An iterated local search for the multi-objective permutation flowshop scheduling problem with sequence-dependent setup times

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• 作者：Jianyou Xu^a ; ^{xujianyou@mail.neu.edu.cn} ; ^{zhyouxu@163.com} ; Chin-Chia Wu^b ; Yunqiang Yin^c ; Win-Chin Lin^b
• 关键词：Iterated local search ; Multi-objective optimization ; Permutation flowshop scheduling with sequence-dependent setup times
• 刊名：Applied Soft Computing
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：52
• 期：Complete
• 页码：39-47
• 全文大小：1874 K
• 卷排序：52

文摘

The multiple objectives and the sequence-dependent setup times are considered in the permutation flowshop scheduling problem. The extension of conventional single-objective iterated local search (ILS) to solve multi-objective combinatorial optimization problem. A Pareto based variable depth search is designed to act as the multi-objective local search phase in the multi-objective ILS. The experimental results on some benchmark problems show that the proposed multi-objective ILS outperforms several powerful multi-objective evolutionary algorithms in the literature. A multi-objective iterated local search is proposed.