Ceyda Oguz
Koç University, Industrial Engineering, Faculty Member
This data set includes the test instances and computational results in the paper entitled "A Matheuristic for the Generalized Order Acceptance and Scheduling Problem" (Tarhan and Oğuz).
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In this paper, a single machine, n-job scheduling problem, in which each job has a distinct due date-and equal earliness and tardiness coefficients, is studied. The objective is to determine an optimal schedule to minimize the sum of... more
In this paper, a single machine, n-job scheduling problem, in which each job has a distinct due date-and equal earliness and tardiness coefficients, is studied. The objective is to determine an optimal schedule to minimize the sum of earliness-tardiness penalties. Based on a new theorem for the idle time insertion in the optimal schedule, the paper presents a deterministic algorithm to obtain the upper bound of an optimal schedule. By combining it with an existing lower bound estimation scheme, a fast branch and bound approach for optimal schedule is proposed. Finally, a numerical example is given to illustrate the effectiveness of the new method.
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This data set includes the test instances and computational results in the paper entitled "A Matheuristic for the Generalized Order Acceptance and Scheduling Problem" (Tarhan and Oğuz).
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Abstract In make-to-order production systems, manufacturer can have limited capacity and due to the order delivery time requirements, it may not be possible to accept all orders. This leads to the order acceptance and scheduling problem... more
Abstract In make-to-order production systems, manufacturer can have limited capacity and due to the order delivery time requirements, it may not be possible to accept all orders. This leads to the order acceptance and scheduling problem with release times and sequence dependent setup times that determines which orders to accept and how to schedule them simultaneously to maximize the revenue (GOAS). The aim of this study is to develop an effective and efficient solution methodology for the GOAS problem. To achieve this aim, we develop a mixed integer linear programming model, a constraint programming model, and a matheuristic algorithm that consists of a time-bucket based mixed integer linear programming model, a variable neighborhood search algorithm and a tabu search algorithm. Computational results show that the proposed matheuristic outperforms both the proposed exact models and previous state-of-the-art algorithms developed for the GOAS problem. The boundary of optimally solved instance size is pushed further and near optimal solutions are obtained in reasonable time for instances falling beyond this boundary.
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Evolutionary methods of protein engineering such as phage display have revolutionized drug design and the means of studying molecular binding. In order to obtain the highest experimental efficiency, the distributions of constructed... more
Evolutionary methods of protein engineering such as phage display have revolutionized drug design and the means of studying molecular binding. In order to obtain the highest experimental efficiency, the distributions of constructed combinatorial libraries should be carefully adjusted. The presented approach takes into account diversity–completeness trade–off and tries to maximize the number of new amino acid sequences generated in each cycle of the experiment. In the paper, the mathematical model is introduced and the parallel genetic algorithm for the defined optimization problem is described. Its implementation on the SunFire 6800 computer proves a high efficiency of the proposed approach.
Research Interests: Mathematics, Computer Science, Distributed Computing, Combinatorial Optimization, Mathematical Programming, and 15 moreModeling, Algorithm, Genetic Algorithm, Protein Engineering, Optimization Problem, parallel Genetic algorithm, Drug Design, Phage display, Display, Evolutionary Algorithm, Mathematical Model, Parallel Algorithm, Amino Acid Profile, Amino Acid Sequence, and High Efficiency
Research Interests: Computer Science, Distributed Computing, Parallel Computing, Computer Vision, Image Processing, and 13 moreComputer Software, Multiprocessor Scheduling, Job Scheduling, CEE, Real Time Application, Heuristic, Lower Bound, Parallel Computer, Task Scheduling, Electrical And Electronic Engineering, Multiprocessing, Heuristic algorithm, and Computers and Electrical Engineering
ABSTRACT This paper studies a non-preemptive two-stage flowshop scheduling problem to minimize the earliness and tardiness under the environment of a common due window. The window size and the window location are considered to be given... more
ABSTRACT This paper studies a non-preemptive two-stage flowshop scheduling problem to minimize the earliness and tardiness under the environment of a common due window. The window size and the window location are considered to be given parameters. The just-in-time problem exists naturally and has many practical applications. The problem is shown to be NP-complete in the strong sense. We develop a branch and bound algorithm and a heuristic to solve the problem. We conduct the computational experiments to test the performances of the algorithms. A strong lower bound is derived for the branch and bound algorithm that can efficiently solve 15 jobs problem for about . The heuristic is shown to be efficient and effective, which can solve the problem of 150 jobs for about and provide near-optimal solution. We justify that the heuristic is an excellent solution approach for large problem instances. We also show that four special cases are either polynomial solvable or NP-complete in the ordinary sense.
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In the paper, the flow-shop scheduling problem with parallel machines at each stage (machine center) is studied. For each job its release and due date as well as a processing time for its each operation are given. The scheduling criterion... more
In the paper, the flow-shop scheduling problem with parallel machines at each stage (machine center) is studied. For each job its release and due date as well as a processing time for its each operation are given. The scheduling criterion consists of three parts: the total weighted ...
Research Interests: Computer Science, Operations Research, Tabu Search, Simulated Annealing, Scheduling, and 12 moreFlow Shop Scheduling, Multidisciplinary, Production economics, Metaheuristic, Mathematical Optimization, Job shop scheduling, Tardiness, Flow shop, Parallel Machines, Approximate Algorithm, Waiting Time, and LINEAR PROGRAM
2000-2001 > Academic research: refereed > Refereed conference pape
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ABSTRACT The berth allocation problem is to allocate space along the quayside to incoming ships at a container terminal in order to minimize some objective function. We consider minimization of total costs for waiting and handling as well... more
ABSTRACT The berth allocation problem is to allocate space along the quayside to incoming ships at a container terminal in order to minimize some objective function. We consider minimization of total costs for waiting and handling as well as earliness or tardiness of completion, for all ships. We assume ships can arrive at any given time, i.e., before or after the berths become available. The resulting problem, which subsumes several previous ones, is expressed as a linear mixed 0–1 program. As it turns out to be too time-consuming for exact solution of instances of realistic size, a Variable Neighborhood Search (VNS) heuristic is proposed, and compared with Multi-Start (MS), a Genetic Search algorithm (GA) and a Memetic Search algorithm (MA). VNS provides optimal solutions for all instances solved to optimality in a previous paper of the first two authors and outperforms MS, MA and GA on large instances.
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2003-2004 > Academic research: refereed > Refereed conference pape
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2003-2004 > Academic research: refereed > Refereed conference pape
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Research Interests: Applied Mathematics, Computer Science, Computational Complexity Theory, Parallel Computing, Computational Complexity, and 8 moreOperations Research, Pure Mathematics, Multiprocessor Scheduling, Scheduling Theory, Discrete Optimization, Numerical Analysis and Computational Mathematics, Multiprocessing, and Polynomial Time
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Multi-layer multiprocessor systems are generally employed in real-time applications such as robotics and computer vision. The authors developed three efficient heuristic scheduling algorithms for such systems. In their model, they... more
Multi-layer multiprocessor systems are generally employed in real-time applications such as robotics and computer vision. The authors developed three efficient heuristic scheduling algorithms for such systems. In their model, they considered scheduling multiprocessor tasks with arbitrary processing times and arbitrary processor requirements in a two-stage hybrid flow-shop to minimize makespan. They also derived an effective lower bound for the problem.
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Page 351. Job Scheduling in a Multi-layer Vision System M. Fikret Ercan1, Ceyda Oguz2, and Yu-Fai Fung1 1 Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong SAR {eefikret, eeyffung} Qee. polyu. edu. ...
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Research Interests: Computer Science, Parallel Computing, Flow Shop Scheduling, Genetic Algorithm, Optimal mine design and scheduling, and 10 moreparallel Genetic algorithm, Multiprocessor Scheduling, Job shop scheduling, Schedule, Parallel Computer, Multiprocessing, Parallel Architecture, Machine Scheduling, Optimal scheduling, and Springer Ebooks
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Abstract This paper addresses an extended version of the generalized order acceptance and scheduling problem by including the logistics aspects into the production scheduling decisions. While order acceptance and scheduling feature of the... more
Abstract This paper addresses an extended version of the generalized order acceptance and scheduling problem by including the logistics aspects into the production scheduling decisions. While order acceptance and scheduling feature of the problem includes the joint decision of which orders to accept and how to schedule them due to the limited capacity in production environment and due to the order delivery time requirements for the customers, logistics aspect of the problem entails the decision of how to batch the accepted orders for the delivery in conjunction with the production scheduling. The objective is to maximize the net revenue in line with the literature of order acceptance and scheduling problem. We first present a mixed integer linear programming and a constraint programming model for this problem. To tackle large size problem instances in which these models fail, we propose an iterated local search algorithm using a new local search scheme. To evaluate the performance of the proposed local search scheme, a variant of this algorithm is developed which replaces the relevant scheme with tabu search. Computational results show that the proposed models achieve small optimality gaps for the small size problems, but their performances deteriorate significantly as the problem size enlarges. For the large size problem instances, the iterated local search algorithm using the proposed local search scheme achieves smaller optimality gaps compared to the one with the tabu search algorithm.
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This article considers minimizing the makespan in a two-stage flowshop scheduling problem with a common second-stage machine. After introducing the problem, we show that it is NP-hard and give two special cases which are polynomially... more
This article considers minimizing the makespan in a two-stage flowshop scheduling problem with a common second-stage machine. After introducing the problem, we show that it is NP-hard and give two special cases which are polynomially solvable. Next, we propose a heuristic algorithm and analyze its worst-case error bound. We then develop some lower bounds. Finally, we perform some computational experiments
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ABSTRACT We study several single-machine non-preemptive scheduling problems to minimize the sum of weighted earliness–tardiness, weighted number of early and tardy jobs, common due window location, and flowtime penalties. We allow the due... more
ABSTRACT We study several single-machine non-preemptive scheduling problems to minimize the sum of weighted earliness–tardiness, weighted number of early and tardy jobs, common due window location, and flowtime penalties. We allow the due window location to be either a decision variable or a given parameter. We assume that the due window location has a tolerance and the window size is a given parameter. We further make the assumption that the ratios of the job processing times to the earliness–tardiness weights are agreeable for the first problem. We propose pseudo-polynomial dynamic programming algorithms to optimally solve the problems. We also provide polynomial time algorithms for several special cases.Scope and purpose The widespread use of Just-In-Time philosophy in manufacturing to eliminate inventories leads to a new class of scheduling problems in which the earliness and/or number of early jobs are penalized as well as the tardiness and/or tardy jobs. In this type of environments, the jobs are sometimes associated with a period of time within which they incur no penalty since the customers will generally allow a time interval for the delivery of the products. This time period is called a due window. There are a variety of applications with due windows in factory automation, production maintenance, and so on. In this paper, we consider the common due window problems to minimize the weighted earliness–tardiness, weighted number of early–tardy jobs and weighted flowtime on a single machine. The main contributions of this paper are identifying the computational complexity of the problems, developing dynamic programming algorithms to optimally solve them, and providing efficient and exact polynomial algorithms for the special cases.
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Research Interests: Psychology, Social Psychology, Job Satisfaction, China, Gender Discrimination, and 12 moreSexual Harassment, Cross-Cultural Comparison, Vocational, Business and Management, Legislation, United States, Cross cultural studies, Sex Discrimination, Mainland China, Harassment, Affective Commitment, and Labor Turnover
The paper considers the hybrid flow-shop scheduling problem with multiprocessor tasks. Motivated by the computational complexity of the problem, we propose a memetic algorithm for this problem in the paper. We first describe the... more
The paper considers the hybrid flow-shop scheduling problem with multiprocessor tasks. Motivated by the computational complexity of the problem, we propose a memetic algorithm for this problem in the paper. We first describe the implementation details of a genetic algorithm, which is used in the memetic algorithm. We then propose a constraint programming based branch-and-bound algorithm to be employed as
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Predictive performance of machine learning algorithms on related problems can be improved using multitask learning approaches. Rather than performing survival analysis on each data set to predict survival times of cancer patients, we... more
Predictive performance of machine learning algorithms on related problems can be improved using multitask learning approaches. Rather than performing survival analysis on each data set to predict survival times of cancer patients, we developed a novel multitask approach based on multiple kernel learning (MKL). Our multitask MKL algorithm both works on multiple cancer data sets and integrates cancer-related pathways/gene sets into survival analysis. We tested our algorithm, which is named as Path2MSurv, on the Cancer Genome Atlas data sets analyzing gene expression profiles of 7,655 patients from 20 cancer types together with cancer-specific pathway/gene set collections. Path2MSurv obtained better or comparable predictive performance when benchmarked against random survival forest, survival support vector machine, and single-task variant of our algorithm. Path2MSurv has the ability to identify key pathways/gene sets in predicting survival times of patients from different cancer types.
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Abstract This paper addresses an extended version of the generalized order acceptance and scheduling problem by including the logistics aspects into the production scheduling decisions. While order acceptance and scheduling feature of the... more
Abstract This paper addresses an extended version of the generalized order acceptance and scheduling problem by including the logistics aspects into the production scheduling decisions. While order acceptance and scheduling feature of the problem includes the joint decision of which orders to accept and how to schedule them due to the limited capacity in production environment and due to the order delivery time requirements for the customers, logistics aspect of the problem entails the decision of how to batch the accepted orders for the delivery in conjunction with the production scheduling. The objective is to maximize the net revenue in line with the literature of order acceptance and scheduling problem. We first present a mixed integer linear programming and a constraint programming model for this problem. To tackle large size problem instances in which these models fail, we propose an iterated local search algorithm using a new local search scheme. To evaluate the performance of the proposed local search scheme, a variant of this algorithm is developed which replaces the relevant scheme with tabu search. Computational results show that the proposed models achieve small optimality gaps for the small size problems, but their performances deteriorate significantly as the problem size enlarges. For the large size problem instances, the iterated local search algorithm using the proposed local search scheme achieves smaller optimality gaps compared to the one with the tabu search algorithm.
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A constraint programming based branch-and-bound algorithm is embedded into a memetic algorithm to solve multiprocessor task scheduling problem in hybrid flow-shop environments. Both meth- ods are able to solve the problem by themselves... more
A constraint programming based branch-and-bound algorithm is embedded into a memetic algorithm to solve multiprocessor task scheduling problem in hybrid flow-shop environments. Both meth- ods are able to solve the problem by themselves but the combination of the two allows to solve larger problem in a shorter amount of time. Computational experiments are conducted on a large set of in- stances and the resulting memetic algorithm gives the best results so far.
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ABSTRACT
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This data set includes the test instances and computational results in the paper entitled as "Generalized Order Acceptance and Scheduling Problem with Batch Delivery: Models and Metaheuristics" (Tarhan and Oğuz) and to be... more
This data set includes the test instances and computational results in the paper entitled as "Generalized Order Acceptance and Scheduling Problem with Batch Delivery: Models and Metaheuristics" (Tarhan and Oğuz) and to be published in Computers and Operations Research with the following doi: https://doi.org/10.1016/j.cor.2021.105414.
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Port terminals processing large cargo vessels play an important role in bulk material supply chains. This paper addresses the question of how to allocate vessels to a location on a berth and the sequence in which the vessels should be... more
Port terminals processing large cargo vessels play an important role in bulk material supply chains. This paper addresses the question of how to allocate vessels to a location on a berth and the sequence in which the vessels should be processed in order to minimize delays. An important consideration in the berth allocation is the presence of tidal constraints that limit the departure of fully loaded vessels from the terminal. We show how the berth allocation problem can be modeled as an integer program and discuss a number of ways to tighten the formulation in order to make it computationally tractable. In addition, a two-phase method is developed for solving these problems. Empirical computational results demonstrate an order of magnitude improvement in performance. The two new approaches can solve significantly larger instances, producing faster solutions for small instances and much tighter bounds for large instances.
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ABSTRACT We consider job scheduling in a multi-layer vision system. We model this problem as scheduling a number of jobs, which are made of multiprocessor tasks, with arbitrary processing times and arbitrary processor requirements in a... more
ABSTRACT We consider job scheduling in a multi-layer vision system. We model this problem as scheduling a number of jobs, which are made of multiprocessor tasks, with arbitrary processing times and arbitrary processor requirements in a two-layer system. Our objective is to minimize the makespan. We have developed several heuristic algorithms that include simple sequencing and scheduling rules. The computational experiments show that three of these heuristic algorithms are efficient.
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Hybrid flow-shop problems and problems with multiprocessor task systems have remained subject of intensive research over several years. Hybrid flow-shop problems overcome one of the limitations of the classical flow-shop model by allowing... more
Hybrid flow-shop problems and problems with multiprocessor task systems have remained subject of intensive research over several years. Hybrid flow-shop problems overcome one of the limitations of the classical flow-shop model by allowing parallel processors at each stage of task ...
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The hybrid flow-shop scheduling problem with multiprocessor tasks finds its applications in real-time machine-vision systems among others. Motivated by this application and the computational complexity of the problem, we propose a genetic... more
The hybrid flow-shop scheduling problem with multiprocessor tasks finds its applications in real-time machine-vision systems among others. Motivated by this application and the computational complexity of the problem, we propose a genetic algorithm in this paper. We first describe the implementation details, which include a new crossover operator. We then perform a preliminary test to set the best values of
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The paper considers the hybrid flow-shop scheduling problem with multiprocessor tasks. Motivated by the computational complexity of the problem, we propose a memetic algorithm for this problem in the paper. We first describe the... more
The paper considers the hybrid flow-shop scheduling problem with multiprocessor tasks. Motivated by the computational complexity of the problem, we propose a memetic algorithm for this problem in the paper. We first describe the implementation details of a genetic algorithm, which is used in the memetic algorithm. We then propose a constraint programming based branch-and-bound algorithm to be employed as
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Intermodal transportation (IMT) combines two or more different modes of transportation without changing the packaging of the freight transported in order to minimize the transportation cost and to utilize the benefits of modes that are... more
Intermodal transportation (IMT) combines two or more different modes of transportation without changing the packaging of the freight transported in order to minimize the transportation cost and to utilize the benefits of modes that are used. One of the most common intermodal freight transportation systems is the Rolling Highway (Ro-La), where a special train system is used to carry highway vehicles on railway cars. This paper reviews IMT and proposes a system in which the facility layout problems are solved simultaneously with the scheduling problems arising in Ro-La transportation. In this context, the best station layouts are obtained by applying a layout improvement algorithm to several initial layouts with respect to different scoring functions. One of the important questions to answer in the IMT problem pertains to the number of loading and unloading platforms. Using the output of the layout improvement algorithm, the train scheduling model is solved to find the minimum number of platforms in a station, the number of trains, and the departures with the carried trucks and trailers, while scheduling train operations, with the objective of minimizing operation costs. The proposed IMT system is applied to the Marmaray Undersea Railway Tunnel Project with regard to different Ro-La systems, and its effectiveness is discussed.
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... sp.edu.sg 2 Department of Management, The Hong Kong Polytechnic University, Hong KongSAR msceyda@polyu.edu.hk 3 Department of Electrical Eng., The Hong Kong Polytechnic University, Hong Kong SAR eeyffung@polyu.edu.hk ... 62 MF Ercan,... more
... sp.edu.sg 2 Department of Management, The Hong Kong Polytechnic University, Hong KongSAR msceyda@polyu.edu.hk 3 Department of Electrical Eng., The Hong Kong Polytechnic University, Hong Kong SAR eeyffung@polyu.edu.hk ... 62 MF Ercan, C. Oguz, and Y.-F. Fung ...
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Page 351. Job Scheduling in a Multi-layer Vision System M. Fikret Ercan1, Ceyda Oguz2, and Yu-Fai Fung1 1 Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong SAR {eefikret, eeyffung} Qee. polyu. edu. ...
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Machine scheduling problems belong to the most difficult deterministic combinatorial optimization problems. Hence, most scheduling problems are NP-hard and it is impossible to find the optimal schedule in reasonable time. In this paper,... more
Machine scheduling problems belong to the most difficult deterministic combinatorial optimization problems. Hence, most scheduling problems are NP-hard and it is impossible to find the optimal schedule in reasonable time. In this paper, we consider a flow-shop scheduling problem with multi-processor tasks. A parallel genetic algorithm using multithreaded programming technique is developed to obtain a quick but good solution to
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Multi-layer multiprocessor systems are generally employed in real-time applications such as robotics and computer vision. The authors developed three efficient heuristic scheduling algorithms for such systems. In their model, they... more
Multi-layer multiprocessor systems are generally employed in real-time applications such as robotics and computer vision. The authors developed three efficient heuristic scheduling algorithms for such systems. In their model, they considered scheduling multiprocessor tasks with arbitrary processing times and arbitrary processor requirements in a two-stage hybrid flow-shop to minimize makespan. They also derived an effective lower bound for the problem.
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The scheduling problem in a multilayer multiprocessor environment finds its relevance in many industrial and computing applications. In this paper, we present a genetic algorithm for the solution. We describe the implementation details... more
The scheduling problem in a multilayer multiprocessor environment finds its relevance in many industrial and computing applications. In this paper, we present a genetic algorithm for the solution. We describe the implementation details and introduce a new crossover operator. Extensive computational experiments demonstrated that genetic algorithm performs well.
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ABSTRACT This paper is concerned with hybrid flow-shop scheduling problem involving multiprocessor tasks. The hybrid flow-shop problem is a generalization of the classical flow-shop problem by permitting multiple parallel processors at... more
ABSTRACT This paper is concerned with hybrid flow-shop scheduling problem involving multiprocessor tasks. The hybrid flow-shop problem is a generalization of the classical flow-shop problem by permitting multiple parallel processors at each stage of task processing. The multiprocessor tasks, on the other hand, overcome the restriction of the classical scheduling problems by allowing tasks to be processed on more than one processor simultaneously. The hybrid flow-shop is defined by the set M = ..., m} of m processing stages, in which each stage contains a set M i = ..., m i of m i identical processors. There is a given set J = ..., n} of n jobs to be processed in this hybrid flow-shop system. Each job can be viewed as a sequence of m multiprocessor tasks. The i-th task in the sequence has to be processed for p ij time units without preemption by size ij processors of stage i, and can be started only after the completion of the previous task from this sequence. In other words, the i-th task of job j J is defined by its processing time, p ij > 0, and the number of processors required, size ij . For convenience, we will regard the i-th task of job j to be comprised of size ij operations, which must be processed simultaneously at stage i. The remaining parameters of the jobs are as follows: r j - release date of job j, q j - delivery time of job j, t ij - transport time between stage i and i +1ofjob j. To be in line with transport times, we will refer to job release dates and delivery times as t 0j and t mj , respectively. Additionally, there are stage- and sequence-dependent set-up times. s ijk , i 0}, k J , denotes the set-up time between job j and job k at stage i,ands i0k is a set-up time, which occurs before i-th task of job k if it is processed first on...
ABSTRACT This study presents a constraint programming (CP) model for the quay crane scheduling problem (QCSP), which occurs at container terminals, with realistic constraints such as safety margins, travel times and precedence relations.... more
ABSTRACT This study presents a constraint programming (CP) model for the quay crane scheduling problem (QCSP), which occurs at container terminals, with realistic constraints such as safety margins, travel times and precedence relations. Next, QCSP with time windows and integrated crane assignment and scheduling problem, are discussed. The performance of the CP model is compared with that of algorithms presented in QCSP literature. The results of the computational experiments indicate that the CP model is able to produce good results while reducing the computational time, and is a robust and flexible alternative for different types of crane scheduling problems.
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ABSTRACT In this paper we study the single-machine problem 1|chains(l), p j = p|∑ C j in which jobs with constant processing times and generalized precedence constraints in form of chains with constant delays are given. One has to... more
ABSTRACT In this paper we study the single-machine problem 1|chains(l), p j = p|∑ C j in which jobs with constant processing times and generalized precedence constraints in form of chains with constant delays are given. One has to schedule the jobs on a single machine such that all delays between consecutive jobs in a chain are satisfied and the sum of all completion times of the jobs is minimized. We show that this problem is polynomially solvable.
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Drawing on social identity theory (P. J. Burke, 1991) and the current status of women and equal opportunity legislation, the authors tested several factors associated with distress in working women in the People's... more
Drawing on social identity theory (P. J. Burke, 1991) and the current status of women and equal opportunity legislation, the authors tested several factors associated with distress in working women in the People's Republic of China (PRC), Hong Kong, and the United States. Women in Hong Kong experienced significantly greater levels of life stress than PRC and U.S. women. Reports of negative attitudes toward women, gender evaluation, and avoidance coping were greater for Hong Kong and PRC women than for U.S. women. Hong Kong women reported more use of positive/confrontational coping mechanisms. Negative attitudes toward women had an important influence on life stress across regions. Moderator tests resulted in 2 significant findings: The effect of negative attitudes toward women on life stress was stronger for PRC and Hong Kong women, and the relationship between nervous/self-destructive coping and life stress was stronger for U.S. women.
Research Interests: Psychology, Social Identity, Women, China, Hong Kong, and 15 moreSocial Identification, Occupational Health Psychology, Equal Opportunities, Social identity theory, Workplace, Cross-Cultural Comparison, Humans, Business and Management, Legislation, United States, Female, Middle Aged, Occupational, Questionnaires, and Adult
In the paper, the flow-shop scheduling problem with parallel machines at each stage (machine center) is studied. For each job its release and due date as well as a processing time for its each operation are given. The scheduling criterion... more
In the paper, the flow-shop scheduling problem with parallel machines at each stage (machine center) is studied. For each job its release and due date as well as a processing time for its each operation are given. The scheduling criterion consists of three parts: the total weighted ...
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... Using the well-known three-field notation with extensions [8], [12] and [14], we denote thisscheduling problem as F2(Pm 1 ,Pm 2 ) size ij C max . ... A multi-stage flow-shop with identical parallel processors at each stage is usually... more
... Using the well-known three-field notation with extensions [8], [12] and [14], we denote thisscheduling problem as F2(Pm 1 ,Pm 2 ) size ij C max . ... A multi-stage flow-shop with identical parallel processors at each stage is usually referred to as a hybrid flow-shop in the ...
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ABSTRACT In this paper, a Decision Support System is proposed for a Just-In-Time production system. The Decision Support System includes three components: database, model base, and interface. The database contains the predefined... more
ABSTRACT In this paper, a Decision Support System is proposed for a Just-In-Time production system. The Decision Support System includes three components: database, model base, and interface. The database contains the predefined parameters together with the data generated for the considered Just-In-Time production system. In the model base, both deterministic and stochastic aspects of the system are considered. The deterministic system is examined by constructing a linear programming model whereas simulation is used as a tool for the stochastic system. Furthermore, a sensitivity analysis is performed on the Just-In-Time production system with the help of the Decision Support System environment for the unit load size changes under different demand patterns by using the alternative solutions obtained from the model base.
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This article considers minimizing the makespan in a two-stage flowshop scheduling problem with a common second-stage machine. After introducing the problem, we show that it is NP-hard and give two special cases which are polynomially... more
This article considers minimizing the makespan in a two-stage flowshop scheduling problem with a common second-stage machine. After introducing the problem, we show that it is NP-hard and give two special cases which are polynomially solvable. Next, we propose a heuristic algorithm and analyze its worst-case error bound. We then develop some lower bounds. Finally, we perform some computational experiments
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ABSTRACT We study several single-machine non-preemptive scheduling problems to minimize the sum of weighted earliness–tardiness, weighted number of early and tardy jobs, common due window location, and flowtime penalties. We allow the due... more
ABSTRACT We study several single-machine non-preemptive scheduling problems to minimize the sum of weighted earliness–tardiness, weighted number of early and tardy jobs, common due window location, and flowtime penalties. We allow the due window location to be either a decision variable or a given parameter. We assume that the due window location has a tolerance and the window size is a given parameter. We further make the assumption that the ratios of the job processing times to the earliness–tardiness weights are agreeable for the first problem. We propose pseudo-polynomial dynamic programming algorithms to optimally solve the problems. We also provide polynomial time algorithms for several special cases.Scope and purpose The widespread use of Just-In-Time philosophy in manufacturing to eliminate inventories leads to a new class of scheduling problems in which the earliness and/or number of early jobs are penalized as well as the tardiness and/or tardy jobs. In this type of environments, the jobs are sometimes associated with a period of time within which they incur no penalty since the customers will generally allow a time interval for the delivery of the products. This time period is called a due window. There are a variety of applications with due windows in factory automation, production maintenance, and so on. In this paper, we consider the common due window problems to minimize the weighted earliness–tardiness, weighted number of early–tardy jobs and weighted flowtime on a single machine. The main contributions of this paper are identifying the computational complexity of the problems, developing dynamic programming algorithms to optimally solve them, and providing efficient and exact polynomial algorithms for the special cases.
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ABSTRACT In this paper, we developed several efficient heuristic algorithms to schedule unit processing time multiprocessor tasks in a two-stage hybrid flow-shop for minimizing makespan. We also derived two effective lower bounds for the... more
ABSTRACT In this paper, we developed several efficient heuristic algorithms to schedule unit processing time multiprocessor tasks in a two-stage hybrid flow-shop for minimizing makespan. We also derived two effective lower bounds for the problem. Then, we analyzed the average performance of the heuristic algorithms by computing the average relative gap of each heuristic solution from the lower bound. The results of the computational experiment to test the average performance of the proposed heuristic algorithms on a set of randomly generated problems showed that three of the proposed heuristic algorithms perform well.
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... View Within Article. 3. Simulated Annealing. Simulated Annealing (SA) exploits an analogy between the annealing process of metals, that is, the way a metal cools and freezes into a minimum energy crystalline structure, and the search... more
... View Within Article. 3. Simulated Annealing. Simulated Annealing (SA) exploits an analogy between the annealing process of metals, that is, the way a metal cools and freezes into a minimum energy crystalline structure, and the search for a minimum in a more general system. ...
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Abstract In this paper we investigate the use of hyper-heuristic methodologies for predicting DNA sequences. In particular, we utilize Sequencing by Hybridization. We believe that this is the first time that hyper-heuristics have been... more
Abstract In this paper we investigate the use of hyper-heuristic methodologies for predicting DNA sequences. In particular, we utilize Sequencing by Hybridization. We believe that this is the first time that hyper-heuristics have been investigated in this domain. A hyper-heuristic is provided with a set of low-level heuristics and the aim is to decide which heuristic to call at each decision point. We investigate three types of hyper-heuristics. Two of these (simulated annealing and tabu search) draw their inspiration from meta-heuristics. The choice ...
Research Interests:
The management of production and logistics systems in today's fierce competition environment is a difficult task and has become progressively complex. Major changes in products, processes, technologies, and societies bring along... more
The management of production and logistics systems in today's fierce competition environment is a difficult task and has become progressively complex. Major changes in products, processes, technologies, and societies bring along remarkable challenges and increasing market demands. Modelling and optimisation of the complex problems arising in production and logistics systems is of paramount importance in surviving and achieving competitive gains in productivity and quality. In recent years, the advancements in ...