Discrete Differential Evolutionary Algorithm for Job-Shop Scheduling Problem with Minimizing Total Weighted Tardiness

被引:0
作者
Ye, Furong [1 ]
You, Zhen [1 ]
Zhang, Defu [1 ]
Leung, Stephen C. H. [2 ]
机构
[1] Xiamen Univ, Dept Comp Sci, Xiamen, Peoples R China
[2] Univ Hong Kong, Fac Engn, Hong Kong, Hong Kong, Peoples R China
来源
2016 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC) | 2016年
关键词
Differential Evolutionary Algorithm; Job-Shop Scheduling Problem; Local Search; TABU SEARCH;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In the modern manufacturing and operations management, on-time delivery is a critical factor towards realizing customer satisfaction. This paper focuses on job-shop scheduling problem to minimize total weighted tardiness and proposes a discrete differential evolution algorithm for this problem. In order to improve the search ability and efficiency, this paper hybrids the local search which is based on the scheduling critical path theory, and develops a migration operation based on the population diversity theory to jump out of local optimum. Computational results on benchmark instances from the literatures show that the proposed algorithm can compete with the existing algorithms.
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页码:56 / 62
页数:7
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