Advances in sand cat swarm optimization: a comprehensive study

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dc.authorscopusidNazim Aghayev / 57218511472
dc.authorwosidNazim Aghayev / IRZ-3970-2023
dc.contributor.authorAnka, Ferzat
dc.contributor.authorAghayev, Nazim
dc.date.accessioned2025-04-17T14:17:34Z
dc.date.available2025-04-17T14:17:34Z
dc.date.issued2025
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Matematik Bölümü
dc.description.abstractThis study provides an in-depth review and analysis of the nature-inspired Sand Cat Swarm Optimization (SCSO) algorithm. The SCSO algorithm effectively focuses on exploring solution areas inspired by sand cat hearing and finding the most suitable solutions for their hunting behavior. This algorithm is easily adaptable to various problems due to its stability, low-cost, flexibility, simple implementation, simplicity, derivative-free mechanism, and reasonable computation time. For these reasons, although it was published recently, it has begun to attract the attention of researchers. SCSO-based research has been presented in prestigious international journals such as Elsevier, Springer, MDPI, and IEEE since its inception in 2022. The studies cited in this paper are examined in three categories: improved, hybrid, and adapted. Research trends show that 39, 21, and 40% of SCSO-based studies fall into these three categories, respectively. Additionally, research on solving various problems inspired by the SCSO algorithm is discussed from two different perspectives: global optimizations and real-world applications. Analysis of the applications shows that 15 and 85% of the studies belong to these two fields, respectively.
dc.identifier.citationAnka, F., & Aghayev, N. (2025). Advances in Sand Cat Swarm Optimization: A Comprehensive Study. Archives of Computational Methods in Engineering, 1-44.
dc.identifier.doi10.1007/s11831-024-10217-0
dc.identifier.issn1134-3060
dc.identifier.issn1886-1784
dc.identifier.scopus2-s2.0-85214141389
dc.identifier.scopusqualityQ1
dc.identifier.urihttp://dx.doi.org/10.1007/s11831-024-10217-0
dc.identifier.urihttps://hdl.handle.net/20.500.12713/6292
dc.identifier.wosWOS:001388938000001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorAghayev, Nazim
dc.institutionauthoridNazim Aghayev / 0000-0002-6466-4274
dc.language.isoen
dc.publisherSpringer science and business media B.V.
dc.relation.ispartofArchives of computational methods in engineering
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.titleAdvances in sand cat swarm optimization: a comprehensive study
dc.typeArticle

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