Crowding-measure-based multiobjective evolutionary algorithm for job shop scheduling

被引：37

作者：

Lei, Deming ^{[1
]}

Wu, Zhiming ^{[1
]}

机构：

[1] Shanghai Jiao Tong Univ, Inst Automat, Shanghai, Peoples R China

来源：

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY | 2006年 / 30卷 / 1-2期

关键词：

crowding measure; job shop scheduling; multiobjective evolutionary algorithm;

D O I：

10.1007/s00170-005-0029-6

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Multiobjective evolutionary algorithm (MOEA) has attracted much attention in the past decade; however, the application of MOEA to practical problems such as job shop scheduling is seldom considered. In this paper, crowding-measure-based multiobjective evolutionary algorithm (CMOEA) is first designed, which makes use of the crowding measure to adjust the external population and assign different fitness for individuals; then CMOEA is applied to job shop scheduling to minimize makespan and the total tardiness of jobs. Finally, the comparison between CMOEA and SPEA demonstrates that CMOEA performs well in job shop scheduling.

引用

页码：112 / 117

页数：6

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