Comparer des méthodes

	Programmation dynamique par scénarios de politique	Analyse de scénarios politiques
Domaine	Simulation	Simulation
Famille	Process / pipeline	Process / pipeline
Année d'origine	1957	1967–1990s
Auteur d'origine	Bellman, Richard E.	Kahn, H. & Wiener, A. J. (seminal); adapted for policy by RAND Corporation and OECD
Type	Sequential optimization with scenario branching	Qualitative-quantitative hybrid scenario method
Source fondatrice	Bellman, R. (1957). Dynamic Programming. Princeton University Press, Princeton, NJ. ISBN: 9780691079516	Swart, R., Raskin, P., Robinson, J. (2004). The problem of the future: sustainability science and scenario analysis. Global Environmental Change, 14(2), 137–146.
Alias	PSDP, Policy-Scenario DP, Scenario-Based Dynamic Programming, Policy DP	PSA, Policy Scenarios, Policy Impact Scenario Analysis, Counterfactual Policy Analysis
Apparentées	5	5
Résumé	Policy Scenario Dynamic Programming (PSDP) applies Bellman's recursive optimization framework to a set of pre-specified policy scenarios, enabling decision-makers to compare staged, sequential decisions under distinct future conditions. It decomposes a complex, multi-period policy choice into tractable sub-problems solved backward through time, yielding optimal action sequences for each scenario and a structured basis for scenario comparison.	Policy Scenario Analysis is a structured method for evaluating how different policy interventions perform across a range of plausible future states. By pairing specific policy levers with alternative scenarios, analysts can assess robustness, trade-offs, and unintended consequences of policy choices before implementation — making it a cornerstone of evidence-based policy design in fields from climate to public health.