Vestnik KRAUNC. Fiz.-Mat. Nauki. 2022. vol. 39. no. 2. pp. 156–180. ISSN 2079-6641

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MSC 68Т27

Review Article

A Concise Overview of Particle Swarm Optimization Methods

E. M. Kazakova

Institute of Applied Mathematics and Automation KBSC RAS, 360000, Nalchik, Shortanova st., 89a, Russia


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.

Key words: optimization, particle swarm optimization, meta-heuristic algorithm.

DOI: 10.26117/2079-6641-2022-39-2-156-180

Original article submitted: 07.07.2022

Revision submitted: 25.08.2022

For citation. Kazakova E. M. A Concise Overview of Particle Swarm Optimization Methods. Vestnik KRAUNC. Fiz.-mat. nauki. 2022, 39: 2, 156-180. DOI: 10.26117/2079-6641-2022-39-2-156-180

Competing interests. The authors declare that there are no conflicts of interest regarding authorship and publication.

Contribution and Responsibility. All authors contributed to this article. Authors are solely responsible for providing the final version of the article in print. The final version of the manuscript was approved by all authors.

The content is published under the terms of the Creative Commons Attribution 4.0 International License (

© Kazakova E. M., 2022


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Kazakova Elena Musovna – Junior Researcher of the Department of Neural Networks and Machine Learning, Institute of Applied Mathematics and Automation, Kabardino-Balkarian Republic, Nalchik, Russia, ORCID 0000-0002-5819-9396.