विधियों की तुलना करें

	Robust Scenario Analysis	स्टोकेस्टिक परिदृश्य विश्लेषण
क्षेत्र	अनुकरण	अनुकरण
परिवार	Process / pipeline	Process / pipeline
उद्भव वर्ष	1950 (foundations); 2003 (modern RDM formulation)	1955–1980s
प्रवर्तक	Wald, A. (minimax foundation); Lempert et al. (RDM framework)	Dantzig, G. B.; Birge, J. R.; and others in stochastic programming tradition
प्रकार	Scenario-based robustness evaluation	Probabilistic scenario enumeration and evaluation
मौलिक स्रोत	Wald, A. (1950). Statistical Decision Functions. Wiley, New York.	Birge, J. R., Louveaux, F. (2011). Introduction to Stochastic Programming (2nd ed.). Springer. ISBN: 9781461402374
उपनाम	RSA, Robust Scenario Planning, Worst-Case Scenario Analysis, Minimax Regret Scenario Analysis	Probabilistic Scenario Analysis, SSA, Stochastic What-If Analysis, Monte Carlo Scenario Analysis
संबंधित	5	4
सारांश	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.	Stochastic Scenario Analysis evaluates a system or decision across multiple explicitly defined scenarios, each assigned a probability of occurrence. Unlike deterministic scenario analysis, it propagates uncertainty through probability distributions and computes expected outcomes, variance, and risk metrics across the scenario space, giving decision-makers a structured view of what could happen and how likely each outcome is.