Survey on genetic algorithms for solving flexible job-shop scheduling problem

被引：0
|
作者：
Huang X. [1 ]
Chen S. [1 ]
Zhou T. [1 ]
Sun Y. [1 ]
机构：
[1] Faculty of Economics and Management, Dalian University of Technology, Dalian
来源：
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2022年 / 28卷 / 02期
关键词：
Chromosome representation; Flexible job-shop scheduling problem; Genetic algorithms; Genetic operation;
D O I：
10.13196/j.cims.2022.02.018
中图分类号：
学科分类号：
摘要：
Flexible Job-Shop Scheduling Problem (FJSP) is an important scheduling problem with extensive applications. As one of the most popular methods for solving FJSP, Genetic algorithms (GAs) have attracted significant attentions of a number of researchers. A survey of recent works on GAs for solving FJSP was given, especially five main chromosome representations and relevant crossover and mutation operators in GAs. Then seven evaluation criteria including encoding feasibility, mapping relation, memory space, decoding complexity, encoding completeness, the complexity of genetic operation and the diversity of genetic operation were proposed to evaluate the five chromosome representations. © 2022, Editorial Department of CIMS. All right reserved.
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页码：536 / 551
页数：15
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