room 019) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184
Stochastic Models for the Design of Supply Chain Networks (Room 216) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
Integrated and Simulation-Based DSS Approaches (Room 215) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
Scheduling and Optimisation Models (Room 217) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186
Managing Risk in Supply Chains II (Room 218) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186
Routing Problems (Room 219) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186
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HC-50: Plenary Session R. Blackburn (Plenaries room) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187
439
SESSION INDEX
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Planning and Operations of Rapid Transit Systems (Room 118) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188
Variants of the Vehicle Routing Problem 2 (Room 111 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188
Applications of Location Analysis (Room 001 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188
Optimal Control of Motorways (Room 119) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189
Hinterland Transportation (Room 002 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189
Information Economics and Networks (Room 211) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190
Fuzzy Programming and Fuzzy Regression Analysis (Room 003 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190
Teaching OR/MS 2 (JMP) (Room 120) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190
Exact and Heuristics Decision Support Approaches for Energy Distribution, Planning and Management (Room 121) 191
DEA Theory III (Room 122) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191
Applications of Combinatorial Optimization (Room 113) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192
Project Scheduling and Control (Room 004 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192
Balancing and Sequencing of Assembly Lines 1 (Room 123) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192
Advances in Nonlinear Optimization: Theory and Applications III (contributed) (Room 124) . . . . . . . . . . . . . . . . . . . . 193
Revenue Management Models in Entertainment, Online Retail and Travel (Room 125) . . . . . . . . . . . . . . . . . . . . . . . . . . 193
Data Analysis and Transport Planning (Room 127) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194
Optimization and Decision Making: Theory and Applications (Room 112) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194
Inventory Planning III (Room 128) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195
Managing Smart Energy Grids under Uncertainty - II (Room 129) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195
Cutting and Packing 3 (Room 006 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195
(In)efficiency and Truthfulness in Auctions (Room 007) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196
Panel Discussion: Analytics in OR Societies (Room 008) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196
Repeated and Stochastic Games (Room 212) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196
Heuristics for Dynamic Transit Routing (Room 009) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197
Nondifferentiable Optimization: Applications to Large-Scale and Combinatorial Problems (Room 010) . . . . . . . . . . . 197
Decision Making and Applications (Room 213) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197
MINLP for Natural Gas Network Optimization (Room 130) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198
Distribution and Transportation in the Petrochemical Sector (Room 011 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198
Dynamical Systems and Game Theory (Room 012 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199
Scheduling and Queuing in Networks (Room 013) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199
Supply Chain Management - Supply and Ressource Planning (Room 014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199
Algorithm Configuration: Black, White and Gray Box (Room 015) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200
Financial Modeling 3 (Room 016) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200
Simulation and Optimization for Robust Supply Networks (Room 131) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201
Supply Chain in Agriculture (Room 132) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201
Advances on Recovery Inventory Management Policies I (Room 017) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202
Soft OR / Systems and Multimethodology 2 (Room 214) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202
Advances in Discrete and Global Optimization and on Graphs I (Room 018) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202
Prescriptive Analytics: Smart Solutions to Real-World Problems I (Room 019) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203
Stochastic Models in Production, Manufacturing and Services (Room 216) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203
Collaborative Decision Making (Social Networks & Web Resources) (Room 215) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203
Medical Informatics (Room 217) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204
Humanitarian Logistics, SCM Practices and Sustainable Development (Room 218) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204
Location Problems (Room 219) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205
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Scheduling and Rescheduling: Passenger Focus (Room 118) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206
Discrete Location (Room 001 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206
O-D Estimation (Room 119) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206
Port Operations - Miscellaneous (Room 002 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207
Learning, Resilience, Competition and Congestion (Room 211) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207
Fuzzy Optimization in Supply Chain Management, Production and Logistics (Room 003 ) . . . . . . . . . . . . . . . . . . . . . . . 208
Case Teaching (Room 120) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208
Energy Markets (Room 121) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208
Workforce Optimization (Room 122) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209
Topics in Linear Programming and Combinatorial Optimization (Room 113) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209
Project Scheduling and Scheduling (Room 004 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 210
Balancing and Sequencing of Assembly Lines 2 (Room 123) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 210
Advances in Nonlinear Optimization: Theory and Applications IV (contributed) (Room 124) . . . . . . . . . . . . . . . . . . . . . 210
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SESSION INDEX
Experimental Research in Management Accounting and Management Control 1 (Room 125) . . . . . . . . . . . . . . . . . . . . .
Combinatorial Methods for Data Analysis (Room 127) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Enumeration of Combinatorial Structures (Room 005 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Interactive MCDM (Room 112) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Demand Planning and Pricing (Room 128) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Controlling Electric Vehicles and Battery Storage (Room 129) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Cutting and Packing 4 (Room 006 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Agent Behavior in Markets and Related Subjects (Room 007) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Genetic and Population Based Algorithms (Room 008) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Algorithms for Stochastic Games (Room 212) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Metaheuristics in Autonomous Search (Room 009) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Nonsmooth Optimization for Learning and Classification (Room 010) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Decision Analysis for Risk Management (Room 213) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Applied Aspects of MINLP (Room 130) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Logistics and Blending in Natural Gas and Mining (Room 011 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Open Source & COIN-OR Optimisation (Room 012 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Location Problems in Networks (Room 013) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Supply Chain Optimization (Room 014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Hyperheuristics: General; and Related Topics (Room 015) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Decision Making in Finance (Room 016) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Planning and Control (Room 131) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Forest Value Chain Optimization (Room 132) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Advances on Recovery Inventory Management Policies II (Room 017) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Multi-Criteria Performance of Funds and Banks (Room 214) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Discrete Optimization I (Room 018) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Prescriptive Analytics: Smart Solutions to Real-World Problems II (Room 019) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Stochastic Vehicle Routing (Room 216) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Decision Analysis & Decision Making Approaches (Room 215) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Scheduling Problems in Water Distribution System Management (Room 217) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Optimization Practices for Sustainable Community Development (Room 218) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Location Problems / Supply Chain (Room 219) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
211
211
212
212
212
213
213
214
214
214
215
215
216
216
217
217
217
218
218
218
219
219
220
220
220
221
221
222
222
223
223
Friday, 8:30-10:00
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Network Capacity and Utilization (Room 118) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224
Vehicle Routing Problems 1 (Room 111 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224
Hub Location (Room 001 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224
Strategic Traffic Planning (Room 119) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225
Yardside Operations (Room 002 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225
Matheuristics I (Room 211) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225
Optimal Control with Applications (Room 003 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226
Dynamic Programming (Room 120) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226
Optimization of Electric Power Networks (Room 121) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227
Timetabling (Room 122) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227
Combinatorial Optimization Applications in Industry and Services (Room 113) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 228
Discrete-Continuous Scheduling (Room 004 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 228
Scheduling Applications 1 (Room 123) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 228
Experimental Research in Management Accounting and Management Control 2 (Room 125) . . . . . . . . . . . . . . . . . . . . . 229
Pattern Recognition (Room 127) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229
Graph Searching Games (Room 005 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 230
Applications of Multiobjective Optimization I (Room 112) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 230
Bi-objective Optimization: Methods and Applications (Room 128) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 230
Energy Trading (Room 129) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231
Cutting and Packing 5 (Room 006 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231
Game Theory and Customer Behavior in Service Systems (Room 007) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 232
Metaheuristics for Vehicle Routing (Room 008) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 232
Dynamic Stochastic Programming and Option Pricing (Room 212) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 232
Various Applications of Heuristics (Room 009) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233
Equilibrium and Variational Inequalities (contributed) (Room 010) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233
Infrastructure Development and Environment 1 (Room 213) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233
MINLP in the Oil and Gas Industry (Room 130) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234
Societal Complexity and Economy (Room 011 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234
Networks and Queueing Systems (Room 013) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235
Supply Chain Management (Room 014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235
441
SESSION INDEX
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IFORS 2014 - Barcelona
Managing Knowledge (Room 016) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235
Advances in Forecasting and Stochastic Programming Applications (Room 131) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236
Applications in Agriculture (Room 132) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236
Importance of Information In Inventory Management (Room 017) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237
Counterparty Risk and Decision Support Systems (Room 214) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237
Discrete Optimization II (Room 018) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237
Quantitative Models for Performance and Dependability I (Room 019) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 238
Auction Theory and Practice (Room 216) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 238
Qualitative Multiple Criteria Decision Making I (Room 215) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239
Water Distribution Network Design and Management (Room 217) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239
Friday, 10:30-12:00
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Getting the Decisions Right, Fast (IBM) (Room 118) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 240
Vehicle Routing Problems 2 (Room 111 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 240
Location (contributed) (Room 001 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 240
Traffic Management (Room 119) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 240
Quayside Operations (Room 002 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241
Matheuristics II (Room 211) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241
Theory of Optimal Control (Room 003 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242
Dynamic Programming and Multicriteria DSS (Room 120) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242
Electricity Networks (Room 121) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242
Team and Assignment Optimization (Room 122) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243
Euclidean Distance Geometry and Applications (Room 113) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243
Scheduling Models in Operational Decision Making (Room 004 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 244
Scheduling Applications 2 (Room 123) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 244
Shop Scheduling (Room 124) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 244
Experimental Research in Management Accounting and Management Control 3 (Room 125) . . . . . . . . . . . . . . . . . . . . . 245
Industrial Applications of Machine Learning (Room 127) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245
Combinatorial Structures (Room 005 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 246
Applications of Multiobjective Optimization II (Room 112) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 246
New Methods for Multiobjective Optimization (Room 128) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 246
Stochastic Unit Commitment with Renewables (Room 129) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247
Cutting and Packing 6 (Room 006 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247
Advances in Service Process Analysis (Room 007) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 248
VNS and ILS (Room 008) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 248
Tools and Applications in Actuarial Sciences (Room 212) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 248
Applications of Metaheuristics (Room 009) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249
Multiobjective Bi-Level Optimization (contributed) (Room 010) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249
Infrastructure Development and Environment 2 (Room 213) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 250
Advances in MINLP (Room 130) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 250
Societal Complexity and Healthcare (Room 011 ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 250
P2P, Social Networks and E-commerce (Room 013) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 251
Forecasting Methods (Room 014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 251
Knowledge Work and Workers (Room 016) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 251
Stochastic Modeling and Simulation with Applications (Room 131) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 252
Healthcare Management (Room 132) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 252
Managing Transshipments (Room 017) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 252
Assessing Systemic Risk (Room 214) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 253
Discrete Optimization III (Room 018) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 253
Quantitative Models for Performance and Dependability II (Room 019) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 254
Network Congestion Models (Room 216) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 254
Qualitative Multiple-Criteria Decision Making II (Room 215) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255
Risk Management and Performance Analysis (Room 217) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255
Friday, 12:15-13:45
FC-50: Plenary Session K. Smith-Miles (Plenaries room) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 256
442
IFORS 2014 - Barcelona
SESSION INDEX
Friday, 14:00-15:30
FD-50: Closing Ceremony (Plenaries room) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 256
443