Title: Chaotic biogeography-based optimisation

Authors: Weian Guo; Wuzhao Li; Qi Kang; Lei Wang; Qidi Wu

Addresses: Sino-German College, Applied Science of Tongji University, Shanghai 201804, China; School of Electronics and Information Engineering, Tongji University, Shanghai 201804, China ' Department of Electrical and Mechanical Engineering, Jiaxing Vocational Technical College, Jiaxing 314036, China; School of Electronics and Information Engineering, Tongji University, Shanghai 201804, China ' School of Electronics and Information Engineering, Tongji University, Shanghai 201804, China ' School of Electronics and Information Engineering, Tongji University, Shanghai 201804, China ' School of Electronics and Information Engineering, Tongji University, Shanghai 201804, China

Abstract: Evolutionary algorithms (EAs) performs much better than traditional ones in solving optimisation problems. Biogeography-based optimisation (BBO) is a newly proposed kind of EAs, robust and needs little extra information when doing optimisation. Chaos is actually a mapping that exhibits some sort of chaotic behaviour, and has the features of randomness and ergodicity, which make chaos optimisation more elaborate in a certain domain without repeated searching. In this paper, BBO and chaos are merged together and chaotic biogeography-based optimisation method is proposed for the first time. According to several famous chaotic models, corresponding chaotic biogeography-based optimisation methods are produced. Comparison of these methods with other algorithms from numerical test shows that the new hybrid optimisation method doses a better job on many benchmark functions.

Keywords: evolutionary algorithms; EAs; chaotic models; chaos; chaotic BBO; biogeography-based optimisation.

DOI: 10.1504/IJCSM.2014.064057

International Journal of Computing Science and Mathematics, 2014 Vol.5 No.2, pp.127 - 136

Available online: 31 Jul 2014 *

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