A novel approach for nature-based optimization algorithms: The threat factor approach

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dc.authorid0000-0001-9752-2718en_US
dc.authorid0000-0001-9402-8490en_US
dc.contributor.authorToz, Metin
dc.contributor.authorToz, Güliz
dc.date.accessioned2021-05-18T12:43:14Z
dc.date.available2021-05-18T12:43:14Z
dc.date.issued2021en_US
dc.departmentKMÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.descriptionWOS:000644953400001en_US
dc.description.abstractNature-inspired optimization algorithms especially those based on the hunting behaviors of the creatures assume that the hunting operations are performed in a safe environment. However, generally, there are threats in real-life for the hunter-animals. This paper focuses on these threat factors and proposes that they can be used to improve the searching abilities of the algorithms. Gray wolf optimization (GWO) algorithm was selected to present the proposed approach and it was assumed that there was a mountain lion as the threat factor living in the same habitat with the wolf pack. The relations between the two predators were modeled and used to improve the performance of the algorithm. Five experiments were conducted to test the performance of the proposed method and the results were compared with the GWO and four optimization algorithms from the literature. It is shown that the proposed algorithm obtained best results for 21 of the 50 benchmark functions, while its closest competitor achieved the best results for 16 functions. Besides, the results of the Wilcoxon signed-rank test indicated that the proposed method is superior to all other methods. In addition, it was shown that the threat factor approach does not cause a significant increase in the processing time.en_US
dc.identifier.citationToz, M., Toz, G. (2021). A novel approach for nature-based optimization algorithms: The threat factor approach. Concurrency and Computation-Practice & Experienceen_US
dc.identifier.doi10.1002/cpe.6341
dc.identifier.issn1532-0626
dc.identifier.issn1532-0634
dc.identifier.scopus2-s2.0-85115273073
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1002/cpe.6341
dc.identifier.urihttps://hdl.handle.net/11492/5002
dc.identifier.wosWOS:000644953400001
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Sceince
dc.indekslendigikaynakScopus
dc.institutionauthorToz, Metin
dc.institutionauthorToz, Güliz
dc.language.isoen
dc.publisherWileyen_US
dc.relation.journalConcurrency and Computation-Practice & Experienceen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectGWO Algorithmen_US
dc.subjectNature&#8208en_US
dc.subjectInspired Optimizationen_US
dc.subjectThreat Factor Approachen_US
dc.titleA novel approach for nature-based optimization algorithms: The threat factor approachen_US
dc.typeArticle

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