Abstract
Biogeography-based optimization (BBO) is a population-based evolutionary algorithm (EA) that is based on the mathematics of biogeography. It mainly uses the biogeography-based migration operator to share the information among solutions. Differential Evolution (DE) is a fast and robust evolutionary algorithm for global optimization. In this paper, we propose a hybrid algorithm of BBO and DE, named BDE, for the global numerical optimization problem. To verify the performance of our proposed BDE, 12 benchmark functions with a wide range of dimensions and diverse complexities are employed. Experiment results indicate that our approach is effective and efficient.
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Mo, H., Li, Z., Zhang, L. (2012). Research on Biogeography Differential Evolution Algorithm. In: Li, Z., Li, X., Liu, Y., Cai, Z. (eds) Computational Intelligence and Intelligent Systems. ISICA 2012. Communications in Computer and Information Science, vol 316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34289-9_32
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DOI: https://doi.org/10.1007/978-3-642-34289-9_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34288-2
Online ISBN: 978-3-642-34289-9
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