Scheduling in FMS Environments by Network-based Hybrid Genetic Algorithm

概要

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Scheduling in flexible manufacturing systems (FMS) must take account the shorter lead-time, multiprocessing environment, the flexibility of alternative workstations with different processing times, and the dynamically changing states. The best scheduling approach described in this paper is to minimize makespan t_M, total flow time t_F, and total tardiness penalty p_T, but in the case of the manufacturing system problems, it is difficult for those traditional optimization techniques to cope with. This paper presents a new flow network-based hybrid genetic algorithm (hGA) approach for generating static schedules in a FMS environment. The proposed method combines with the neighborhood search technique in mutation operation to improve solution of the FMS problem, and to enhance the performance of the genetic search process, we update the change of crossover ration and mutation ration. The numerical experiments show that the proposed flow network-based hGA is both effective and efficient to the FMS problems.
社団法人電子情報通信学会の論文
2003-02-28