Self-adapting differential evolution algorithm with chaos random for global numerical optimization

Authors:
Ming Yang;Jing Guan;Zhihua Cai;Lu Wang
Affiliations:
School of Computer Science, China University of Geosciences, Wuhan, China;Institute for Pattern Recognition and Artificial Intelligence, Huazhong University of Science and Technology, Wuhan, China;School of Computer Science, China University of Geosciences, Wuhan, China;Department of Computer Engineering, Ordnance Engineering College, Shijiazhuang, China
Venue:
ISICA'10 Proceedings of the 5th international conference on Advances in computation and intelligence
Year:
2010

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Abstract

Choosing the proper control parameters for DE is quite difficult because the best settings for the control parameters can be different for different functions. In this paper, the proposed self-adaptive method is an attempt to determine the values of control parameters F and CR. In this method, the adjusting of F and CR associates with fitness of individuals and the new values are Chaos random numbers. The experiment results show that this algorithm can attain better solutions than other algorithms for multimodal functions.