Genetic Algorithm For Open Shop Scheduling Problem

被引：0
|
作者：
Benziani, Yacine [1 ]
Kacem, Imed [2 ]
Laroche, Pierre [2 ]
机构：
[1] Univ North Dakota, Grand Forks, ND 58201 USA
[2] Univ Lorraine, LCOMS Lab, F-57045 Metz, France
来源：
2018 5TH INTERNATIONAL CONFERENCE ON CONTROL, DECISION AND INFORMATION TECHNOLOGIES (CODIT) | 2018年
关键词：
BOUND ALGORITHM; OPTIMIZATION; SEARCH;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we present a genetic algorithm for the open shop scheduling problem. We use a simple and efficient chromosome representation based on the job's occurrence and the fitness function reflect the length of the schedule. The solutions obtained after performing the different operators of the genetic algorithm are always feasible. Heuristic approaches are also developed to generate the initial population and to improve the obtained solutions. The algorithm was implemented and computational results show interesting result.
引用
收藏
页码：935 / 939
页数：5
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