Dynamic group optimization algorithm with embedded chaos
Tang R.1; Fong S.1; Wong R.K.4; Wong K.K.L.3
Source PublicationIEEE Access
AbstractRecently, a new algorithm named dynamic group optimization (DGO) has been proposed, which is developed to mimic the behaviors of animal and human group socializing. However, one of the major drawbacks of the DGO is the premature convergence. Therefore, in order to deal with this challenge, we introduce chaos theory into the DGO algorithm and come up with a new chaotic dynamic group optimization algorithm (CDGO) that can accelerate the convergence of DGO. Various chaotic maps are used to adjust the update of solutions in CDGO. Extensive experiments have been carried out, and the results have shown that CDGO can be a very promising tool for solving optimization algorithms. We also demonstrated good results based on real world data, where, in particular, solving multimedia data clustering problems.
KeywordChaos convergence dynamic group optimization heuristic algorithms
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Cited Times [WOS]:1   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Affiliation1.Universidade de Macau
2.Western Sydney University
3.The University of Adelaide
4.University of New South Wales (UNSW) Australia
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GB/T 7714
Tang R.,Fong S.,Wong R.K.,et al. Dynamic group optimization algorithm with embedded chaos[J]. IEEE Access,2018,6:22728-22743.
APA Tang R.,Fong S.,Wong R.K.,&Wong K.K.L..(2018).Dynamic group optimization algorithm with embedded chaos.IEEE Access,6,22728-22743.
MLA Tang R.,et al."Dynamic group optimization algorithm with embedded chaos".IEEE Access 6(2018):22728-22743.
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