Title: Using selection to improve quantum-behaved particle swarm optimisation

Authors: Haixia Long, Jun Sun, Xiaogen Wang, C-H. Lai, Wenbo Xu

Addresses: School of Information Technology, Southern Yangtze University, No. 1800, Lihudadao Road, Wuxi, 214122 Jiangsu, China. ' School of Information Technology, Southern Yangtze University, No. 1800, Lihudadao Road, Wuxi, 214122 Jiangsu, China. ' School of Information Technology, Southern Yangtze University, No. 1800, Lihudadao Road, Wuxi, 214122 Jiangsu, China. ' School of Computing and Mathematical Sciences, University of Greenwich, Greenwich, London SE10 9LS, UK. ' School of Information Technology, Southern Yangtze University, No. 1800, Lihudadao Road, Wuxi, 214122 Jiangsu, China

Abstract: Quantum-behaved particle swarm optimisation (QPSO) algorithm is a global convergence guaranteed algorithms, which outperforms original PSO in search ability but has fewer parameters to control. This paper describes two selection mechanisms into QPSO to improve the search ability of QPSO. One is the QPSO with tournament selection (QPSO-TS) and the other is the QPSO with roulette-wheel selection (QPSO-RS). While the centre of position distribution of each particle in QPSO is determined by global best position and personal best position, in the QPSO with selection operation, the global best position is substituted by a candidate solution through selection. The QPSO with selection operation also maintains the mean best position of the swarm as in the previous QPSO to make the swarm more efficient in global search. The experiment results on benchmark functions show that both QPSO-RS and QPSO-TS have better performance and stronger global search ability than QPSO and standard PSO.

Keywords: quantum-behaved particle swarm optimisation; QPSO; tournament selection; roulette-wheel selection; global best position; QPSO-TS; QPSO-R; search abilityS.

DOI: 10.1504/IJICA.2009.031780

International Journal of Innovative Computing and Applications, 2009 Vol.2 No.2, pp.100 - 114

Published online: 24 Feb 2010 *

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