A survey: Particle Swarm Optimization based algorithms to solve premature convergence problem
Data(s) |
10/08/2014
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Resumo |
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. |
Formato |
application/pdf |
Identificador | |
Publicador |
Science Publications |
Relação |
http://eprints.qut.edu.au/85241/1/out.pdf DOI:10.3844/jcssp.2014.1758.1765 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. |
Direitos |
Copyright 2014 Science Publications |
Fonte |
Institute for Future Environments; School of Information Systems; Science & Engineering Faculty; Smart Services CRC |
Tipo |
Journal Article |