A Comprehensive Review of Particle Swarm Optimization

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Publicat a:International Journal of Engineering Research in Africa vol. 23 (Apr 2016), p. 141
Autor principal: Benuwa, Ben Bright
Altres autors: Ghansah, Benjamin, Wornyo, Dickson Keddy, Adabunu, Sefakor Awurama
Publicat:
Trans Tech Publications Ltd.
Accés en línia:Citation/Abstract
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Resum:  Particle swarm optimization (PSO) is a heuristic global optimization method. PSO was motivated by the social behavior of organisms, such as bird flocking, fish schooling and human social relations. Its properties of low constraint on the continuity of objective function and the ability to adapt various dynamic environments, makes PSO one of the most important swarm intelligence algorithms and ostensibly the most commonly used optimization technique. This survey presents a comprehensive investigation of PSO and in particular, a proposed theoretical framework to improve its implementation. We hope that this survey would be beneficial to researchers studying PSO algorithms and would also serve as the substratum for future research in the study area, particularly those pursuing their career in artificial intelligence. In the end, some important conclusions and possible research directions of PSO that need to be studied in the future are proposed.
ISSN:1663-3571
1663-4144
DOI:10.4028/www.scientific.net/JERA.23.141
Font:Materials Science Database