Embedding ant system in genetic algorithm for re-entrant hybrid flow shop scheduling problems with time window constraints

被引：0
作者：
Chettha Chamnanlor
Kanchana Sethanan
Mitsuo Gen
Chen-Fu Chien
机构：
[1] Khon Kaen University,Department of Industrial Engineering, Faculty of Engineering
[2] Tokyo University of Science,Department of Industrial Engineering and Engineering Management
[3] Fuzzy Logic Systems Institute,undefined
[4] National Tsing Hua University,undefined
来源：
Journal of Intelligent Manufacturing | 2017年 / 28卷
关键词：
Reentrant flexible flow shop; Time window; Hybrid genetic algorithm; Ant colony optimization; Local search;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper focuses on minimizing the makespan for a reentrant hybrid flow shop scheduling problem with time window constraints (RHFSTW), which is often found in manufacturing systems producing the slider part of hard-disk drive products, in which production needs to be monitored to ensure high quality. For this reason, production time control is required from the starting-time-window stage to the ending-time-window stage. Because of the complexity of the RHFSTW problem, in this paper, genetic algorithm hybridized ant colony optimization (GACO) is proposed to be used as a support tool for scheduling. The results show that the GACO can solve problems optimally with reasonable computational effort.
引用
收藏
页码：1915 / 1931
页数：16
相关论文
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