Quantum-behaved particle swarm optimization with a hybrid probability distribution

Authors:
Jun Sun;Wenbo Xu;Wei Fang
Affiliations:
Center of Intelligent and High Performance Computing, School of Information Technology, Southern Yangtze University, Jiangsu, China;Center of Intelligent and High Performance Computing, School of Information Technology, Southern Yangtze University, Jiangsu, China;Center of Intelligent and High Performance Computing, School of Information Technology, Southern Yangtze University, Jiangsu, China
Venue:
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Year:
2006

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Abstract

Based on the previous introduced Quantum-behaved Particle Swarm Optimization (QPSO), in this paper, a revised QPSO with novel iterative equation is proposed. While the iterative equation in the QPSO is educed from exponential distribution, the novel one derives from the distribution function of the sum of two random variables with exponential and normal distribution, respectively. The Revised QPSO 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 Revised QPSO has stronger global search ability than QPSO and PSO.