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A perturb biogeography based optimization with mutation for global numerical optimization
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AI
DOI：10.1016/j.amc.2011.05.110.png)
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Biogeography based optimization (BBO) is a new evolutionary optimization algorithm based on the science of biogeography for global optimization. We propose three extensions to BBO. First, we propose a new migration operation based sinusoidal migration model called perturb migration, which is a generalization of the standard BBO migration operator. Then, the Gaussian mutation operator is integrated into perturb biogeography based optimization (PBBO) to enhance its exploration ability and to improve the diversity of population. Experiments have been conducted on 23 benchmark problems of a wide range of dimensions and diverse complexities. Simulation results and comparisons demonstrate the proposed PBBO algorithm using sinusoidal migration model is better, or at least comparable to, the RCBBO based linear model, RCBBO-G, RCBBO-L and evolutionary algorithms from literature when considering the quality of the solutions obtained. (C) 2011 Elsevier Inc. All rights reserved.
Keyword:
Biogeography based optimization
Perturb opertor
Global numerical optimization
Exploration
Exploitation
期刊
IF:
3.4
论文数:
2.3W
被引数:
3.3W
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