Improved Whale Optimization Algorithm Based On π Number
Öz
Anahtar Kelimeler
Teşekkür
Kaynakça
- [1] Alatas, B. “ACROA: Artificial Chemical Reaction Optimization Algorithm for global optimization.” Expert Systems with Applications 38, 13170–13180, 2011.
- [2] Hatamlou A. “Black hole: a new heuristic optimization approach for data clustering,” Inf Sci, 222:175–184. 2013.
- [3] Huang F, Wang L, He Q. “An effective co-evolutionary differential evolution for constrained optimization,” Appl Math Computation, 186(1), 340–356, 2007.
- [4] Kirkpatrick S, Gelatt CD, Vecchi MP. “Optimization by simulated annealing,” Science, 220(4598), 671–680. 1983.
- [5] CernýV. “Thermodynamical approach to the traveling salesman problem: an efficient simulation algorithm,” Journal of Optimization Theory and Applications, 45(1), 41–51, 1985.
- [6] Rashedi E, Nezamabadi-Pour H, Saryazdi S. “GSA: a gravitational search algorithm,” Inf Sci, 179,2232–2248,2009.
- [7] Mirjalili, S., Mirjalili, S. M., & Hatamlou, “A. Multi-verse optimizer: a nature-inspired algorithm for global optimization” Neural Computing and Applications, 27(2), 495-513. 2016.
- [8] Dorigo M, Birattari M, Stutzle T. “Ant colony optimization,” IEEE Comput Intell, 1(4), 28–39. 2006.
Ayrıntılar
Birincil Dil
İngilizce
Konular
Yapay Zeka
Bölüm
Araştırma Makalesi
Yazarlar
Bahadur Alızada
*
0000-0001-6587-4057
Azerbaijan
Yayımlanma Tarihi
30 Haziran 2020
Gönderilme Tarihi
18 Aralık 2019
Kabul Tarihi
10 Mayıs 2020
Yayımlandığı Sayı
Yıl 2020 Cilt: 4 Sayı: 1