Statistical stability analysis for particle swarm optimization dynamics with random coefficients

Yuji Koguma, Eitaro Aiyoshi

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Particle Swarm Optimization (PSO), a meta-heuristic global optimization method, has attracted special interest for its simple algorithm and high searching ability. The updating formula of PSO involves coefficients with random numbers as parameters to enhance diversification ability in searching for the global optimum. However, the randomness makes stability of the searching points difficult to be analyzed mathematically, and the users need to adjust the parameter values by trial and error. In this paper, stability of the stochastic dynamics of PSO is analyzed mathematically and exact stability condition taking the randomness into consideration is presented with an index "statistical eigenvalue", which is a new concept to evaluate the degree of the stability of PSO dynamics. Accuracy and effectiveness of the proposed stability discrimination using the presented index are certified in numerical simulation for simple examples.

Original languageEnglish
Pages (from-to)1020-1030
Number of pages11
JournalIEEJ Transactions on Electronics, Information and Systems
Volume131
Issue number5
DOIs
Publication statusPublished - 2011

Keywords

  • Meta-heuristics
  • Particle Swarm Optimization
  • Stability analysis

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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