AI 中文总结
该研究提出首个自适应鲁棒疏散规划模型，联合优化避难所选址等多环节，实验显示集中式路径规划可大幅降低最坏情况未满足需求与疏散时间，自适应再分配可提升救灾覆盖。
AI 中文摘要
防灾准备中的疏散规划需要在疏散人数及其空间分布未知的不确定性下做出关键决策，包括避难所选址、疏散路径分配以及救灾物资预置。由于这些决策高度相互依赖，规划者必须在最大化救灾需求覆盖与最小化疏散时间这两个相互冲突的目标间进行权衡。据我们所知，我们提出了首个自适应鲁棒疏散规划模型，该模型可联合优化避难所选址、疏散路径分配、救灾物资预置以及灾后救灾物资分配。该模型最小化各避难所未满足救灾需求的最坏情况加权总和，以及依赖拥堵程度的疏散时间。我们刻画了该带混合整数补偿的问题的理论复杂度驱动因素，并开发了一种分块-边界算法，该算法仅选择性划分不确定性集合中最关键的子块，同时保持可处理性并生成强上下界。为量化集中式路径规划的价值，我们还构建了一种用户路径选择替代方案，即疏散者在可接受路径中自主选择。计算实验量化了集中式路径规划的价值，与分散式用户路径选择相比，其可将最坏情况未满足需求和疏散时间分别降低多达90.6%和79.3%。自适应灾后物资再分配进一步提升了救灾需求覆盖。在不确定性下，疏散路径与救灾分配间的协调创造了显著的运营价值：集中式路径规划主要通过协调跨避难所的疏散人流缓解拥堵，而自适应再分配则主要在救灾物资稀缺或预置不灵活时提升救灾需求覆盖。
英文摘要
Evacuation planning for disaster preparedness requires making critical decisions under uncertainty before the number and spatial distribution of evacuees are known, including shelter location, evacuation route assignment, and relief supply prepositioning. Because these decisions are highly interdependent, planners must balance the competing objectives of maximizing relief demand coverage and minimizing evacuation time. We propose, to our knowledge, the first adaptive robust evacuation planning model to jointly optimize shelter locations, evacuation route assignments, relief supply prepositioning, and post-disaster relief item distribution. The model minimizes the worst-case weighted sum of unmet demand for relief items across shelters and the congestion-dependent evacuation time. We characterize theoretical complexity drivers of the resulting problem with mixed-integer recourse and develop a partition-and-bound algorithm that maintains tractability by selectively partitioning only the most critical subpartition of the uncertainty set while producing strong upper and lower bounds. To quantify the value of centralized route planning, we also formulate a user route choice alternative in which evacuees choose among acceptable routes. Computational experiments quantify the value of centralized route planning, which reduces worst-case unmet demand and evacuation time by up to 90.6\% and 79.3\%, respectively, relative to decentralized user route choice. Adaptive post-disaster supply redistribution further improves relief demand coverage. Coordination between evacuation routing and relief distribution creates substantial operational value under uncertainty. Centralized route planning primarily mitigates congestion by coordinating evacuee flows across shelters, whereas adaptive redistribution primarily improves relief demand coverage when relief supplies are scarce or inflexibly prepositioned.
