Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Analyse de scénarios robuste× | Analyse de sensibilité× | |
|---|---|---|
| Domaine≠ | Simulation | Prise de décision |
| Famille≠ | Process / pipeline | MCDM |
| Année d'origine≠ | 1950 (foundations); 2003 (modern RDM formulation) | 2004 |
| Auteur d'origine≠ | Wald, A. (minimax foundation); Lempert et al. (RDM framework) | Saltelli, A., Tarantola, S., Campolongo, F., Ratto, M. |
| Type≠ | Scenario-based robustness evaluation | Robustness wrapper — parameter / weight perturbation sensitivity indices |
| Source fondatrice≠ | Wald, A. (1950). Statistical Decision Functions. Wiley, New York. link ↗ | Saltelli, A., Tarantola, S., Campolongo, F., Ratto, M. (2004). Sensitivity Analysis in Practice. Wiley, Chichester DOI ↗ |
| Alias≠ | RSA, Robust Scenario Planning, Worst-Case Scenario Analysis, Minimax Regret Scenario Analysis | — |
| Apparentées≠ | 5 | 0 |
| Résumé≠ | 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. | SENSITIVITY-ANALYSIS (Sensitivity Analysis — Systematic assessment of output variation w.r.t. input perturbations) is a ranking multi-criteria decision-making (MCDM) method introduced by Saltelli, A., Tarantola, S., Campolongo, F., Ratto, M. in 2004. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. |
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