Σύγκριση μεθόδων

	Προσομοιωμένη Ανόπτηση	Διαφορική Εξέλιξη
Πεδίο	Βελτιστοποίηση	Βελτιστοποίηση
Οικογένεια	Process / pipeline	Process / pipeline
Έτος προέλευσης	1983	1997
Δημιουργός	—	Rainer Storn & Kenneth Price
Τύπος	Probabilistic metaheuristic / local search	Population-based stochastic metaheuristic
Θεμελιώδης πηγή	Kirkpatrick, S., Gelatt, C.D. & Vecchi, M.P. (1983). Optimization by Simulated Annealing. Science, 220(4598), 671-680.	Storn, R. & Price, K. (1997). Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces. Journal of Global Optimization, 11(4), 341–359.
Εναλλακτικές ονομασίες	Benzetimli Tavlama (Simulated Annealing), SA, probabilistic local search	DE algorithm, Diferansiyel Evrim (DE), DE optimization
Συναφείς	5	5
Σύνοψη	Simulated annealing is a probabilistic local-search metaheuristic introduced by Kirkpatrick, Gelatt, and Vecchi in 1983. It models the physical annealing process in metallurgy — where a material is heated and then slowly cooled to reach a low-energy crystalline state — and uses this analogy to escape local optima in combinatorial and continuous optimization problems.	Differential Evolution (DE), introduced by Rainer Storn and Kenneth Price in 1997, is a population-based stochastic optimisation algorithm designed for continuous parameter spaces. It generates candidate solutions by combining vector differences between existing population members, making it a powerful and parameter-lean alternative to Genetic Algorithms and Particle Swarm Optimisation when the search landscape is non-convex, multimodal, or poorly suited to gradient-based methods.