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

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

190 Scopus Citations
View graph of relations

Author(s)

  • Tao Xiang
  • Xiaofeng Liao
  • Kwok-wo Wong

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)1637-1645
Journal / PublicationApplied Mathematics and Computation
Volume190
Issue number2
Publication statusPublished - 15 Jul 2007

Abstract

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. © 2007 Elsevier Inc. All rights reserved.

Research Area(s)

  • Chaotic optimization, Particle swarm optimization, Piecewise linear chaotic map

Citation Format(s)

An improved particle swarm optimization algorithm combined with piecewise linear chaotic map. / Xiang, Tao; Liao, Xiaofeng; Wong, Kwok-wo.

In: Applied Mathematics and Computation, Vol. 190, No. 2, 15.07.2007, p. 1637-1645.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review