विधियों की तुलना करें

	अंकगणितीय अनुकूलन एल्गोरिथम	हैरिस हॉक्स ऑप्टिमाइजेशन
क्षेत्र	अनुकूलन	अनुकूलन
परिवार	Machine learning	Machine learning
उद्भव वर्ष	2020	2019
प्रवर्तक	Laith Abualigah	Ali Asghar Heidari
प्रकार	Mathematical metaheuristic algorithm	Nature-inspired metaheuristic algorithm
मौलिक स्रोत	Abualigah, L., Yousri, D., Abd Elaziz, M., Ewees, A. A., Al-qaness, M. A., & Gandomi, A. H. (2021). Arithmetic optimization algorithm: A new metaheuristic algorithm for solving optimization problems. Applied Mathematics and Computation, 392, 125450.	Heidari, A. A., Mirjalili, S., Faris, H., Aljarah, I., Mafarja, M., & Chen, H. (2019). Harris hawks optimization: Algorithm and applications. Future Generation Computer Systems, 97, 849-872.
उपनाम	AOA	HHO
संबंधित	5	4
सारांश	The Arithmetic Optimization Algorithm (AOA) is a metaheuristic optimization approach introduced by Abualigah et al. in 2020 that leverages mathematical operators (multiplication, division, addition, subtraction) as the inspiration for search strategies. Unlike nature-inspired algorithms, AOA uses the inherent properties of arithmetic operations to balance exploration and exploitation, making it particularly effective for mathematical optimization problems.	Harris Hawks Optimization (HHO) is a metaheuristic algorithm introduced by Heidari et al. in 2019, inspired by the hunting strategies of Harris's hawks. The algorithm models the cooperative hunting behavior and escape strategies of these raptors to solve complex optimization problems. HHO balances exploration through perching and exploitation through dynamic pursuit, making it effective for multimodal and high-dimensional optimization.