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Flexible Job-shop Scheduling with Non-fixed Availability Constraint by Using Hybrid Genetic Algorithm

Flexible Job-shop Scheduling with Non-fixed Availability Constraint by Using Hybrid Genetic Algorithm

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カテゴリ: 部門大会

論文No: MC6-4

グループ名: 【C】平成17年電気学会電子・情報・システム部門大会講演論文集

発行日: 2005/09/06

タイトル(英語): Flexible Job-shop Scheduling with Non-fixed Availability Constraint by Using Hybrid Genetic Algorithm

著者名: Jie Gao(早稲田大学),Mitsuo Gen(早稲田大学)

著者名(英語): Jie Gao(Waseda University),Mitsuo Gen(Waseda University)

キーワード: Flexible job-shop scheduling|maintenance|availability constrain|genetic algorithms|bottleneck shifting

要約(日本語): Most flexible job-shop scheduling models assume that the machines are available all of the time. However, in most realistic situations, machines may be non-available due to maintenance, pre-schedules et al. In this paper, we study the flexible job-shop scheduling problem where each machine is subject to an arbitrary number of non-available maintenance periods during the planning horizon. Each maintenance task is with is a time window in which the completion time of that maintenance task can be moved within. This is, completion times of the maintenance tasks are not fixed, and have to be determined during the scheduling procedure. Our objective is to schedule jobs and maintenance activities so that the makespan of the jobs is minimized under availability constraints. We then propose a hybrid genetic algorithm to solve the problem. In such an approach, we use priority-based representation method and apply advanced genetic manipulations in order to enhance the solution quality. We also propose an innovative decoding procedure that generates active schedules from the chromosomes. Several examples are presented to show the effectiveness and efficiency of the suggested methodology.

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