A three-layer chromosome genetic algorithm for multi-cell scheduling with flexible routes and machine sharing

Yanling Feng, Guo Li*, Suresh P. Sethi

*此作品的通讯作者

    科研成果: 期刊稿件文章同行评审

    42 引用 (Scopus)

    摘要

    Alternative machines assignment, machine sharing, and inter-cell movements are very common yet difficult to be solved integratedly in modern dynamic Cellular Manufacturing Systems (CMS). In this paper, we incorporate these issues and consider a dynamic cellular scheduling problem with flexible routes and machine sharing. We employ a mixed integer programming scheduling model to minimize both the makespan and the total workload. To solve this new model, we propose a three-layer chromosome genetic algorithm (TCGA). We first compare the performances of the proposed TCGA with the optimal solution obtained by CPLEX. Computational results show that the TCGA performs well within a reasonable amount of time. We further compare our proposed TCGA with the classic genetic algorithm (GA) and the shortest processing time (SPT) rule through numerical experiments. The results reveal that the TCGA significantly improves the performance and effectively balances the workload of machines.

    源语言英语
    页(从-至)269-283
    页数15
    期刊International Journal of Production Economics
    196
    DOI
    出版状态已出版 - 2月 2018

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