用改进的混合规划方法，高效求解带封城的疫情应对策略。
A Metric Hybrid Planning Approach to Solving Pandemic Planning Problems with Simple SIR Models
- 将经典SIR模型扩展为含封城状态的转移模型。
- 在多种复杂场景下，理论与实验均验证了方法有效性。
- 适合政策制定者和公共卫生研究者参考。
疫情是疾病在大范围传播的事件，可能对社会造成严重的健康、经济与社会影响。因此，研究有效的疫情缓解策略具有重大社会价值。疫情可数学建模为分室模型，如易感-感染-移除（SIR）模型。本文将SIR模型的求解方程扩展至包含封城措施的状态转移模型，并基于此构建了一个度量混合规划问题，采用度量混合规划器求解。通过引入有效不等式，提升了规划器的运行效率，并在多种挑战性设置下，从理论上和实验上均证明了该方法的成功。
原文摘要 · Abstract (English)
A pandemic is the spread of a disease across large regions, and can have devastating costs to the society in terms of health, economic and social. As such, the study of effective pandemic mitigation strategies can yield significant positive impact on the society. A pandemic can be mathematically described using a compartmental model, such as the Susceptible Infected Removed (SIR) model. In this paper, we extend the solution equations of the SIR model to a state transition model with lockdowns. We formalize a metric hybrid planning problem based on this state transition model, and solve it using a metric hybrid planner. We improve the runtime effectiveness of the metric hybrid planner with the addition of valid inequalities, and demonstrate the success of our approach both theoretically and experimentally under various challenging settings.
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