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A real-coded biogeography-based optimization with mutation
Authors:Wenyin Gong  Zhihua Cai
Affiliation:a School of Computer Science, China University of Geosciences, Wuhan 430074, PR China
b Department of Computer Science, The University of Western Ontario, London, Ontario, Canada N6A 5B7
Abstract:Biogeography-based optimization (BBO) is a new biogeography inspired algorithm for global optimization. There are some open research questions that need to be addressed for BBO. In this paper, we extend the original BBO and present a real-coded BBO approach, referred to as RCBBO, for the global optimization problems in the continuous domain. Furthermore, in order to improve the diversity of the population and enhance the exploration ability of RCBBO, the mutation operator is integrated into RCBBO. Experiments have been conducted on 23 benchmark problems of a wide range of dimensions and diverse complexities. The results indicate the good performance of the proposed RCBBO method. Moreover, experimental results also show that the mutation operator can improve the performance of RCBBO effectively.
Keywords:Biogeography-based optimization   Mutation   Global optimization   Evolutionary programming   Exploration ability
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