A genetic algorithm for the Flexible Job-shop Scheduling Problem

被引：619
|
作者：
Pezzella, F. [1 ]
Morganti, G. [1 ]
Ciaschetti, G. [1 ]
机构：
[1] Univ Politecn Marche, Dipartimento Ingn Informat Gestionale & Automaz, I-60131 Ancona, Italy
来源：
COMPUTERS & OPERATIONS RESEARCH | 2008年 / 35卷 / 10期
关键词：
job-shop scheduling; genetic algorithms; flexible manufacturing systems;
D O I：
10.1016/j.cor.2007.02.014
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 present a genetic algorithm for the Flexible Job-shop Scheduling Problem (FJSP). The algorithm integrates different strategies for generating the initial population, selecting the individuals for reproduction and reproducing new individuals. Computational result shows that the integration of more strategies in a genetic framework leads to better results, with respect to other genetic algorithms. Moreover, results are quite comparable to those obtained by the best-known algorithm, based on tabu search. These two results, together with the flexibility of genetic paradigm, prove that genetic algorithms are effective for solving FJSP. (C) 2007 Elsevier Ltd. All rights reserved.
引用
收藏
页码：3202 / 3212
页数：11
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