COMPARISON OF METAHEURISTIC ALGORITHMS WITH DIFFERENT PERFORMANCE CRITERIA

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dc.contributor.authorZoralioğlu, Yıldız
dc.contributor.authorArslan, Sibel
dc.date.accessioned2024-10-26T17:43:09Z
dc.date.available2024-10-26T17:43:09Z
dc.date.issued2023
dc.departmentSivas Cumhuriyet Üniversitesi
dc.description.abstractNature-inspired metaheuristic algorithms are widely used because they achieve successful results in difficult optimization problems. Their popularity has led to the development of new metaheuristics for solving different engineering problems. New metaheuristics lead scientific research by providing faster and more efficient results. In this study, Artificial Rabbit Algorithm (ARO), Dwarf Mongoose Algorithm (DMO) and Genetic Algorithm (GA), which are recently developed metaheuristics, are compared. According to the literature review, the performances of these three algorithms are compared for the first time. Single and multi-modal standard quality test functions were used to evaluate the algorithms. The results of the algorithms were checked by t-test to see if there is a significant difference in terms of the functions used. According to the results obtained, it was observed that ARO produced more successful results than the other algorithms compared. This shows that the newly developed metaheuristics can be used in many engineering problems.
dc.identifier.doi10.54365/adyumbd.1344257
dc.identifier.endpage275
dc.identifier.issn2149-0309
dc.identifier.issue21
dc.identifier.startpage266
dc.identifier.trdizinid1217223
dc.identifier.urihttps://doi.org/10.54365/adyumbd.1344257
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/1217223
dc.identifier.urihttps://hdl.handle.net/20.500.12418/25046
dc.identifier.volume10
dc.indekslendigikaynakTR-Dizin
dc.language.isoen
dc.relation.ispartofAdıyaman Üniversitesi Mühendislik Bilimleri Dergisi
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectGenetic Algorithm
dc.subjectMetaheuristic Algorithms
dc.subjectArtificial Rabbit Algorithm
dc.subjectDwarf Mongoose Algorithm
dc.subjectQuality Test Functions
dc.titleCOMPARISON OF METAHEURISTIC ALGORITHMS WITH DIFFERENT PERFORMANCE CRITERIA
dc.typeArticle

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