Multi-population interactive coevolutionary algorithm for flexible job shop scheduling problems

被引：25
|
作者：
Xing, Li-Ning [1 ]
Chen, Ying-Wu [1 ]
Yang, Ke-Wei [1 ]
机构：
[1] Natl Univ Def Technol, Coll Informat Syst & Management, Changsha, Hunan, Peoples R China
来源：
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS | 2011年 / 48卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Combinatorial optimization; Flexible job shop scheduling; Genetic algorithm; Ant colony optimization; Multi-population; Interactive; Coevolutionary; SHIFTING BOTTLENECK; GENETIC ALGORITHM; OPTIMIZATION; STRATEGY;
D O I：
10.1007/s10589-009-9244-7
中图分类号：
C93 [管理学]; O22 [运筹学];
学科分类号：
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要：
In this paper, it proposes a multi-population interactive coevolutionary algorithm for the flexible job shop scheduling problems. In the proposed algorithm, both the ant colony optimization and genetic algorithm with different configurations were applied to evolve each population independently. By the interaction, competition and sharing mechanism among populations, the computing resource is utilized more efficiently, and the quality of populations is improved effectively. The performance of our proposed approach was evaluated by a lot of benchmark instances taken from literature. The experimental results have shown that the proposed algorithm is a feasible and effective approach for the flexible job shop scheduling problem.
引用
收藏
页码：139 / 155
页数：17
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