Methoden vergleichen

	African Vultures Optimization Algorithm	Slime Mould Algorithm
Fachgebiet	Optimierung	Optimierung
Familie	Machine learning	Machine learning
Entstehungsjahr	2020	2020
Urheber	Hossein Moghdani	Shimin Li
Typ	Nature-inspired metaheuristic algorithm	Nature-inspired metaheuristic algorithm
Wegweisende Quelle	Moghdani, H., & Salimifard, K. (2020). Volleyball player optimizer and African vultures optimization algorithms for solving global optimization problems. Applied Soft Computing, 97, 106794.	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.
Aliasnamen	AVOA	SMA
Verwandt	4	5
Zusammenfassung	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 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.