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Análisis de Escenarios Robusto×Simulación de Monte Carlo×
CampoSimulaciónToma de decisiones
FamiliaProcess / pipelineMCDM
Año de origen1950 (foundations); 2003 (modern RDM formulation)1949
Autor originalWald, A. (minimax foundation); Lempert et al. (RDM framework)Metropolis, N., Ulam, S.
TipoScenario-based robustness evaluationRobustness wrapper — Monte Carlo uncertainty propagation
Fuente 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 ↗
AliasRSA, Robust Scenario Planning, Worst-Case Scenario Analysis, Minimax Regret Scenario Analysis
Relacionados50
ResumenRobust 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.
ScholarGateConjunto de datos
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  1. v1
  2. 1 Fuentes
  3. PUBLISHED

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ScholarGateComparar métodos: Robust Scenario Analysis · MONTE-CARLO-SIMULATION. Recuperado el 2026-06-17 de https://scholargate.app/es/compare