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A heuristic optimization method inspired by wolf preying behavior
Simon Fong1; Suash Deb2; Xin-She Yang3
2015-10
Source PublicationNeural Computing and Applications
ISSN0941-0643
Volume26Issue:7Pages:1725–1738
Abstract

Optimization problems can become intractable when the search space undergoes tremendous growth. Heuristic optimization methods have therefore been created that can search the very large spaces of candidate solutions. These methods, also called metaheuristics, are the general skeletons of algorithms that can be modified and extended to suit a wide range of optimization problems. Various researchers have invented a collection of metaheuristics inspired by the movements of animals and insects (e.g., firefly, cuckoos, bats and accelerated PSO) with the advantages of efficient computation and easy implementation. This paper studies a relatively new bio-inspired heuristic optimization algorithm called the Wolf Search Algorithm (WSA) that imitates the way wolves search for food and survive by avoiding their enemies. The WSA is tested quantitatively with different values of parameters and compared to other metaheuristic algorithms under a range of popular non-convex functions used as performance test problems for optimization algorithms, with superior results observed in most tests. 

KeywordBio-inspired Optimization Metaheuristic Wolf Search Algorithm
DOIhttps://doi.org/10.1007/s00521-015-1836-9
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000360005900017
PublisherSPRINGER LONDON LTD, 236 GRAYS INN RD, 6TH FLOOR, LONDON WC1X 8HL, ENGLAND
The Source to ArticleScopus
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Citation statistics
Cited Times [WOS]:29   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorSimon Fong; Suash Deb; Xin-She Yang
Affiliation1.Department of Computer and Information Science, University of Macau, Taipa, Macau SAR
2.Department of Computer Science and Engineering, Cambridge Institute of Technology, Ranchi, India
3.School of Design engineering and Mathematics, Middlesex University, London, UK
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Simon Fong,Suash Deb,Xin-She Yang. A heuristic optimization method inspired by wolf preying behavior[J]. Neural Computing and Applications,2015,26(7):1725–1738.
APA Simon Fong,Suash Deb,&Xin-She Yang.(2015).A heuristic optimization method inspired by wolf preying behavior.Neural Computing and Applications,26(7),1725–1738.
MLA Simon Fong,et al."A heuristic optimization method inspired by wolf preying behavior".Neural Computing and Applications 26.7(2015):1725–1738.
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