• Journal of Korean Institute of Industrial Engineers
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• v.35 no.4
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• pp.218-225
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• 2009

This paper considers a parallel-machine scheduling problem with job release times and sequence-dependent setup times. The objective of this problem is to determine the allocation policy of jobs and the scheduling policy of machines so as to minimize the weighted sum of setup times, delay times, and tardy times. A mathematical model for optimal solution is derived and a meta heuristic algorithm based on the improved ant colony system is proposed in this paper. The performance of the meta heuristic algorithm is evaluated through compare with optimal solutions using randomly generated several examples.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.12 no.19
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• pp.79-88
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• 1989

This characteristics of process industries are high capital intensity, relatively long and sequence dependent setup times, and extremely limited capacity resources. The lot sizing, sequencing and limited capacity resources factors must he considered for production scheduling in these industries. This paper presents a mixed integer programming model for production scheduling. The economic trade offs between capacitated lot sizing flow shop scheduling and sequence dependent setup times also be compared with SMITH-DANIELS's model. As a results, it is shown that this paper has lower total cost, more efficient throughput than SMITH-DANIELS's model.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.3
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• pp.339-348
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• 2011

Reconfigurable manufacturing system (RMS), alternatively called changeable manufacturing, is a new manufacturing paradigm designed for rapid change in hardware and software components in order to quickly adjust production capacity and functionality in response to sudden changes in market or in regulatory requirements. Although there has been much progress in hardware components during the last decade, not much work has been done on operational issues of RMS. As one of starting studies on the operational issues, we suggest a framework for the system setup and scheduling problems to cope with the reconfigurability of RMS. System setup, which includes batching, part grouping, and loading, are concerned with the pre-arrangement of parts and tools before the system begins to process, and scheduling is the problem of allocating manufacturing resources over time to perform the operations specified by system setup. The framework consists of 8 scenarios classified by three major factors: order arrival process, part selection process, and tool magazine capacity. Each of the scenarios is explained with its subproblems and their interrelationships.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.2
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• pp.125-137
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• 2010

This study focuses on the problem of scheduling wafer lots of several product families in the deposition workstation in a semiconductor wafer fabrication facility. There are multiple identical parallel machines in the deposition workstation, and two types of setups, record-dependent setup and family setup, may be required at the deposition machines. A record-dependent setup is needed to find optimal operational conditions for a wafer lot on a machine, and a family setup is needed between processings of different families. We suggest two-phase heuristic algorithms in which a priority-rule-based scheduling algorithm is used to generate an initial schedule in the first phase and the schedule is improved in the second phase. Results of computational tests on randomly generated test problems show that the suggested algorithms outperform a scheduling method used in a real manufacturing system in terms of the sum of weighted flowtimes of the wafer lots.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.17 no.31
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• pp.115-123
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• 1994

Group scheduling, which is a kind of operations scheduling based on the GT concept is analyzed in a multi-stage manufacturing system. The purpose of this research is to develop and evaluate a heuristic algorithm for determining gro up sequence and job sequence within each group to minimize a complex cost function, i.e. the sum of the total pe-nalty cost for tardiness and the total holding cost for flow time, in a multi-stage manufacturing system with group setup time dependent upon group sequence. A heuristic algorithm for group sc heduling is developed, and a numerical example is illustrated. For the evaluation of the pro-posed heuristic algorithm, the heuristic solution of each of 63 problems is compared with that of random scheduling. The result shows that the proposed heuristic algorithm provides better solution in light of the proposed cost function.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.13 no.21
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• pp.91-100
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• 1990

This paper is concerned with the development of optimal algorithms for multi-stage flowshop scheduling problems with sequence dependent setup times. In the previous researches the setup time of a job is considered to be able to begin at the earliest opportunity given a particular sequence at the start of operations. In this paper the setup time of a job is considered to be able to begin only at the completion of that job on the previous machine to reflect the effects of the setup time to the performance measure of sequence dependent setup time flowshop scheduling. The results of the study consist of two areas; first, a general integer programming(IP) model is formulated and a nixed integer linear programming(MILP) model is also formulated by introducing a new binary variable. Second a depth-first branch and bound algorithm is developed. To reduce the computational burdens we use the best heuristic schedule developed by Choi(1989) as the first trial. The experiments for developed algorithm are designed for a 4$\times$3$\times$3 factorial design with 360 observations. The experimental factors are PS(ratio of processing time to setup time), M(number of machines), N(number of jobs).

• Journal of Korean Institute of Industrial Engineers
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• v.12 no.2
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• pp.33-44
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• 1986

This research is concerned with group scheduling problems in multi-stage manufacturing system with dependent setup time. The objective of the research is to develop and evaluate a heuristic algorithm for determining group sequence and job sequence within each group to minimize total tardiness in multi-stage manufacturing systems with sequence dependent group setup time. The group scheduling heuristic algorithm is developed and evaluated by comparisons with twenty-seven problems with the known optimum solutions and 144,000 random schedules of a large variety problems. The results indicate that the proposed heuristic algorithm gets the same optimum solutions for the problems and also provides the good solutions in comparison with the random schedules of the large variety problems. A numerical example is given to illustrate the heuristic algorithm.

• Journal of the Korea Society of Computer and Information
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• v.19 no.6
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• pp.101-108
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• 2014

The parallel machine scheduling is to schedule each job to exactly one parallel machine so that the total completion time is minimized. It is used in various manufacturing system areas such as steel industries, semiconductor manufacturing and plastic industries. Each job has a setup phase and a processing phase. A removal phase is needed in some application areas. A processing phase is performed by a parallel machine alone while a setup phase and a removal phase are performed by both a server and a parallel machine simultaneously. Most of previous researches used a single server and considered only a setup phase and a processing phase. If a single server is used for scheduling, the bottleneck in the server increases the total completion time. Even though the number of parallel machines is increased, the total completion time is not reduced significantly. In this paper, we have proposed an efficient algorithm for the parallel machine scheduling using multiple servers and considering setup, processing and removal phases. We also have investigated experimentally how the number of servers and the number of parallel machines affect the total completion time.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.3
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• pp.305-312
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• 2014

This research deals with a problem that minimizes makespan in a non-identical 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 big-size problems in a reasonable computational time. To assess the performance of the algorithms, we conduct a computational experiment, from which we found the heuristic algorithms show different performances as the problem characteristics are changed and the simple heuristics show better performances than genetic algorithm based heuristics for the case when the numbers of jobs and/or machines are large.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.105-106
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• 2010