Σύγκριση μεθόδων

	Αλγόριθμος Αριθμητικής Βελτιστοποίησης	Γενετικός Αλγόριθμος
Πεδίο	Βελτιστοποίηση	Βελτιστοποίηση
Οικογένεια	Machine learning	Process / pipeline
Έτος προέλευσης	2020	1975
Δημιουργός	Laith Abualigah	John Henry Holland
Τύπος	Mathematical metaheuristic algorithm	Population-based metaheuristic
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.	Holland, J.H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press.
Εναλλακτικές ονομασίες	AOA	GA, evolutionary algorithm, Genetik Algoritma — Evrimsel Optimizasyon
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.	A genetic algorithm (GA) is a population-based metaheuristic optimization method introduced by John Henry Holland (1975) that mimics the principles of natural selection. It maintains a population of candidate solutions and iteratively improves them through selection, crossover, and mutation operators, making it especially powerful on discontinuous, non-convex, and multi-modal search spaces where classical gradient-based methods fail.