Hybrid algorithm based on particle swarm optimization and artificial fish swarm algorithm

Authors:
Jingqing Jiang;Yuling Bo;Chuyi Song;Lanying Bao
Affiliations:
College of Computer Science and Technology, Inner Mongolia University for Nationalities, Tongliao, China;College of Mathematics, Inner Mongolia University for Nationalities, Tongliao, China;College of Mathematics, Inner Mongolia University for Nationalities, Tongliao, China;College of Mathematics, Inner Mongolia University for Nationalities, Tongliao, China
Venue:
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part I
Year:
2012

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Abstract

A hybrid algorithm based on particle swarm optimization(PSO) and artificial fish swarm algorithm(AFSA) is proposed. It combines the advantages of PSO and AFSA. The improved AFSA is introduced into PSO at the iteration. The following behavior and swarming behavior of AFSA are performed on two sub-swarms simultaneously. The proposed algorithm increases the variety of the population and improves the accuracy of the solution.