A novel hybrid differential evolution and particle swarm optimization algorithm for unconstrained optimization

被引：89

作者：

Zhang, Changsheng ^{[1
]}

Ning, Jiaxu

Lu, Shuai ^{[1
]}

Ouyang, Dantong ^{[1
]}

Ding, Tienan ^{[1
]}

机构：

[1] Minist Educ, Key Lab Symbol Computat & Knowledge Engn, Changchun 130012, Peoples R China

来源：

OPERATIONS RESEARCH LETTERS | 2009年 / 37卷 / 02期

关键词：

Particle swarm optimization; Unconstrained optimization; Differential evolution algorithm; GLOBAL OPTIMIZATION; GENETIC ALGORITHM; SIMPLEX SEARCH; TABU SEARCH; PRINCIPLES;

D O I：

10.1016/j.orl.2008.12.008

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：

An algorithm called DE-PSO is proposed which incorporates concepts from DE and PSO, updating particles not only by DE operators but also by mechanisms of PSO. The proposed algorithm is tested on several benchmark functions. Numerical comparisons with different hybrid meta-heuristics demonstrate its effectiveness and efficiency. (C) 2009 Elsevier B.V. All rights reserved.

引用

页码：117 / 122

页数：6

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