Journal of the Korean Operations Research and Management Science Society (한국경영과학회지)

The Korean Operations Research and Management Science Society (한국경영과학회)
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A Hybrid Genetic Algorithm for Job Shop Scheduling

Job Shop 일정계획을 위한 혼합 유전 알고리즘

  • 박병주 (동아대학교 에이전트 기반 전자상거래팀(BK21)) ;
  • 김현수 (동아대학교 경영정보과학부)
  • Published : 2001.06.01
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Abstract

The job shop scheduling problem is not only NP-hard, but is one of the well known hardest combinatorial optimization problems. The goal of this research is to develop an efficient scheduling method based on hybrid genetic algorithm to address job shop scheduling problem. In this scheduling method, generating method of initial population, new genetic operator, selection method are developed. The scheduling method based on genetic algorithm are tested on standard benchmark job shop scheduling problem. The results were compared with another genetic algorithm0-based scheduling method. Compared to traditional genetic, algorithm, the proposed approach yields significant improvement at a solution.

Keywords

References

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