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

Author

Imran, Muhammad ; Hashim, Rathiah ; Khalid, Noor Elaiza Abd

Author_Institution

FSKTM, Univ. Tun Hussein onn Malaysia, Batu Pahat, Malaysia

fYear

2012

Firstpage

80

Lastpage

85

Abstract

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.

Keywords

convergence; evolutionary computation; particle swarm optimisation; statistical distributions; stochastic processes; OSTPSO; convergence acceleration; early convergence; opposition based particle swarm optimization; optimization problem; premature convergence; stochastic algorithm; student T distribution; student T mutation; Benchmark testing; Convergence; Educational institutions; Equations; Optimization; Sociology; Statistics; PSO; PSO with student T distribution; modified PSO; student T distribution;

fLanguage

English

Publisher

ieee

Conference_Titel

Data Mining and Optimization (DMO), 2012 4th Conference on

Conference_Location

Langkawi

Print_ISBN

978-1-4673-2717-6

Type

conf

DOI

10.1109/DMO.2012.6329802

Filename

6329802