nakisa-asurveyparticle-2014.pdf (108.49 kB)
A survey: Particle swarm optimization based algorithms to solve premature convergence problem
journal contribution
posted on 2014-01-01, 00:00 authored by Bahareh NakisaBahareh Nakisa, M Z A Nazri, M N Rastgoo, S AbdullahParticle 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. © 2014 Science Publications.
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Journal
Journal of Computer ScienceVolume
10Issue
9Pagination
1758 - 1765Publisher
Science PublicationsLocation
New York, N.Y.Publisher DOI
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ISSN
1549-3636Language
engPublication classification
C1.1 Refereed article in a scholarly journalUsage metrics
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