A hybrid evolutionary algorithm for the job shop scheduling problem

被引：26
|
作者：
Zobolas, G. I. [1 ]
Tarantilis, C. D. [1 ]
Ioannou, G. [1 ]
机构：
[1] Athens Univ Econ & Business, Management Sci Lab, Dept Management Sci & Technol, Athens 11369, Greece
来源：
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY | 2009年 / 60卷 / 02期
关键词：
Production scheduling; job shop; evolutionary algorithms; VNS; GENETIC ALGORITHM; DIFFERENTIAL EVOLUTION; SHIFTING BOTTLENECK; SEARCH ALGORITHM; LOCAL SEARCH; OPTIMIZATION;
D O I：
10.1057/palgrave.jors.2602534
中图分类号：
C93 [管理学];
学科分类号：
12 ; 1201 ; 1202 ; 120202 ;
摘要：
In this paper, a hybrid metaheuristic method for the job shop scheduling problem is proposed. The optimization criterion is the minimization of makespan and the solution method consists of three components: a Differential Evolution-based algorithm to generate a population of initial solutions, a Variable Neighbourhood Search method and a Genetic Algorithm to improve the population; the latter two are interconnected. Computational experiments on benchmark data sets demonstrate that the proposed hybrid metaheuristic reaches high quality solutions in short computational times using fixed parameter settings.
引用
收藏
页码：221 / 235
页数：15
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