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Gaussian guided self-adaptivewolf search algorithm based on information entropy theory
Qun Song1; Simon Fong1; Suash Deb2; Thomas Hanne3
2018-01-10
Source PublicationEntropy
ISSN1099-4300
Volume20Issue:1
Abstract

Nowadays, swarm intelligence algorithms are becoming increasingly popular for solving many optimization problems. The Wolf Search Algorithm (WSA) is a contemporary semi-swarm intelligence algorithm designed to solve complex optimization problems and demonstrated its capability especially for large-scale problems. However, it still inherits a common weakness for other swarm intelligence algorithms: that its performance is heavily dependent on the chosen values of the control parameters. In 2016, we published the Self-AdaptiveWolf Search Algorithm (SAWSA), which offers a simple solution to the adaption problem. As a very simple schema, the original SAWSA adaption is based on random guesses, which is unstable and naive. In this paper, based on the SAWSA, we investigate the WSA search behaviour more deeply. A new parameter-guided updater, the Gaussian-guided parameter control mechanism based on information entropy theory, is proposed as an enhancement of the SAWSA. The heuristic updating function is improved. Simulation experiments for the new method denoted as the Gaussian-Guided Self-Adaptive Wolf Search Algorithm (GSAWSA) validate the increased performance of the improved version of WSA in comparison to its standard version and other prevalent swarm algorithms.

KeywordSwarm Intelligence Algorithms Wolf Search Algorithm Self-adaptation Entropy-guided Parameter Control
DOI10.3390/e20010037
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaPhysics
WOS SubjectPhysics, Multidisciplinary
WOS IDWOS:000424876200037
PublisherMDPI AG, ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
Fulltext Access
Citation statistics
Cited Times [WOS]:1   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorSimon Fong
Affiliation1.Department of Computer and Information Science, University of Macau, Macau 999078, China
2.Decision Sciences and Modelling Program, Victoria University, Melbourne 8001, Australia
3.Institute for Information Systems, University of Applied Sciences and Arts Northwestern Switzerland, 4600 Olten, Switzerland
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Qun Song,Simon Fong,Suash Deb,et al. Gaussian guided self-adaptivewolf search algorithm based on information entropy theory[J]. Entropy,2018,20(1).
APA Qun Song,Simon Fong,Suash Deb,&Thomas Hanne.(2018).Gaussian guided self-adaptivewolf search algorithm based on information entropy theory.Entropy,20(1).
MLA Qun Song,et al."Gaussian guided self-adaptivewolf search algorithm based on information entropy theory".Entropy 20.1(2018).
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