Whale optimization algorithm for numerical constrained optimization

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dc.contributor.authorÇelik, Yuksel
dc.contributor.authorKaradeniz, Alper Talha
dc.date.accessioned2024-09-29T16:32:21Z
dc.date.available2024-09-29T16:32:21Z
dc.date.issued2020
dc.departmentKarabük Üniversitesien_US
dc.description.abstractWhale Optimization Algorithm (WOA), WOA is a recently developed, nature-inspired, meta-heuristic optimization algorithm. The algorithm was developed in 2016, inspired by bubble hunting strategies used by humpback whales. To determine the performance of each optimization algorithm developed, they should be tested on a different type of optimization test problems. In this paper, we aim to investigate and analyse WOA logarithm on constrained optimization the performance and accuracy of the proposed method are examined on 13 (G1-G13) constrained numerical benchmark functions, and the obtained results are compared with other meta-heuristic optimization algorithms which taken from the literature. The experimental results show that WOA has low performance on constrained optimization.en_US
dc.identifier.endpage554en_US
dc.identifier.issn2147-4575
dc.identifier.issue3en_US
dc.identifier.startpage547en_US
dc.identifier.trdizinid467747en_US
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/467747
dc.identifier.urihttps://hdl.handle.net/20.500.14619/11579
dc.identifier.volume8en_US
dc.indekslendigikaynakTR-Dizinen_US
dc.language.isoenen_US
dc.relation.ispartofACADEMIC PLATFORM-JOURNAL OF ENGINEERING AND SCIENCEen_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.titleWhale optimization algorithm for numerical constrained optimizationen_US
dc.typeArticleen_US

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