Advances in sand cat swarm optimization: a comprehensive study
Yükleniyor...
Dosyalar
Tarih
2025
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer science and business media B.V.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This 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.
Açıklama
Anahtar Kelimeler
Kaynak
Archives of computational methods in engineering
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
Sayı
Künye
Anka, F., & Aghayev, N. (2025). Advances in Sand Cat Swarm Optimization: A Comprehensive Study. Archives of Computational Methods in Engineering, 1-44.
