Large-scale Evacuation Routing and Scheduling Optimization with Uninterrupted Traffic Flow
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In many emergency management operations, an efficient evacuation strategy is of great importance because if it is successful, it has the ability to significantly reduce the loss of property and human life. This thesis develops a routing and scheduling optimization framework for large-scale vehicular evacuation. To guarantee high optimization efficiency, we consider the routing and scheduling optimization as a two-stage problem instead of optimizing them as a whole (i.e. using time-space network). In the first phase, a multiple-objective binary programming model, with the objectives of minimizing the network clearance time and total in-network time is proposed to find an optimal routing plan. In the second phase, a simulation-based scheduling Heuristic is proposed to dynamically generate the time-dependent departure rates. A real-world evacuation scenario in Eastern Shore of Maryland is studied by using the proposed optimization model. The calculation results indicate a good optimization capability and flexibility of the proposed model.