A chaotic optimization method based on logistic-sine map for numerical function optimization

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dc.authoridKocamaz, Adnan Fatih/0000-0002-7729-8322
dc.authoriddemir, fahrettin burak/0000-0001-9095-5166;
dc.authorwosidKocamaz, Adnan Fatih/C-2820-2014
dc.authorwosiddemir, fahrettin burak/ABG-1147-2020
dc.authorwosidTUNCER, Türker/ABG-1146-2020
dc.authorwosidTUNCER, Turker/W-4846-2018
dc.contributor.authorDemir, Fahrettin Burak
dc.contributor.authorTuncer, Turker
dc.contributor.authorKocamaz, Adnan Fatih
dc.date.accessioned2024-08-04T20:47:12Z
dc.date.available2024-08-04T20:47:12Z
dc.date.issued2020
dc.departmentİnönü Üniversitesien_US
dc.description.abstractMeta-heuristic optimization algorithms have been used to solve mathematically unidentifiable problems. The main purpose of the optimization methods on problem-solving is to choose the best solution in predefined conditions. To increase performance of the optimization methods, chaotic maps for instance Logistic, Singer, Sine, Tent, Chebyshev, Circle have been widely used in the literature. However, hybrid 1D chaotic maps have higher performance than the 1D chaotic maps. The hybrid chaotic maps have not been used in the optimization process. In this article, 1D hybrid chaotic map (logistic-sine map)-based novel swarm optimization method is proposed to achieve higher numerical results than other optimization methods. Logistic-sine map has good statistical result, and this advantage is used directly to calculate global optimum value in this study. The proposed algorithm is a swarm-based optimization algorithm, and the seed value of the logistic-sine map is generated from local best solutions to reach global optimum. In order to test the proposed hybrid chaotic map-based optimization method, widely used numerical benchmark functions are chosen. The proposed chaotic optimization method is also tested on compression spring design problem. Results and comparisons clearly show that the proposed chaotic optimization method is successful.en_US
dc.identifier.doi10.1007/s00521-020-04815-9
dc.identifier.endpage14239en_US
dc.identifier.issn0941-0643
dc.identifier.issn1433-3058
dc.identifier.issue17en_US
dc.identifier.scopus2-s2.0-85081591433en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage14227en_US
dc.identifier.urihttps://doi.org/10.1007/s00521-020-04815-9
dc.identifier.urihttps://hdl.handle.net/11616/99222
dc.identifier.volume32en_US
dc.identifier.wosWOS:000560557000072en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer London Ltden_US
dc.relation.ispartofNeural Computing & Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectChaotic optimizationen_US
dc.subjectLogistic-sine mapen_US
dc.subjectSwarm-based optimizationen_US
dc.subjectChaosen_US
dc.titleA chaotic optimization method based on logistic-sine map for numerical function optimizationen_US
dc.typeArticleen_US

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