방법 비교

	Robust Tabu Search	불확실성 하에서도 좋은 성능을 유지하는 해 찾기: 강건 모의 담금질
분야	시뮬레이션	시뮬레이션
계열	Process / pipeline	Process / pipeline
기원 연도	1989 (TS); robust variant ~2000s	1983 (SA); robust variant emerged 1990s–2000s
창시자	Glover, F. (Tabu Search); robustness extensions by various authors	Kirkpatrick, Gelatt & Vecchi (SA basis); robust formulation developed across the operations research community
유형	Metaheuristic with robustness mechanism	Metaheuristic with robustness evaluation
원전	Glover, F. (1989). Tabu search — Part I. ORSA Journal on Computing, 1(3), 190–206.	Kirkpatrick, S., Gelatt, C. D., Vecchi, M. P. (1983). Optimization by simulated annealing. Science, 220(4598), 671-680.
별칭	RTS, Robust TS, Uncertainty-aware Tabu Search, Tabu Search under Uncertainty	RSA, Robust SA, Uncertainty-robust simulated annealing, Worst-case simulated annealing
관련	6	5
요약	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.	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.