Real-Time Transit Vehicle Routing Optimization in Intermodal Emergency Evacuations
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Real-Time Transit Vehicle Routing Optimization in Intermodal Emergency Evacuations

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  • Abstract:
    Since Hurricane Katrina, extensive studies have been conducted aiming to optimize transit vehicle routing in an emergency evacuation. However, the vast majority of the studies focus on solving the deterministic vehicle routing problem, in which all evacuation data are known in advance. These studies are generally not practical in dealing with real-world problems that involve considerable uncertainty in the evacuation data set. In this project, a SmartEvac system is developed for dynamic vehicle routing optimization in an emergency evacuation. The SmartEvac system is capable of processing dynamic evacuation data—such as random pickup requests, travel time change, and network interruptions—in real time. The objective is to minimize the total travel time for all transit vehicles. A column generation based online optimization model is integrated into the SmartEvac system. The optimization model is based on two structures: a master problem model and a sub-problem model. The master problem model is used for route selection from a restricted routes set, while the sub-problem model is developed to progressively add new routes into the restricted routes set. The sub-problem is formulated as a shortest path problem with capacity constraints and is solved using a cycle elimination algorithm. When the evacuation data are updated, the SmartEvac system will reformulate the optimization model and generate new routes set based on the existing routes set. The computational results on benchmark problems are compared to the results from other studies in the literature. The SmartEvac system outperforms the other approaches on most of the benchmark problems in terms of computation time and solution quality. CORSIM simulation is used as a test bed for the SmartEvac system. CORSIM RunTime-Extension is developed for communications between the simulation and the SmartEvac system. A case study of the Hurricane Gustav emergency evacuation is conducted, where different scenarios corresponding to the different situations that happened in the Hurricane Gustav emergency evacuation are proposed to evaluate the performance of the SmartEvac system in response to real-time data. The average processing time is 28.9 seconds, and the maximum processing time is 171 seconds, which demonstrates the SmartEvac system’s capability of real-time vehicle routing optimization on an Intel Core I5 Laptop. The dynamic vehicle routing optimization model is deployed and implemented to a web-based online service system to allow transit agencies or drivers to exchange necessary data.
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