方法对比
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| 稳健情景分析× | 敏感性分析× | |
|---|---|---|
| 领域≠ | 仿真 | 决策 |
| 方法族≠ | Process / pipeline | MCDM |
| 起源年份≠ | 1950 (foundations); 2003 (modern RDM formulation) | 2004 |
| 提出者≠ | Wald, A. (minimax foundation); Lempert et al. (RDM framework) | Saltelli, A., Tarantola, S., Campolongo, F., Ratto, M. |
| 类型≠ | Scenario-based robustness evaluation | Robustness wrapper — parameter / weight perturbation sensitivity indices |
| 开创性文献≠ | 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 ↗ |
| 别名≠ | RSA, Robust Scenario Planning, Worst-Case Scenario Analysis, Minimax Regret Scenario Analysis | — |
| 相关≠ | 5 | 0 |
| 摘要≠ | 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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