Ant Colony Optimization approach for Job-shop Scheduling Problem

被引:0
|
作者
Zhang, Haipeng [1 ]
Gen, Mitsuo [1 ]
Fujimura, Shigeru [1 ]
Kim, Kwan Woo [1 ]
机构
[1] Waseda Univ, Grad Sch Informat Prod & Syst, Tokyo, Japan
关键词
Job-shop Scheduling Problem; Ant Colony Optimization; Meta-heuristic Method; SPT; LPTI SRT; LRT; LRM;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Ant Colony Optimization (ACO) is recently proposed as one of meta-heuristic methods for solving, hard combinatorial optimization problems.,,Job-shop Scheduling Problem (JSP) is to determine the, operation sequences on the machines for minimizing a makespan, and also has been confirmed as one of NP-hard problems. In this paper, an ACO approach for solving JSP is presented. We propose hybrid ACO that is combined other heuristic method to find good solution. The traditional heuristic methods include shortest processing time (SPT), longest processing time (LPT), shortest remaining time (SRT), longest remaining time (LRT), longest remaining time excluding the operation under consideration (LRM) for assigning priorities to the unscheduled operations is defined. Some numerical examples are demonstrated to show the performance of JSP using hybrid ACO.
引用
收藏
页码:426 / 431
页数:6
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