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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한산업공학회 Industrial Engineering & Management Systems Industrial Engineering & Management Systems 제10권 제2호
- 발행연도
- 2011.6
- 수록면
- 134 - 139 (6page)
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초록· 키워드
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The problem of scheduling in permutation flowshops has been extensively investigated by many researchers. Recently, attempts are being made to consider more than one objective simultaneously and develop algorithms to obtain a set of Pareto-optimal solutions. Varadharajan et al. (2005) presented a multi-objective simulated-annealing algorithm (MOSA) for the problem of permutation-flowshop scheduling with the objectives of minimizing the makespan and the total flowtime of jobs. The MOSA uses two initial sequences obtained using heuristics, and seeks to obtain non-dominated solutions through the implementation of a probability function, which probabilistically selects the objective of minimizing either the makespan or the total flowtime of jobs. In this paper, the same problem of heuristically developing non-dominated sequences is considered. We propose an effective heuristics based on simulated annealing (SA), in which the weighted sum of the makespan and the total flowtime is used. The essences of the heuristics are in selecting the initial sequence, setting the weight and generating a solution in the search process. Using a benchmark problem provided by Taillard (1993), which was used in the MOSA, these conditions are extracted in a large-scale experiment. The non-dominated sets obtained from the existing algorithms and the proposed heuristics are compared. It was found that the proposed heuristics drastically improved the performance of finding the non-dominated frontier.
목차
Abstract
1. INTRODUCTION
2. TWO-OBJECTIVE PERMUTATIONFLOWSHOP SCHEDULING PROBLEM
3. BASICS OF SA IMPLEMENTED IN THE CURRENT STUDY
4. SET OF PARETO-OPTIMAL SOLUTIONS OBTAINED FOR PROBLEM 1 OF SIZE (20×20) GIVEN BY TAILLARD (1993)
5. EFFECT OF THE NEIGHBOURHOOD STRUCTURES
6. EFFECT OF THE INITIAL SEQUENCE AND WEIGHT SETTING
7. PERFORMANCE OF THE PROPOSED SA SEAECH METHOD
8. CONCLUSION
REFERENCES
참고문헌 (6)
참고문헌 신청
Varadharajan, T. K. / 2005 / A multiobjective simulated-annealing algorithm for scheduling in flowshops to minimize the makespan and total flowtime of jobs / European Journal of Operational Research 167:772~795
Taillard, E. / 1993 / Benchmark for basic scheduling problems / European Journal of Operational Research 64:278~285
Ishibuchi, H. / 1998 / A Multi-objective Genetic Local Search Algorithm and Its Application to Flowshop Scheduling / IEEE Transactions on Systems, Man and Cybernetics-Part C: Applications and Reviews 28:392~403
Ulungu, E. L. / 1999 / MOSA Method: A tool for solving multiobjective combinatorial optimization problems / Journal of Multicriteria Decision Analysis 8:221~236
Kirkpatrick, S. / 1983 / Optimization by simulated annealing / Science 220:671~680
Taillard, E. / 1993 / Benchmark for basic scheduling problems / European Journal of Operational Research 64:278~285
Ishibuchi, H. / 1998 / A Multi-objective Genetic Local Search Algorithm and Its Application to Flowshop Scheduling / IEEE Transactions on Systems, Man and Cybernetics-Part C: Applications and Reviews 28:392~403
Ulungu, E. L. / 1999 / MOSA Method: A tool for solving multiobjective combinatorial optimization problems / Journal of Multicriteria Decision Analysis 8:221~236
Kirkpatrick, S. / 1983 / Optimization by simulated annealing / Science 220:671~680
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