방법 비교

	강건 이산 사건 시뮬레이션	심층 불확실성 하에서의 최악의 경우 및 최소 최대 후회 평가를 포함한 강건 시나리오 분석
분야	시뮬레이션	시뮬레이션
계열	Process / pipeline	Process / pipeline
기원 연도	1990s–2000s	1950 (foundations); 2003 (modern RDM formulation)
창시자	Banks, Carson, Nelson, Nicol (canonical DES); robust extensions: operations research community	Wald, A. (minimax foundation); Lempert et al. (RDM framework)
유형	Simulation with robustness analysis	Scenario-based robustness evaluation
원전	Banks, J., Carson, J. S., Nelson, B. L., & Nicol, D. M. (2010). Discrete-Event System Simulation (5th ed.). Prentice Hall. ISBN: 9780136062127	Wald, A. (1950). Statistical Decision Functions. Wiley, New York.
별칭	Robust DES, Uncertainty-Aware DES, Robust DEVS, Resilient Discrete-Event Simulation	RSA, Robust Scenario Planning, Worst-Case Scenario Analysis, Minimax Regret Scenario Analysis
관련	6	5
요약	Robust Discrete-Event Simulation (Robust DES) is a simulation methodology that extends classical discrete-event simulation by explicitly incorporating uncertainty in model parameters — such as interarrival times, service durations, and resource capacities — and evaluating system performance across worst-case or distributional uncertainty sets rather than point estimates alone. It is widely applied in manufacturing, healthcare, logistics, and supply chain systems where parameter misspecification or real-world variability can lead to misleading simulation conclusions.	Robust Scenario Analysis evaluates a set of candidate strategies across a structured collection of plausible future scenarios and selects the strategy that performs acceptably well — or best in the worst case — regardless of which scenario materializes. It merges scenario planning with robustness criteria such as maximin, minimax regret, or satisficing to support decisions under deep, irreducible uncertainty.