Convergence analysis of brain storm optimization algorithm

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

Abstract

Brain storm optimization (BSO) algorithm is a new kind of swarm intelligence algorithm, which is inspired by collective behavior of human beings. In this paper, a Markov model for brain storm optimization algorithm is derived. The model gives the theoretical probability of the occurrence of each possible population as the number of generation count goes to infinity. Using the Markov model, the convergence of the brain storm optimization is analyzed.

Original languageEnglish
Title of host publication2016 IEEE Congress on Evolutionary Computation, CEC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3747-3752
Number of pages6
ISBN (Electronic)9781509006229
DOIs
StatePublished - 14 Nov 2016
Event2016 IEEE Congress on Evolutionary Computation, CEC 2016 - Vancouver, Canada
Duration: 24 Jul 201629 Jul 2016

Publication series

Name2016 IEEE Congress on Evolutionary Computation, CEC 2016

Conference

Conference2016 IEEE Congress on Evolutionary Computation, CEC 2016
Country/TerritoryCanada
CityVancouver
Period24/07/1629/07/16

Keywords

  • Brain storm optimization
  • Convergence analysis
  • Markov chain
  • Style

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