Σύγκριση μεθόδων

	Αλγόριθμος Αριθμητικής Βελτιστοποίησης	Αλγόριθμος Μύκητα της Λάσπης
Πεδίο	Βελτιστοποίηση	Βελτιστοποίηση
Οικογένεια	Machine learning	Machine learning
Έτος προέλευσης	2020	2020
Δημιουργός	Laith Abualigah	Shimin Li
Τύπος	Mathematical metaheuristic algorithm	Nature-inspired metaheuristic algorithm
Θεμελιώδης πηγή	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.	Li, S., Chen, H., Wang, M., Heidari, A. A., & Chakraborty, S. (2020). Slime mould algorithm: A new method for stochastic optimization. Future Generation Computer Systems, 111, 300-323.
Εναλλακτικές ονομασίες	AOA	SMA
Συναφείς	5	5
Σύνοψη	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.	The Slime Mould Algorithm (SMA) is a nature-inspired metaheuristic optimization technique introduced by Li et al. in 2020. It mimics the behavior of slime moulds, which spread and contract to find optimal food sources. SMA addresses complex optimization problems by simulating the adaptive foraging and spatial distribution patterns of these organisms.