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Soft Computing

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27.05.2015 | Focus

Chaotic cuckoo search

verfasst von: Gai-Ge Wang, Suash Deb, Amir H. Gandomi, Zhaojun Zhang, Amir H. Alavi

Erschienen in: Soft Computing | Ausgabe 9/2016

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Abstract

This study proposes a novel chaotic cuckoo search (CCS) optimization method by incorporating chaotic theory into cuckoo search (CS) algorithm. In CCS, chaos characteristics are combined with the CS with the intention of further enhancing its performance. Further, the elitism scheme is incorporated into CCS to preserve the best cuckoos. In CCS method, 12 chaotic maps are applied to tune the step size of the cuckoos used in the original CS method. Twenty-seven benchmark functions and an engineering case are utilized to investigate the efficiency of CCS. The results clearly demonstrate that the performance of CCS together with a suitable chaotic map is comparable as well as superior to that of the CS and other metaheuristic algorithms.

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Titel: Chaotic cuckoo search
verfasst von: Gai-Ge Wang
Suash Deb
Amir H. Gandomi
Zhaojun Zhang
Amir H. Alavi
Publikationsdatum: 27.05.2015
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 9/2016
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-015-1726-1

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