A modified particle swarm optimization for correlated phenomena


Autoria(s): Arefi, Ali; Haghifam, Mahmoud Reza
Data(s)

01/12/2011

Resumo

The wide applicability of correlation analysis inspired the development of this paper. In this paper, a new correlated modified particle swarm optimization (COM-PSO) is developed. The Correlation Adjustment algorithm is proposed to recover the correlation between the considered variables of all particles at each of iterations. It is shown that the best solution, the mean and standard deviation of the solutions over the multiple runs as well as the convergence speed were improved when the correlation between the variables was increased. However, for some rotated benchmark function, the contrary results are obtained. Moreover, the best solution, the mean and standard deviation of the solutions are improved when the number of correlated variables of the benchmark functions is increased. The results of simulations and convergence performance are compared with the original PSO. The improvement of results, the convergence speed, and the ability to simulate the correlated phenomena by the proposed COM-PSO are discussed by the experimental results.

Identificador

http://eprints.qut.edu.au/68731/

Publicador

Elsevier BV

Relação

DOI:10.1016/j.asoc.2011.07.018

Arefi, Ali & Haghifam, Mahmoud Reza (2011) A modified particle swarm optimization for correlated phenomena. Applied Soft Computing, 11(8), pp. 4640-4654.

Direitos

Copyright 2011 Elsevier Science Publishers B. V. Amsterdam, The Netherlands

Fonte

School of Electrical Engineering & Computer Science; Science & Engineering Faculty

Palavras-Chave #Particle swarm optimization #Correlation coefficient #Mutation #Secondary PSO
Tipo

Journal Article