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Policy Scenario Multi-Objective Optimization/Evidence
Method evidence record

Policy Scenario Multi-Objective Optimization

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.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Policy Scenario Multi-Objective Optimization — Scenario-conditioned Pareto-optimal Policy Search
Taxonomic method record · process-pipeline / simulation
  • Deb, K. (2001). Multi-Objective Optimization Using Evolutionary Algorithms. John Wiley & Sons, Chichester. · ISBN 9780471873396
  • Walker, W. E., Harremoës, P., Rotmans, J., van der Sluijs, J. P., van Asselt, M. B. A., Janssen, P., & Krayer von Krauss, M. P. (2003). Defining uncertainty: a conceptual basis for uncertainty management in model-based decision support. Integrated Assessment, 4(1), 5–17. · DOI 10.1076/iaij.4.1.5.16466
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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Taxonomic bucketMulti-objective genetic algorithmmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMulti-Objective Optimizationmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketPolicy Scenario Analysismachine-suggested · Relational suggestion, not evidence.Taxonomic bucketRobust Multi-Objective Optimizationmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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