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Optimizing self-adaptive gender ratio of elephant search algorithm by min-max strategy
Zhonghuan Tian1; Simon Fong1; Raymond Wong2; Millham R.3
2016-10-24
Conference Name2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)
Source Publication2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2016
Pages121-126
Conference Date13-15 Aug. 2016
Conference PlaceChangsha, China
PublisherIEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Abstract

Elephant Search Algorithm (ESA) is one of the contemporary metaheuristic search recently proposed. Its efficacy depends largely on the right choice of gender ratio that balances the proportion between the number of male and female elephants as search agents with different functions. The male elephants are responsible for global exploration, roaming to new dimensions of search space. The female elephants focus on doing local search, for finding the optimal solution. The value for this gender ratio however needs to be manually chosen in the original version of ESA. An automatic mechanism for finding the appropriate gender ratio ESA agents is proposed in this paper. A self-adaptive method guided by min-max strategy is used to search for the optimal gender ratio of ESA. The self-adaptive method is simulated on nine optimization testing functions with different dimensions. Compared with enumerated global-best ratio, the self-adaptive ratio obtained by our method can save 90% of computation time at the cost of 20% compromise in fitness value in most testing functions. Simulation results are also compared with classical meta-heuristic algorithms including PSO, Firefly and WSA. ESA's performance with min-max ratio is also comparable towards these algorithms.

KeywordElephant Search Algorithm Parameter Tuning Self-adaptive Min-max Strategy Meta-heuristics
DOI10.1109/FSKD.2016.7603161
URLView the original
Indexed ByCPCI-S
Language英語English
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000386658300021
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Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.Department of Computer and Information Science University of Macau Taipa, Macau SAR
2.School of Computer Science and Engineering University of New South Wales Sydney, Australia
3.ICT and Society Research Group Department of Information Technology Durban University of Technology, Durban, South Africa
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Zhonghuan Tian,Simon Fong,Raymond Wong,et al. Optimizing self-adaptive gender ratio of elephant search algorithm by min-max strategy[C]:IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA,2016:121-126.
APA Zhonghuan Tian,Simon Fong,Raymond Wong,&Millham R..(2016).Optimizing self-adaptive gender ratio of elephant search algorithm by min-max strategy.2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2016,121-126.
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