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Anàlisi d'Escenaris Robustos×Simulació Monte Carlo×
CampSimulacióPresa de decisions
FamíliaProcess / pipelineMCDM
Any d'origen1950 (foundations); 2003 (modern RDM formulation)1949
Autor originalWald, A. (minimax foundation); Lempert et al. (RDM framework)Metropolis, N., Ulam, S.
TipusScenario-based robustness evaluationRobustness wrapper — Monte Carlo uncertainty propagation
Font seminalWald, A. (1950). Statistical Decision Functions. Wiley, New York. link ↗Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
ÀliesRSA, Robust Scenario Planning, Worst-Case Scenario Analysis, Minimax Regret Scenario Analysis
Relacionats50
ResumRobust 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.MONTE-CARLO-SIMULATION (Monte Carlo Simulation — Stochastic uncertainty propagation through MCDM model) is a ranking multi-criteria decision-making (MCDM) method introduced by Metropolis, N., Ulam, S. in 1949. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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ScholarGateCompara mètodes: Robust Scenario Analysis · MONTE-CARLO-SIMULATION. Recuperat el 2026-06-17 de https://scholargate.app/ca/compare