Salīdzināt metodes

	Robust Simulated Annealing	Simulated Annealing
Nozare	Simulācija	Optimizācija
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	1983 (SA); robust variant emerged 1990s–2000s	1983
Autors	Kirkpatrick, Gelatt & Vecchi (SA basis); robust formulation developed across the operations research community	—
Tips	Metaheuristic with robustness evaluation	Probabilistic metaheuristic / local search
Pirmavots	Kirkpatrick, S., Gelatt, C. D., Vecchi, M. P. (1983). Optimization by simulated annealing. Science, 220(4598), 671-680.	Kirkpatrick, S., Gelatt, C.D. & Vecchi, M.P. (1983). Optimization by Simulated Annealing. Science, 220(4598), 671-680.
Citi nosaukumi	RSA, Robust SA, Uncertainty-robust simulated annealing, Worst-case simulated annealing	Benzetimli Tavlama (Simulated Annealing), SA, probabilistic local search
Saistītās	5	5
Kopsavilkums	Robust Simulated Annealing (RSA) adapts the classical simulated annealing metaheuristic to seek solutions that perform well not just under nominal conditions but across the full range of uncertain or adversarial parameter values. By embedding a robustness evaluation — worst-case, expected-case, or regret-based — into the SA acceptance step, RSA trades some nominal optimality for resilience, making it valuable when problem parameters are imprecisely known or subject to environmental variation.	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.