Memetic particle swarm optimization

被引：115

作者：

Petalas, Y. G. ^{[1
]}

Parsopoulos, K. E. ^{[1
]}

Vrahatis, M. N. ^{[1
]}

机构：

[1] Univ Patras, Dept Math, Computat Intelligence Lab, Artificial Intelligence Res Ctr UPAIRC, GR-26110 Patras, Greece

来源：

ANNALS OF OPERATIONS RESEARCH | 2007年 / 156卷 / 01期

关键词：

global optimization; particle swarm optimization; memetic algorithms; local search;

D O I：

10.1007/s10479-007-0224-y

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：

We propose a new Memetic Particle Swarm Optimization scheme that incorporates local search techniques in the standard Particle Swarm Optimization algorithm, resulting in an efficient and effective optimization method, which is analyzed theoretically. The proposed algorithm is applied to different unconstrained, constrained, minimax and integer programming problems and the obtained results are compared to that of the global and local variants of Particle Swarm Optimization, justifying the superiority of the memetic approach.

引用

页码：99 / 127

页数：29

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