A Hybrid Algorithm for Flexible Job-shop Scheduling Problem

被引：22
|
作者：
Tang, Jianchao [1 ,2 ]
Zhang, Guoji [1 ]
Lin, Binbin [1 ]
Zhang, Bixi [3 ]
机构：
[1] South China Univ Technol, Guangzhou 510641, Guangdong, Peoples R China
[2] South China Normal Univ, Guangzhou 510631, Guangdong, Peoples R China
[3] Guangdong Univ Technol Guangdong, Guangzhou 510006, Guangdong, Peoples R China
来源：
CEIS 2011 | 2011年 / 15卷
基金：
中国国家自然科学基金;
关键词：
Flexible job-shop scheduling problem; Chaos particle swarm optimization; Genetic algorithm; GENETIC ALGORITHM;
D O I：
10.1016/j.proeng.2011.08.689
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
By combining the chaos particle swarm optimization with genetic algorithm, a hybrid algorithm is proposed in this paper. A novel initialization method is proposed based on the improved Kacem assignments scheme. And according to the characteristic of flexible job-shop scheduling problem, genetic operators are presented. Finally, this method is validated on a series of benchmark datasets. Experimental results indicate that this method is efficient and competitive compared to some existing methods. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of [CEIS 2011]
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页数：6
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