Dynamic particle swarm optimization using a wavelet mutation strategy for composite function optimization

Jianchao Fan, Jun Wang

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

Abstract

In this paper, a novel dynamic particle swarm optimization is considered for composite function optimization. Because the complex computation problem exists commonly in practice, solving this problem is significant. The dynamic neighborhood topology and wavelet mutation could assist the PSO algorithm cooperate with neighbor particles and overcome the premature problem. The results offer insight into how the proposed algorithm has the better effectiveness in solving composite functions.

Original languageEnglish
Title of host publication2015 7th International Conference on Advanced Computational Intelligence, ICACI 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages329-333
Number of pages5
ISBN (Electronic)9781479972579
DOIs
Publication statusPublished - 10 Aug 2015
Externally publishedYes
Event7th International Conference on Advanced Computational Intelligence, ICACI 2015 - Wuyi, China
Duration: 27 Mar 201529 Mar 2015

Publication series

Name2015 7th International Conference on Advanced Computational Intelligence, ICACI 2015

Conference

Conference7th International Conference on Advanced Computational Intelligence, ICACI 2015
Country/TerritoryChina
CityWuyi
Period27/03/1529/03/15

Keywords

  • Lead
  • Optimization
  • Out of order
  • Topology

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