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Vestnik KRAUNC. Fiziko-Matematicheskie Nauki, 2022, Volume 39, Number 2, Pages 150–174
DOI: https://doi.org/10.26117/2079-6641-2022-39-2-150-174 (Mi vkam544) 		 
This article is cited in 2 scientific papers (total in 2 papers)

INFORMATION AND COMPUTATION TECHNOLOGIES

A concise overview of particle swarm optimization methods

E. M. Kazakova

Institute of Applied Mathematics and Automation KBSC RAS
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DOI: https://doi.org/10.26117/2079-6641-2022-39-2-150-174
Abstract: Particle Swarm Optimization (PSO) is a meta-heuristic method of global, inferred, proposed by Kennedy and Eberhart in 1995. It is currently one of the most commonly used search methods. This review provides a brief overview of PSO research in recent years – swarm and rate initialization methods in PSO, modifications, neighborhood topologies, hybridization, and an overview of various PSO applications.
Keywords: optimization, particle swarm optimization, meta-heuristic algorithm.
Document Type: Article
UDC: 519.7
Language: Russian
Citation: E. M. Kazakova, “A concise overview of particle swarm optimization methods”, Vestnik KRAUNC. Fiz.-Mat. Nauki, 39:2 (2022), 150–174
Citation in format AMSBIB
\Bibitem{Kaz22}
\by E.~M.~Kazakova
\paper A concise overview of particle swarm optimization methods
\jour Vestnik KRAUNC. Fiz.-Mat. Nauki
\yr 2022
\vol 39
\issue 2
\pages 150--174
\mathnet{http://mi.mathnet.ru/vkam544}
\crossref{https://doi.org/10.26117/2079-6641-2022-39-2-150-174}
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    • This publication is cited in the following 2 articles:
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    		Vestnik KRAUNC. Fiziko-Matematicheskie Nauki Vestnik KRAUNC. Fiziko-Matematicheskie Nauki
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