Metaheuristic Algorithms: Optimal Balance of Intensification and Diversification
Xin-She Yang1; Suash Deb2; Simon Fong3
2014-05-01
Source PublicationApplied Mathematics and Information Sciences
ISSN1935-0090
Volume8Issue:3Pages:977-983
Abstract

In nature-inspired metaheuristic algorithms, two key components are local intensification and global diversification, and their interaction can significantly affect the efficiency of a metaheuristic algorithm. However, there is no rule for how to balance these important components. In this paper, we provide a first attempt to give some theoretical basis for the optimal balance of exploitation and exploration for 2D multimodal objective functions. Then, we use it for choosing algorithm-dependent parameters. Finally, we use the recently developed eagle strategy and cuckoo search to solve two benchmarks so as to confirm if the optimal balance can be achieved in higher dimensions. For multimodal problems, computational effort should focus on the global explorative search, rather than intensive local search. We also briefly discuss the implications for further research. 

KeywordCuckoo Search Eagle Strategy Metaheuristic Performance Evaluation
DOIhttp://dx.doi.org/10.12785/amis/080306
URLView the original
Indexed BySCIE
Language英语
WOS Research AreaMathematics ; Physics
WOS SubjectMathematics, Applied ; Physics, Mathematical
WOS IDWOS:000331387600006
PublisherNATURAL SCIENCES PUBLISHING CORP-NSP, 19 W 34 ST, SUITE 1018, NEW YORK, NY 10001 USA
The Source to ArticleScopus
Fulltext Access
Citation statistics
Cited Times [WOS]:43   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.School of Science and Technology, Middlesex University, London NW4 4BT, UK
2.Department of Computer Science and Engineering, Cambridge Institute of Technology, Ranchi, India
3.Department of Computer and Information Science, University of Macau, Macau SAR
Recommended Citation
GB/T 7714
Xin-She Yang,Suash Deb,Simon Fong. Metaheuristic Algorithms: Optimal Balance of Intensification and Diversification[J]. Applied Mathematics and Information Sciences,2014,8(3):977-983.
APA Xin-She Yang,Suash Deb,&Simon Fong.(2014).Metaheuristic Algorithms: Optimal Balance of Intensification and Diversification.Applied Mathematics and Information Sciences,8(3),977-983.
MLA Xin-She Yang,et al."Metaheuristic Algorithms: Optimal Balance of Intensification and Diversification".Applied Mathematics and Information Sciences 8.3(2014):977-983.
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