Process / pipelineSimulation / optimization
策略情景多目标优化——情景条件化帕累托最优策略搜索
策略情景多目标优化（PS-MOO）将显式的策略情景构建与多目标优化相结合，以识别跨越各种可能未来状态的帕累托最优策略选项。决策者评估每个不同策略情景下相互竞争的目标（如经济效率、公平性和环境影响）之间的权衡取舍，然后比较帕累托前沿以选择稳健的或依赖于情景的策略。
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来源
- 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 ↗
如何引用本页
ScholarGate. (2026, June 3). Policy Scenario Multi-Objective Optimization — Scenario-conditioned Pareto-optimal Policy Search. ScholarGate. https://scholargate.app/zh/simulation/policy-scenario-multi-objective-optimization
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