Stability analysis in consideration of random numbers for particle swarm optimization dynamics: The best parameter for sustainable search

Yuji Koguma, Eitaro Aiyoshi

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Particle Swarm Optimization (PSO), which has attracted special interest as a global optimization method recently, has a drawback in that its sustainable search can not be executed until the end of computation. In order to endow global searching abilities to PSO, repetition of unstable and stable states of the particles is necessary. In this paper, based on stability analysis of PSO's model, with considering its random numbers, we realize sustainable search by choosing system parameters on boundary region between unstable and stable states, and then introduce an optimization model with global searching abilities as a revision of the conventional PSO.

Original languageEnglish
Pages (from-to)29-38
Number of pages10
JournalIEEJ Transactions on Electronics, Information and Systems
Volume130
Issue number1
DOIs
Publication statusPublished - 2010

Keywords

  • Linear stability analysis
  • Meta-heuristics
  • Particle swarm optimization

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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