Particle Swarm Optimization with Dynamic Dimension Crossover for High Dimensional Problems

Authors:
Chengyu Hu;Xuesong Yan;Chuanfeng Li
Affiliations:
School of Computer, China University of Geosciences, Wuhan, China 430074 and Department of Control Science and Engineering, Huazhong University of Science & Technology, Wuhan, China 430074;School of Computer, China University of Geosciences, Wuhan, China 430074;Department of Control Science and Engineering, Huazhong University of Science & Technology, Wuhan, China 430074
Venue:
ISICA '08 Proceedings of the 3rd International Symposium on Advances in Computation and Intelligence
Year:
2008

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Abstract

Previous work presented some modified approaches based particle swarm optimization (PSO) to solve complex optimization problems. Preliminary results demonstrated that PSO with crossover (CPSO) constituted a promising approach to solve some optimization problems. However how to optimize high dimensional problem with crossover became challenging. In this paper, a modified PSO with dimension crossover is proposed. First we analyze the cause of hardly optimizing the high dimensional problem, and then design one dynamic dimension crossover PSO (DDC-PSO) to cope with high dimensional problems. Theoretical analysis is also presented to show why the modified algorithm can be effective. Finally DDC-PSO is tested on five benchmark optimization problems and the results show a superior performance compared to the standard PSO and CPSO.