Chaotic biogeography-based optimisation
by Weian Guo; Wuzhao Li; Qi Kang; Lei Wang; Qidi Wu
International Journal of Computing Science and Mathematics (IJCSM), Vol. 5, No. 2, 2014

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.

Online publication date: Sat, 20-Sep-2014

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