Improved Whale Optimization Algorithm Based On π Number
Öz
Anahtar Kelimeler
Whale Optimization Algorithm, Benchmark Functions, optimization
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.
- [9] Kennedy J, Eberhart R. “Particle swarm optimization,” In: Proceedings of the 1995 IEEE international conference on neural networks, Australia, 1942–1948, 1995.
- [10] Basturk B, Karaboga D. “An artificial bee colony (ABC) algorithm for numeric function optimization,” In: Proceedings of the IEEE swarm intelligence symposium, Indianapolis, USA, 12–14 May 2006.