Solving Job-Shop Scheduling Problem with Improved Genetic Algorithm

被引：0
|
作者：
Wu, Weijun [1 ]
Yu, Songnian [1 ]
Ding, Wang [1 ]
机构：
[1] Shanghai Univ, Sch Engn & Comp Sci, Shanghai 200072, Peoples R China
来源：
PROCEEDINGS OF 2008 INTERNATIONAL PRE-OLYMPIC CONGRESS ON COMPUTER SCIENCE, VOL II: INFORMATION SCIENCE AND ENGINEERING | 2008年
关键词：
improved genetic algorithm; job-shop scheduling problem; new crossover operator; new mutation operator;
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：
In this paper, we propose a new improved genetic algorithm (IGA) for the job-shop scheduling problems (JSSPs). The proposed method introduces a new crossover operator and a new mutation operator which can inherit characteristics well, maintain the diversity of population, and get better solutions. By applying the proposed method to Fisher and Thompson's 10x10 (FT10x10) and 20x5 (FT20x5) problems, we show the effectiveness.
引用
收藏
页码：348 / 352
页数：5
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