An efficient memetic algorithm for solving the job shop scheduling problem

被引:78
作者
Gao, Liang [2 ]
Zhang, Guohui [1 ]
Zhang, Liping [2 ]
Li, Xinyu [2 ]
机构
[1] Zhengzhou Inst Aeronaut Ind Management, Zhengzhou 450015, Peoples R China
[2] Huazhong Univ Sci & Technol, State Key Lab Digital Mfg Equipment & Technol, Wuhan 430074, Peoples R China
基金
中国国家自然科学基金;
关键词
Job shop scheduling; Memetic algorithm; Local search; Neighborhood structure; SHIFTING BOTTLENECK PROCEDURE; HYBRID GENETIC ALGORITHM; SEARCH ALGORITHM;
D O I
10.1016/j.cie.2011.01.003
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The job shop scheduling problem (JSP) is well known as one of the most complicated combinatorial optimization problems, and it is a NP-hard problem. Memetic algorithm (MA) which combines the global search and local search is a hybrid evolutionary algorithm. In this pal er, an efficient MA with a novel local search is proposed to solve the JSP. Within the local search, a systematic change of the neighborhood is carried out to avoid trapping into local optimal. And two neighborhood structures are designed by exchanging and inserting based on the critical path. The objective of minimizing makespan is considered while satisfying a number of hard constraints. The computational results obtained in experiments demonstrate that the efficiency of the proposed MA is significantly superior to the other reported approaches in the literature. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:699 / 705
页数:7
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