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A STOCHASTIC PROGRAMMING APPROACH FOR SHELTER LOCATION AND EVACUATION PLANNING

机译:避难所位置和疏散规划的随机规划方法

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Shelter location and traffic allocation decisions are critical for an efficient evacuation plan. In this study, we propose a scenario-based two-stage stochastic evacuation planning model that optimally locates shelter sites and that assigns evacuees to nearest shelters and to shortest paths within a tolerance degree to minimize the expected total evacuation time. Our model considers the uncertainty in the evacuation demand and the disruption in the road network and shelter sites. We present a case study for a potential earthquake in Istanbul. We compare the performance of the stochastic programming solutions to solutions based on single scenarios and mean values.
机译:避难所的位置和交通分配决定对于有效的疏散计划至关重要。在这项研究中,我们提出了一种基于场景的两阶段随机疏散计划模型,该模型可以最佳地定位避难所,并将疏散人员分配到最近的避难所,并在容忍度内分配最短路径,以最大程度地减少预期的总疏散时间。我们的模型考虑了疏散需求的不确定性以及路网和避难所的破坏。我们提出一个伊斯坦布尔潜在地震的案例研究。我们将随机编程解决方案的性能与基于单个方案和均值的解决方案进行比较。

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