Particle swarm optimization with multiscale searching method

Xiaohui Yuan, Jing Peng, Yasumasa Nishiura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

This paper presents a new method for effectively searching all global minima of a multimodal function. The method is based on particle swarm optimizer, particles are dynamically divided into serval subgroups of different size in order to explore variable space using various step size simultaneously, In each subgroup, a new scheme is proposed to update the the positions of particles, this scheme takes into consideration the effect of all subgroup seeds. Experimental results for one dimensional, two dimensional and thirty dimensional test suites demonstrated that this method can get overall promising performance over a wide range problems.

Original languageEnglish
Title of host publicationComputational Intelligence and Security - International Conference, CIS 2005, Proceedings
Pages669-674
Number of pages6
Publication statusPublished - 2005 Dec 1
Externally publishedYes
EventInternational Conference on Computational Intelligence and Security, CIS 2005 - Xi'an, China
Duration: 2005 Dec 152005 Dec 19

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3801 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherInternational Conference on Computational Intelligence and Security, CIS 2005
CountryChina
CityXi'an
Period05/12/1505/12/19

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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