Journal
APPLIED MATHEMATICS AND COMPUTATION
Volume 216, Issue 9, Pages 2749-2758Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.amc.2010.03.123
Keywords
Biogeography-based optimization; Mutation; Global optimization; Evolutionary programming; Exploration ability
Categories
Funding
- CUG, China Scholarship Council [2008641008]
- National High Technology Research and Development Program of China [2009AA12Z117]
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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. Crown Copyright (C) 2010 Published by Elsevier Inc. All rights reserved.
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