Chaotic biogeography-based optimisation

被引:2
|
作者
Guo, Weian [1 ,2 ]
Li, Wuzhao [2 ,3 ]
Kang, Qi [2 ]
Wang, Lei [2 ]
Wu, Qidi [2 ]
机构
[1] Tongji Univ, Sino German Coll, Appl Sci, Shanghai 201804, Peoples R China
[2] Tongji Univ, Sch Elect & Informat Engn, Shanghai 201804, Peoples R China
[3] Jiaxing Vocat Tech Coll, Dept Elect & Mech Engn, Jiaxing 31403693, Peoples R China
基金
中国国家自然科学基金; 美国国家科学基金会;
关键词
evolutionary algorithms; EAs; chaotic models; chaotic system; chaotic biogeography-based optimisation; BBO;
D O I
10.1504/IJCSM.2014.064057
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Evolutionary algorithms (EAs) performs much better than traditional ones in solving optimisation problems. Biogeography-based optimisation (BBO) is a newly proposed kind of EAs, robust and needs little extra information when doing optimisation. Chaos is actually a mapping that exhibits some sort of chaotic behaviour, and has the features of randomness and ergodicity, which make chaos optimisation more elaborate in a certain domain without repeated searching. In this paper, BBO and chaos are merged together and chaotic biogeography-based optimisation method is proposed for the first time. According to several famous chaotic models, corresponding chaotic biogeography-based optimisation methods are produced. Comparison of these methods with other algorithms from numerical test shows that the new hybrid optimisation method doses a better job on many benchmark functions.
引用
收藏
页码:127 / 136
页数:10
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