A perturb biogeography based optimization with mutation for global numerical optimization

被引:73
作者
Li, Xiangtao [1 ,2 ]
Wang, Jinyan [1 ]
Zhou, Junping [1 ]
Yin, Minghao [1 ,2 ]
机构
[1] NE Normal Univ, Coll Comp Sci, Changchun 130117, Peoples R China
[2] Jilin Univ, Minist Educ, Key Lab Symbol Computat & Knowledge Engn, Changchun 130012, Peoples R China
基金
中国国家自然科学基金;
关键词
Biogeography based optimization; Perturb opertor; Global numerical optimization; Exploration; Exploitation; PARTICLE SWARM; CONVERGENCE; ALGORITHM; COLONY;
D O I
10.1016/j.amc.2011.05.110
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
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.
引用
收藏
页码:598 / 609
页数:12
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