Process / pipelineSimulation / optimization
策略情景遗传算法 — 策略备选空间上的进化搜索
策略情景遗传算法（Policy Scenario Genetic Algorithm, PSGA）将进化搜索应用于系统性地探索多重未来情景下的大型组合策略备选空间。它不穷举所有选项，而是培育候选策略的连续世代，保留在各种情景条件下表现良好的策略，从而产生稳健、高性能的策略建议。
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Method map
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来源
- 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. link ↗
如何引用本页
ScholarGate. (2026, June 3). Policy Scenario Genetic Algorithm — Evolutionary Search over Discrete Policy Alternative Spaces. ScholarGate. https://scholargate.app/zh/simulation/policy-scenario-genetic-algorithm
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