A real-coded biogeography-based optimization with mutation

被引:146
作者
Gong, Wenyin [1 ]
Cai, Zhihua [1 ]
Ling, Charles X. [2 ]
Li, Hui [1 ]
机构
[1] China Univ Geosci, Sch Comp Sci, Wuhan 430074, Peoples R China
[2] Univ Western Ontario, Dept Comp Sci, London, ON N6A 5B7, Canada
基金
国家高技术研究发展计划(863计划);
关键词
Biogeography-based optimization; Mutation; Global optimization; Evolutionary programming; Exploration ability; DIFFERENTIAL EVOLUTION; GLOBAL OPTIMIZATION;
D O I
10.1016/j.amc.2010.03.123
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 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.
引用
收藏
页码:2749 / 2758
页数:10
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