Small world network based dynamic topology for particle swarm optimization

Qingxue Liu, Barend Jacobus Van Wyk, Yanxia Sun

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Citations (Scopus)

Abstract

A new particle optimization algorithm with dynamic topology is proposed based on 'small world' network. The technique imitates the dissemination of information in a 'small world network' by dynamically updating the neighborhood topology of particle swarm optimization. The proposed dynamic neighborhood strategy can effectively coordinate the exploration and exploitation ability of particle swarm optimization. Simulations demonstrated that convergence of the swarms is guaranteed. Experiments demonstrated that the proposed method maintained the population diversity and enhanced the global search ability.

Original languageEnglish
Title of host publication2015 11th International Conference on Natural Computation, ICNC 2015
EditorsZheng Xiao, Zhao Tong, Kenli Li, Xingwei Wang, Keqin Li
PublisherIEEE Computer Society
Pages289-294
Number of pages6
ISBN (Electronic)9781467376792
DOIs
Publication statusPublished - 8 Jan 2016
Event11th International Conference on Natural Computation, ICNC 2015 - Zhangjiajie, China
Duration: 15 Aug 201517 Aug 2015

Publication series

NameProceedings - International Conference on Natural Computation
Volume2016-January
ISSN (Print)2157-9555

Conference

Conference11th International Conference on Natural Computation, ICNC 2015
Country/TerritoryChina
CityZhangjiajie
Period15/08/1517/08/15

Keywords

  • Local model
  • global model
  • neighborhood topology
  • particle swarm
  • small world network

ASJC Scopus subject areas

  • General Computer Science
  • Biomedical Engineering
  • Computational Mechanics
  • General Mathematics
  • General Neuroscience

Fingerprint

Dive into the research topics of 'Small world network based dynamic topology for particle swarm optimization'. Together they form a unique fingerprint.

Cite this