Methoden vergleichen

	Policy Scenario Multi-Objective Optimization	Policy Scenario Analysis
Fachgebiet	Simulation	Simulation
Familie	Process / pipeline	Process / pipeline
Entstehungsjahr	1990s–2000s	1967–1990s
Urheber	Evolved from multi-objective optimization and policy scenario analysis communities	Kahn, H. & Wiener, A. J. (seminal); adapted for policy by RAND Corporation and OECD
Typ	Scenario-conditioned multi-objective search	Qualitative-quantitative hybrid scenario method
Wegweisende Quelle	Deb, K. (2001). Multi-Objective Optimization Using Evolutionary Algorithms. John Wiley & Sons, Chichester. ISBN: 9780471873396	Swart, R., Raskin, P., Robinson, J. (2004). The problem of the future: sustainability science and scenario analysis. Global Environmental Change, 14(2), 137–146.
Aliasnamen	PS-MOO, Policy-Driven MOO, Scenario-Based Multi-Objective Optimization, Policy MOO	PSA, Policy Scenarios, Policy Impact Scenario Analysis, Counterfactual Policy Analysis
Verwandt	4	5
Zusammenfassung	Policy Scenario Multi-Objective Optimization (PS-MOO) integrates explicit policy scenario construction with multi-objective optimization to identify Pareto-optimal policy options across plausible future states. Decision-makers evaluate trade-offs between competing objectives — such as economic efficiency, equity, and environmental impact — for each distinct policy scenario, then compare Pareto fronts to select robust or scenario-contingent strategies.	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.