So sánh phương pháp

	Thuật toán Lửng mật (Honey Badger Algorithm - HBA)	Aquila Optimizer
Lĩnh vực	Tối ưu hóa	Tối ưu hóa
Họ	Machine learning	Machine learning
Năm ra đời	2023	2021
Người khởi xướng	Fatma A. Hashim	Laith Abualigah
Loại	Nature-inspired metaheuristic algorithm	Nature-inspired metaheuristic algorithm
Công trình gốc	Hashim, F. A., Hussain, K., & Houssein, E. H. (2023). Honey badger algorithm: A new meta-heuristic optimization algorithm. Neural Computing and Applications, 35(17), 12265-12287.	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.
Tên gọi khác	HBA	AO
Liên quan	5	3
Tóm tắt	The Honey Badger Algorithm (HBA) is a nature-inspired metaheuristic optimization algorithm presented by Hashim et al. in 2023, modeled on the hunting behavior and intelligent strategies of honey badgers (Mellivora capensis). Honey badgers are known for their remarkable problem-solving abilities, fearlessness, and persistent pursuit of prey and food sources despite significant obstacles. HBA captures these behavioral traits to create 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.