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Mongkalig, Chatpon,Tabucanon, Mario T.,Hop, Nguyen Van Korean Institute of Industrial Engineers 2005 Industrial Engineeering & Management Systems Vol.4 No.1
This paper presents new scheduling heuristics, namely Mean Progressive Weighted Tardiness Estimator (MPWT) Heuristic Method and modified priority rules with sequence-dependent setup times consideration. These are designed to solve job shop scheduling problems with new performance measures - progressive weighted tardiness penalties. More realistic constraints, which are inter-machine overlapping sequence-dependent setup times, are considered. In real production environments, inter-machine overlapping sequence-dependent setups are significant. Therefore, modified scheduling generation algorithms of active and nondelay schedules for job shop problems with inter-machine overlapping sequence-dependent setup times are proposed in this paper. In addition, new customer-based measures of performance, which are total earliness and progressive weighted tardiness, and total progressive weighted tardiness, are proposed. The objective of the first experiment is to compare the proposed priority rules with the consideration of sequence-dependent setup times and the standard priority rules without setup times consideration. The results indicate that the proposed priority rules with setup times consideration are superior to the standard priority rules without the consideration of setup times. From the second experiment and the third experiment to compare the proposed MPWT heuristic approach with the efficient priority rules with setup times consideration, the MPWT heuristic method is significantly superior to the Batched Apparent Tardiness Cost with Sequence-dependent Setups (BATCS) rule, and other priority rules based on total earliness and progressive weighted tardiness, and total earliness and tardiness.
Common Due-Date Assignment and Scheduling on Parallel Machines with Sequence-DependentSetup Times
Jun-Gyu Kim,Jae-Min Yu,Dong-Ho Lee 한국경영과학회 2013 Management Science and Financial Engineering Vol.19 No.1
This paper considers common due-date assignment and scheduling on parallel machines. The main decisions are: (a) deter-mining the common due-date; (b) allocating jobs to machines; and (c) sequencing the jobs assigned to each machine. The objective is to minimize the sum of the penalties associated with common due-date assignment, earliness and tardiness. As an extension of the existing studies on the problem, we consider sequence-dependent setup times that depend on the type of job just completed and on the job to be processed. The sequence-dependent setups, commonly found in various manufacturing systems, make the problem much more complicated. To represent the problem more clearly, a mixed integer programming model is suggested, and due to the complexity of the problem, two heuristics, one with individual sequence-dependent setup times and the other with aggregated sequence-dependent setup times, are suggested after analyzing the characteristics of the problem. Computational experiments were done on a number of test instances and the results are reported.
Nader A. Al Theeb,Mohammed S. Obeidat,Manar Aljarrah,Theyab A. Alhwiti 대한산업공학회 2019 Industrial Engineeering & Management Systems Vol.18 No.4
A single machine scheduling problem with sequence-dependent setup times and setup costs has a critical role in manufacturing and service sectors to minimize orders delays and costs. This study provides multiple objectives model tosolve the single machine total weighted tardiness and setup costs scheduling problem associated with sequencedependent setup times and sequence-dependent setup costs (MOSTWTSCSD). The objectives are to minimize thetotal weighted tardiness and the total setup costs for all jobs without any certain relationship between the setup timeand the setup cost, as happened in some machines. An alternative heuristic procedure based on discrete particle swarmoptimization (DPSO) is suggested to find representative Pareto front (non-dominated) solutions. Many efficient methods have been used inside the DPSO to improve its performance. Results show that the ability of the suggested solution approach to provide a representative Pareto fronts in reasonable computational efforts compared with anotherheuristic.
작업순서와 기계 의존적인 작업준비시간을 고려한 이종병렬기계의 일정계획을 위한 효과적인 작업할당 방법을 이용한 유전알고리즘
주철민,김병수 대한산업공학회 2012 산업공학 Vol.25 No.3
This paper considers a unrelated parallel machine scheduling problem with ready times, due times and sequence and machine-dependent setup times. The objective of this problem is to determine the allocation of jobs and the scheduling of machines to minimize the total tardy time. A mathematical model for optimal solution is derived. An in-depth analysis of the model shows that it is very complicated and difficult to obtain optimal solutions as the problem size becomes large. Therefore, a genetic algorithm using an effective dispatching method is proposed. The performance of the proposed genetic algorithm is evaluated using several randomly generated examples.
Cheol Min Joo,Byung Soo Kim 대한산업공학회 2012 Industrial Engineeering & Management Systems Vol.11 No.1
This paper considers a non-identical parallel machine scheduling problem with sequence and machine dependent setup times. The objective of this problem is to determine the allocation of jobs and the scheduling of each machine to minimize makespan. A mathematical model for optimal solution is derived. An in-depth analysis of the model shows that it is very complicated and difficult to obtain optimal solutions as the problem size becomes large. Therefore, two meta-heuristics, genetic algorithm (GA) and a new population-based evolutionary meta-heuristic called self-evolution algorithm (SEA), are proposed. The performances of the meta-heuristic algorithms are evaluated through compare with optimal solutions using randomly generated several examples.
주철민,김병수 대한산업공학회 2012 Industrial Engineeering & Management Systems Vol.11 No.1
This paper considers a non-identical parallel machine scheduling problem with sequence and machine dependent setup times. The objective of this problem is to determine the allocation of jobs and the scheduling of each machine to minimize makespan. A mathematical model for optimal solution is derived. An in-depth analysis of the model shows that it is very complicated and difficult to obtain optimal solutions as the problem size becomes large. Therefore, two meta-heuristics, genetic algorithm (GA) and a new population-based evolutionary meta-heuristic called self-evolution algorithm (SEA), are proposed. The performances of the meta-heuristic algorithms are evaluated through compare with optimal solutions using randomly generated several examples.
Joo, Cheol-Min,Kim, Byung-Soo Korean Institute of Industrial Engineers 2012 Industrial Engineeering & Management Systems Vol.11 No.1
This paper considers a non-identical parallel machine scheduling problem with sequence and machine dependent setup times. The objective of this problem is to determine the allocation of jobs and the scheduling of each machine to minimize makespan. A mathematical model for optimal solution is derived. An in-depth analysis of the model shows that it is very complicated and difficult to obtain optimal solutions as the problem size becomes large. Therefore, two meta-heuristics, genetic algorithm (GA) and a new population-based evolutionary meta-heuristic called self-evolution algorithm (SEA), are proposed. The performances of the meta-heuristic algorithms are evaluated through compare with optimal solutions using randomly generated several examples.
Heuristic Algorithms for a Scheduling Problem in a Semiconductor Probing Facility
조성준,방준영 한국산업경영시스템학회 2017 한국산업경영시스템학회 학술대회 Vol.2017 No.추계초록
This research focuses on a scheduling problem in the semiconductor probing facility. Probing facility is composed of identical parallel machines and the parallel machines form three workstations for the tests with different recipes. Each machine can be set to three different tests and sequence-dependent setup times are required between operations due to temperature and probe card loading/unloading. Precedence relationship exists between three tests of each wafer lot. The scheduling problem for the probing facility is a parallel machine scheduling problem with precedence relationship and sequence dependent setup time. We develop heuristic algorithm to minimize makespan for the scheduling problem and numerical experiments are conducted to evaluate the performance.
작업순서 및 기계 의존적인 준비시간을 고려한 제약이 주어진 이종병렬기계의 일정계획에 관한 연구
주철민 ( Cheol Min Joo ) 한국경영공학회 2012 한국경영공학회지 Vol.17 No.3
This paper considers a restricted non-identical parallel machine scheduling problem with sequence and machine dependent setup times. The objective of this problem is to determine the allocation of jobs and the scheduling of machines to minimize the makespan. A mathematical model for optimal solution is derived. An in-depth analysis of the model shows that it is very complicated and difficult to obtain optimal solutions as the problem size becomes large. Therefore, two meta-heuristic algorithms based on ant colony system and genetic algorithm are proposed. The performance of the proposed algorithms are evaluated using randomly generated several examples.