A genetic algorithm for a re-entrant job-shop scheduling problem with sequence-dependent setup times

被引:17
|
作者
Sun, J. U. [1 ]
机构
[1] Hankuk Univ Foreign Studies, Sch Ind & Management Engn, Yonsin Shi 449791, Kyonggi Do, South Korea
关键词
job-shop scheduling; re-entrant work flows; sequence-dependent setup; genetic algorithm; Taguchi method; UP TIMES; TUTORIAL SURVEY; PERFORMANCE; MACHINES; DATES;
D O I
10.1080/03052150802613335
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This article addresses a re-entrant job-shop scheduling problem with sequence-dependent setup times. The disjunctive graph model with the objective of the minimum makespan is used to capture the interactions between machines. On the basis of this representation, two heuristic procedures and a genetic algorithm are proposed to obtain near-optimal solutions for this problem. Also, an experimental design method for determining the various genetic parameters based on the Taguchi approach is presented. A comparative study is conducted to examine the performance of these proposed algorithms and the results show that the genetic algorithm outperforms the other heuristic procedures, which are modified versions of recently published existing methods.
引用
收藏
页码:505 / 520
页数:16
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