A survey: Particle swarm optimization based algorithms to solve premature convergence problem

Bahareh Nakisa, Mohd Zakree Ahmad Nazri, Mohammad Naim Rastgoo, Salwani Abdullah

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

Particle Swarm Optimization (PSO) is a biologically inspired computational search and optimization method based on the social behaviors of birds flocking or fish schooling. Although PSO is represented in solving many well-known numerical test problems, but it suffers from the premature convergence. A number of basic variations have been developed due to solve the premature convergence problem and improve quality of solution founded by the PSO. This study presents a comprehensive survey of the various PSO-based algorithms. As part of this survey, we include a classification of the approaches and we identify the main features of each proposal. In the last part of the study, some of the topics within this field that are considered as promising areas of future research are listed.

Original languageEnglish
Pages (from-to)1758-1765
Number of pages8
JournalJournal of Computer Science
Volume10
Issue number10
DOIs
Publication statusPublished - 2014

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Particle swarm optimization (PSO)
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Keywords

  • Diversity guided search
  • Particle swarm optimization (PSO)
  • Premature convergence

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Artificial Intelligence

Cite this

A survey : Particle swarm optimization based algorithms to solve premature convergence problem. / Nakisa, Bahareh; Ahmad Nazri, Mohd Zakree; Rastgoo, Mohammad Naim; Abdullah, Salwani.

In: Journal of Computer Science, Vol. 10, No. 10, 2014, p. 1758-1765.

Research output: Contribution to journalArticle

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