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Policy Scenario Genetic Algorithm/Evidence
Method evidence record

Policy Scenario Genetic Algorithm

The Policy Scenario Genetic Algorithm applies evolutionary search to systematically explore large, combinatorial policy alternative spaces under multiple future scenarios. Rather than exhaustively enumerating options, it breeds successive generations of candidate policies, retaining those that perform well across scenario conditions, yielding robust, high-performing policy recommendations.

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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 Genetic Algorithm — Evolutionary Search over Discrete Policy Alternative Spaces
Taxonomic method record · process-pipeline / simulation
  • Holland, J. H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor, MI. · ISBN 9780262581110
  • Lempert, R. J., Popper, S. W., & Bankes, S. C. (2003). Shaping the Next One Hundred Years: New Methods for Quantitative, Long-Term Policy Analysis. RAND Corporation, Santa Monica, CA. · URL
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Related methods

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

Same method familyGenetic Algorithmmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMulti-objective genetic algorithmmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketPolicy Scenario Analysismachine-suggested · Relational suggestion, not evidence.Taxonomic bucketPolicy Scenario 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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