Salīdzināt metodes

	Robust Simulated Annealing	Robustā tabu meklēšana
Nozare	Simulācija	Simulācija
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	1983 (SA); robust variant emerged 1990s–2000s	1989 (TS); robust variant ~2000s
Autors	Kirkpatrick, Gelatt & Vecchi (SA basis); robust formulation developed across the operations research community	Glover, F. (Tabu Search); robustness extensions by various authors
Tips	Metaheuristic with robustness evaluation	Metaheuristic with robustness mechanism
Pirmavots	Kirkpatrick, S., Gelatt, C. D., Vecchi, M. P. (1983). Optimization by simulated annealing. Science, 220(4598), 671-680.	Glover, F. (1989). Tabu search — Part I. ORSA Journal on Computing, 1(3), 190–206.
Citi nosaukumi	RSA, Robust SA, Uncertainty-robust simulated annealing, Worst-case simulated annealing	RTS, Robust TS, Uncertainty-aware Tabu Search, Tabu Search under Uncertainty
Saistītās	5	6
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.	Robust Tabu Search (RTS) extends the classical Tabu Search metaheuristic by evaluating candidate solutions not only on their nominal objective value but also on their performance under uncertainty. Instead of seeking the best solution for a single scenario, RTS seeks solutions that perform well across a range of scenarios or realizations, trading peak optimality for reliability.