WOASCALF: A new hybrid whale optimization algorithm based on sine cosine algorithm and levy flight to solve global optimization problems

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dc.authoridAmir Seyyedabbasi / 0000-0001-5186-4499en_US
dc.authorscopusidAmir Seyyedabbasi / 57202833910en_US
dc.authorwosidAmir Seyyedabbasi / GFG-1335-2022
dc.contributor.authorSeyyedabbasi, Amir
dc.date.accessioned2022-10-28T06:30:19Z
dc.date.available2022-10-28T06:30:19Z
dc.date.issued2022en_US
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Yazılım Mühendisliği Bölümüen_US
dc.description.abstractIn recent years, researchers have been focused on solving optimization problems in order to determine the global optimum. Increasing the dimension of a problem increases its computational cost and complexity as well. In order to solve these types of problems, metaheuristic algorithms are used. The whale optimization algorithm (WOA) is one of the most well-known algorithms based on whale hunting behavior. In this paper, the WOA algorithm is combined with the Sine Cosine Algorithm (SCA), which is based on the principle of trigonometric sine-cosine. The WOA algorithm has superior performance in the exploration phase in contrast with the exploitation phase, whereas the SCA algorithm has weaknesses in the exploitation phase. The levy flight distribution has been used in the hybrid WOA and SCA algorithm to improve these deficiencies. This study introduced a novel hybrid algorithm named WOASCALF. In this algorithm, the search agents' position updates are based on a hybridization of the WOA, SCA, and levy flight. Each of these metaheuristic algorithms has reasonable performance, however, the Levy distribution caused small and large distance leaps in each phase of the algorithm. Thus, it is possible for the appropriate search agent to move in different directions of the search space. The performance of the WOASCALF has been evaluated by the 23 well-known benchmark functions and three real-world engineering problems. The result analysis demonstrates that the exploration ability of WOASCALF has strong superiority over other compared algorithms.en_US
dc.identifier.citationSeyyedabbasi, A. (2022). WOASCALF: A new hybrid whale optimization algorithm based on sine cosine algorithm and levy flight to solve global optimization problems. Advances in Engineering Software, 173 doi:10.1016/j.advengsoft.2022.103272en_US
dc.identifier.doi10.1016/j.advengsoft.2022.103272en_US
dc.identifier.scopus2-s2.0-85138144765en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1016/j.advengsoft.2022.103272
dc.identifier.urihttps://hdl.handle.net/20.500.12713/3204
dc.identifier.volume173en_US
dc.identifier.wosWOS:000864730800004en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorSeyyedabbasi, Amir
dc.language.isoenen_US
dc.publisherElsevier Ltden_US
dc.relation.ispartofAdvances in Engineering Softwareen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectHybrid Metaheuristic Algorithmen_US
dc.subjectLevy Flight Distributionen_US
dc.subjectSCAen_US
dc.subjectWOAen_US
dc.titleWOASCALF: A new hybrid whale optimization algorithm based on sine cosine algorithm and levy flight to solve global optimization problemsen_US
dc.typeArticleen_US

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