Genetic algorithms for the job-shop scheduling problem with unrelated parallel constraints: heuristic mixing method machines and precedence

被引:27
作者
Ghedjati, F [1 ]
机构
[1] Univ Paris 06, F-75252 Paris 05, France
关键词
scheduling; job-shop; unrelated parallel machines; linear and non-linear process routings; genetic algorithms; heuristic mixing method;
D O I
10.1016/S0360-8352(99)00019-4
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 are interested in job-shop scheduling problems with several unrelated parallel machines and precedence constraints between the operations of the jobs (with either linear or non-linear process routings). The objective is to minimize the maximum completion time (C-max) We propose an original resolution method based on genetic algorithms and that we call heuristic mixing method, where crossovers merge the specific heuristics designed for the considered problem. After a description of both the problem and the resolution method, we present the experimental results. (C) 1999 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:39 / 42
页数:4
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