A novel particle swarm optimizer with time-delay

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

15 Scopus Citations
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Author(s)

  • Tao Xiang
  • Kwok-wo Wong
  • Xiaofeng Liao

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)789-793
Journal / PublicationApplied Mathematics and Computation
Volume186
Issue number1
Publication statusPublished - 1 Mar 2007

Abstract

Particle swarm optimization (PSO) is a relatively new population-based heuristic optimization technique. It has been widely applied to optimization problems for simplicity and capability of finding fairly good solutions rapidly. However, it may be trapped in local optima and fails to converge to global optimum. In this paper, the concept of time-delay is introduced into PSO to control the process of information diffusion and keep the particle diversity. Four time-delay schemes are proposed then. Experimental results verify their superiority both in robustness and efficiency. Conclusions are drawn in the end. © 2006 Elsevier Inc. All rights reserved.

Research Area(s)

  • Diversity, Particle swarm optimization, Time-delay

Citation Format(s)

A novel particle swarm optimizer with time-delay. / Xiang, Tao; Wong, Kwok-wo; Liao, Xiaofeng.

In: Applied Mathematics and Computation, Vol. 186, No. 1, 01.03.2007, p. 789-793.

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