Opposition based Particle Swarm Optimization with student T mutation (OSTPSO)

Particle swarm optimization (PSO) is a stochastic algorithm, used for the optimization problems, proposed by Kennedy [1] in 1995. PSO is a recognized algorithm for optimization problems, but suffers from premature convergence. This paper presents an Opposition-based PSO (OPSO) to accelerate the conv...

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Bibliographic Details
Published in:Conference on Data Mining and Optimization
Main Author: Imran M.; Hashim R.; Khalid N.E.A.
Format: Conference paper
Language:English
Published: 2012
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84869433380&doi=10.1109%2fDMO.2012.6329802&partnerID=40&md5=af0013c69589f5e4eb7c0369ad890918
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Summary:Particle swarm optimization (PSO) is a stochastic algorithm, used for the optimization problems, proposed by Kennedy [1] in 1995. PSO is a recognized algorithm for optimization problems, but suffers from premature convergence. This paper presents an Opposition-based PSO (OPSO) to accelerate the convergence of PSO and at the same time, avoid early convergence. The proposed OPSO method is coupled with the student T mutation. Results from the experiment performed on the standard benchmark functions show an improvement on the performance of PSO. © 2012 IEEE.
ISSN:21556946
DOI:10.1109/DMO.2012.6329802