An improved particle swarm optimization algorithm combined with piecewise linear chaotic map

被引：203

作者：

Xiang, Tao ^{[1
]}

Liao, Xiaofeng

Wong, Kwok-wo

机构：

[1] Chongqing Univ, Coll Comp Sci, Chongqing 400044, Peoples R China

[2] City Univ Hong Kong, Dept Elect Engn, Hong Kong, Hong Kong, Peoples R China

来源：

APPLIED MATHEMATICS AND COMPUTATION | 2007年 / 190卷 / 02期

关键词：

particle swarm optimization; chaotic optimization; piecewise linear chaotic map;

D O I：

10.1016/j.amc.2007.02.103

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Particle swarm optimization (PSO) has gained increasing attention in tackling complex optimization problems. Its further superiority when hybridized with other search techniques is also shown. Chaos, with the properties of ergodicity and stochasticity, is definitely a good candidate, but currently only the well-known logistic map is prevalently used. In this paper, the performance and deficiencies of schemes coupling chaotic search into PSO are analyzed. Then, the piecewise linear chaotic map (PWLCM) is introduced to perform the chaotic search. An improved PSO algorithm combined with PWLCM (PWLCPSO) is proposed subsequently, and experimental results verify its great superiority. (C) 2007 Elsevier Inc. All rights reserved.

引用

页码：1637 / 1645

页数：9

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