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The Closest String Problem (CSP) calls for finding an n-string that minimizes its maximum distance from m given n-strings. Integer linear programming (ILP) proved to be able to solve large CSPs under the Hamming distance, whereas for the... more
The Closest String Problem (CSP) calls for finding an n-string that minimizes its maximum distance from m given n-strings. Integer linear programming (ILP) proved to be able to solve large CSPs under the Hamming distance, whereas for the Levenshtein distance, preferred in computational biology, no ILP formulation has so far be investigated. Recent research has however demonstrated that another metric, rank distance, can provide interesting results with genomic sequences. Moreover, CSP under rank distance can easily be modeled via ILP: optimal solutions can then be certified, or information on approximation obtained via dual gap. In this work we test this ILP formulation on random and biological data. Our experiments, conducted on strings with up to 600 nucleotides, show that the approach outperforms literature heuristics. We also enforce the formulation by cover inequalities. Interestingly, due to the special structure of the rank distance between two strings, cover separation can be done in polynomial time.
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This chapter presents a real-time emergency evacuation handling system based on internet of things (IoT) technologies. The IoT infrastructure has a core computational component that is in charge of minimizing the time necessary to... more
This chapter presents a real-time emergency evacuation handling system based on internet of things (IoT) technologies. The IoT infrastructure has a core computational component that is in charge of minimizing the time necessary to evacuate people from a building. The space and time dimension are discretized according to metrics and models in literature, as well as original methods. The component formulates and solves a linearized, time-indexed flow problem on a network that represents feasible movements of people at a suitable frequency. Accurate parameter setting makes the computational time to solve the model compliant with real-time use. An application of the proposed IoT system and its core algorithm to handle safe evacuation test in Palazzo Camponeschi—a building in L’Aquila (Italy) now and then used for exhibitions—is described, and diverse uses of the methodology are presented.
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Distributing material flows among the workstations of a plant is a crucial problem in order to reduce both production and logistics costs, especially when product mix and volume production are very large. Optimal solutions should meet due... more
Distributing material flows among the workstations of a plant is a crucial problem in order to reduce both production and logistics costs, especially when product mix and volume production are very large. Optimal solutions should meet due dates requirements while assigning operations in accordance to the production capacity available at the moment. Pursuing this objective is however complicated in case of a large product mix, due to the possibly large number of machine set-ups required. This paper deals with a real production process consisting in the assembly of micropumps and dispensers carried out by a major international manufacturer in its plants in Centre Italy. Two articulated methods based on column generation are devised for tackling situations of different size and complexity, and a sample of their potential effectiveness is exhibited.
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We address a 1-dimensional cutting stock problem where, in addition to trimloss minimization, we require that the set of cutting patterns forming the solution can be sequenced so that the number of stacks of parts maintained open... more
We address a 1-dimensional cutting stock problem where, in addition to trimloss minimization, we require that the set of cutting patterns forming the solution can be sequenced so that the number of stacks of parts maintained open throughout the process never exceeds a given s. For this problem, we propose a new integer linear programming formulation whose constraints grow quadratically with the number of distinct part types.
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We formulate a spatial pricing problem as bilevel non-capacitated location: a leader first decides which facilities to open and sets service prices taking competing offers into account; then, customers make individual decisions minimizing... more
We formulate a spatial pricing problem as bilevel non-capacitated location: a leader first decides which facilities to open and sets service prices taking competing offers into account; then, customers make individual decisions minimizing individual costs that include access charges in the spirit of Hotelling. Both leader and customers are assumed to be risk-neutral. For non-metric costs (i.e., when access costs do not satisfy the triangle inequality), the problem is NP-hard even if facilities can be opened at no fixed cost. We describe an algorithm for solving the Euclidean 1-dimensional case (i.e., with access cost defined by the Euclidean norm on a line) with fixed opening costs and a single competing facility.
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One of the main issues in the glass industry is the minimization of the trim loss generated when cutting large parts (stocks) into small items. In our application stocks are produced in the plant. Many distinct stock sizes are feasible,... more
One of the main issues in the glass industry is the minimization of the trim loss generated when cutting large parts (stocks) into small items. In our application stocks are produced in the plant. Many distinct stock sizes are feasible, and technical constraints limit the variety of cutting patterns to those producing a single type of item per stock. Consequently, the focus is not on seeking an optimal subset of cutting patterns, but rather on choosing an optimal subset of a limited number of stock sizes. In this paper we discuss a 0-1 linear programming formulation for this problem based on a p-median model. Tested on data from the field, the formulation shows an impressive reduction of the trim loss produced in the present plant operation and definitely outperforms traditional exact approaches in terms of computation time.
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This paper describes the design of an Internet of Things (IoT) system for building evacuation. There are two main design decisions for such systems: i) specifying the platform on which the IoT intelligent components should be located; and... more
This paper describes the design of an Internet of Things (IoT) system for building evacuation. There are two main design decisions for such systems: i) specifying the platform on which the IoT intelligent components should be located; and ii) establishing the level of collaboration among the components. For safety-critical systems, such as evacuation, real-time performance and evacuation time are critical. The approach aims to minimize computational and evacuation delays and uses Queuing Network (QN) models. The approach was tested, by computer simulation, on a real exhibition venue in Alan Turing Building, Italy, that has 34 sets of IoT sensors and actuators. Experiments were performed that tested the effect of segmenting the physical space into different sized virtual cubes. Experiments were also conducted concerning the distribution of the software architecture. The results show that using centralized architectural pattern with a segmentation of the space into large cubes is the ...
The paper describes models for scheduling the patterns that form a solution of a cutting stock problem. We highlight the problem of providing the required final products with the necessary items obtained from the cut, choosing which... more
The paper describes models for scheduling the patterns that form a solution of a cutting stock problem. We highlight the problem of providing the required final products with the necessary items obtained from the cut, choosing which pattern feeds which lot of parts. This problem can be solved prior to schedule cuts, or in an integrated way. We present integer programming models for both approaches.
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ABSTRACT Two NP-complete unweighted graph partitioning problems are considered: Simple Max Partitioning (SMP) and Uniform Graph Partitioning (UGP). For both problems, polynomial-time algorithms are available for special classes of graphs.... more
ABSTRACT Two NP-complete unweighted graph partitioning problems are considered: Simple Max Partitioning (SMP) and Uniform Graph Partitioning (UGP). For both problems, polynomial-time algorithms are available for special classes of graphs. In the present paper, the class of line-graphs is considered and a polynomial algorithm is proposed to solve both UGP and SMP in this class.