A Memetic Algorithm for Solving Flexible Job-shop Scheduling Problems

被引：0
|
作者：
Ma, Wenping [1 ]
Zuo, Yi [1 ]
Zeng, Jiulin [1 ]
Liang, Shuang [1 ]
Jiao, Licheng [1 ]
机构：
[1] Xidian Univ, Key Lab Intelligent Percept & Image Understanding, Minist Educ china, Xian 710071, Peoples R China
来源：
2014 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC) | 2014年
关键词：
flexible job-shop scheduling; memetic algorithm; tabu search; simulated annealing; SEARCH;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The flexible Job-shop Scheduling Problem (FJSP) is an extension of the classical job-shop scheduling problem (JSP). In this paper, a memetic algorithm (MA) for the FJSP is presented. This MA is a hybrid genetic algorithm which explores the search space and two efficient local searchers to exploit information in the search region. An extensive computational study on 49 benchmark problems shows that the algorithm is effective and robust, with respect to other well-known effective algorithms.
引用
收藏
页码：66 / 73
页数：8
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