The performance measurement of a canonical particle swarm optimizer with diversive curiosity

Authors:
Hong Zhang;Jie Zhang
Affiliations:
Department of Brain Science and Engineering, Kyushu Institute of Technology, Kitakyushu, Japan;Wuxi Bowen Software Technology Co., Ltd, Wuxi, Jiangsu, China
Venue:
ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part I
Year:
2010

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Abstract

For improving the search performance of a canonical particle swarm optimizer (CPSO), we propose a newly canonical particle swarm optimizer with diversive curiosity (CPSO/DC) A crucial idea here is to introduce diversive curiosity into the CPSO to comprehensively manage the trade-off between exploitation and exploration for alleviating stagnation To demonstrate the effectiveness of the proposed method, computer experiments on a suite of five-dimensional benchmark problems are carried out We investigate the characteristics of the CPSO/DC, and compare the search performance with other methods The obtained results indicate that the search performance of the CPSO/DC is superior to that by EPSO, ECPSO and RGA/E, but is inferior to that by PSO/DC for the Griewank and Rastrigin problems.