A survey: Particle Swarm Optimization based algorithms to solve premature convergence problem

Nakisa, Bahareh & Rastgoo, Mohammad Naim (2014) A survey: Particle Swarm Optimization based algorithms to solve premature convergence problem. Journal of Computer Science, 10(9), pp. 1758-1765.

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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, the authors have included a classification of the approaches and they have 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.

Impact and interest:

6 citations in Scopus
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ID Code: 85241
Item Type: Journal Article
Refereed: Yes
DOI: 10.3844/jcssp.2014.1758.1765
ISSN: 1549-3636‎
Divisions: Current > Institutes > Institute for Future Environments
Current > Schools > School of Information Systems
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Current > Research Centres > Smart Services CRC
Copyright Owner: Copyright 2014 Science Publications
Deposited On: 12 Jul 2015 22:25
Last Modified: 16 Jul 2015 01:34

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