A tutorial survey of job-shop scheduling problems using genetic algorithms: Part II. Hybrid genetic search strategies

被引：42

作者：

Cheng, RW ^{[1
]}

Gen, M

Tsujimura, Y

机构：

[1] Northeastern Univ, Shenyang 110006, Peoples R China

[2] Ashikaga Inst Technol, Ashikaga 326, Japan

来源：

COMPUTERS & INDUSTRIAL ENGINEERING | 1999年 / 37卷 / 1-2期

关键词：

genetic algorithms; job-shop scheduling; combinatorial optimization problem and hybrid; heuristics;

D O I：

10.1016/S0360-8352(99)00022-4

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Job-shop scheduling problem is one of the well-known hardest combinatorial optimization problems. During the past decade, two important issues have been extensively studied. One is how to encode a solution into a chromosome so as to ensure that a chromosome will correspond to a feasible solution. The other issue is how to enhance the performance of genetic search by incorporating traditional heuristic method. The purpose of the paper is to give a brief survey of recent works on various hybrid genetic algorithms for the problem. (C) 1999 Published by Elsevier Science Ltd. All rights reserved.

引用

页码：51 / 55

页数：5

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