Hybridizing harmony search with biogeography based optimization for global numerical optimization

	Hybridizing harmony search with biogeography based optimization for global numerical optimization
	Wang G.; Guo L.; Duan H.; Wang H.; Liu L.; Shao M.
	2013
发表期刊	Journal of Computational and Theoretical Nanoscience
ISSN	ISBN/15461955
卷号	10 期号:10
摘要	A novel robust hybrid meta-heuristic optimization approach, which can be considered as an improvement of the recently developed biogeography based optimization, namely HSBBO, is proposed to solve global numerical optimization problem. HSBBO combines the exploration of harmony search (HS) with the exploitation of BBO effectively, and hence it can generate the promising candidate solutions. The detailed implementation procedure for this improved meta-heuristic method is also described. Fourteen standard benchmark functions are applied to verify the effects of these improvements and it is demonstrated that, in most situations, the performance of this hybrid meta-heuristic method (HSBBO) is superior to or at least highly competitive with the standard BBO and other population-based optimization methods, such as ACO, BBO, DE, ES, GA, HS, PBIL, PSO and SGA. The effect of the HSBBO parameters is also analyzed. Copyright 2013 American Scientific Publishers.
收录类别	SCI ; EI
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/40696
专题	中科院长春光机所知识产出
推荐引用方式 GB/T 7714	Wang G.,Guo L.,Duan H.,et al. Hybridizing harmony search with biogeography based optimization for global numerical optimization[J]. Journal of Computational and Theoretical Nanoscience,2013,10(10).
APA	Wang G.,Guo L.,Duan H.,Wang H.,Liu L.,&Shao M..(2013).Hybridizing harmony search with biogeography based optimization for global numerical optimization.Journal of Computational and Theoretical Nanoscience,10(10).
MLA	Wang G.,et al."Hybridizing harmony search with biogeography based optimization for global numerical optimization".Journal of Computational and Theoretical Nanoscience 10.10(2013).

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