השוואת שיטות

	אלגוריתם אופטימיזציית נשרים אפריקאים	ממטב-טבע אלגוריתם האופטימיזציה אקווילה (Aquila Optimizer - AO)
תחום	אופטימיזציה	אופטימיזציה
משפחה	Machine learning	Machine learning
שנת המקור	2020	2021
הוגה השיטה	Hossein Moghdani	Laith Abualigah
סוג	Nature-inspired metaheuristic algorithm	Nature-inspired metaheuristic algorithm
מקור מכונן	Moghdani, H., & Salimifard, K. (2020). Volleyball player optimizer and African vultures optimization algorithms for solving global optimization problems. Applied Soft Computing, 97, 106794.	Abualigah, L., Yousri, D., Abd Elaziz, M., Ewees, A. A., Al-qaness, M. A., & Gandomi, A. H. (2021). Aquila optimizer: A novel meta-heuristic optimization algorithm. Computers and Industrial Engineering, 157, 107250.
כינויים	AVOA	AO
קשורות	4	3
תקציר	The African Vultures Optimization Algorithm (AVOA) is a metaheuristic algorithm introduced by Moghdani and Salimifard in 2020, inspired by the search and scavenging behavior of African vultures. Vultures employ sophisticated collaborative strategies to locate carrion across vast distances, using thermal air currents and group dynamics to navigate efficiently. AVOA translates these collective hunting behaviors into an effective optimization framework.	The Aquila Optimizer (AO) is a nature-inspired metaheuristic algorithm presented by Abualigah et al. in 2021, modeled after the hunting behavior and sensory abilities of golden eagles (aquila chrysaetos). The algorithm captures the exploration and exploitation phases of eagle hunting, including high-altitude soaring, exploration with high-precision vision, and rapid diving attacks. AO is designed to solve both constrained and unconstrained optimization problems.