Title :
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
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;
Conference_Titel :
Data Mining and Optimization (DMO), 2012 4th Conference on
Conference_Location :
Langkawi
Print_ISBN :
978-1-4673-2717-6
DOI :
10.1109/DMO.2012.6329802
