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

• 發表在: Conference on Data Mining and Optimization
• 主要作者: 2-s2.0-84869433380
• 格式: Conference paper
• 語言: English
• 出版: 2012
• 在線閱讀: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84869433380&doi=10.1109%2fDMO.2012.6329802&partnerID=40&md5=af0013c69589f5e4eb7c0369ad890918
• ISSN: 21556946
• DOI: 10.1109/DMO.2012.6329802

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.