A main objective in the evacuation routing problem is to minimize total evacuation time. Analytical models have been developed for this problem with a major draw back due to assuming constant travel time (speed). A routing solution that is based on assuming constant speed may produce, if applied in real life conditions, impractical and ineffective results. Therefore, it is more realistic to assume that travel time is a function of road flow and density. Simulation models have been developed for evacuation planning that can predict travel time as a function of road density. However, these models are not capable of finding the best routes for evacuation. They are mostly used to evaluate alternatives and devise recommendations. To overcome these shortcomings, this dissertation develops a new model where routes optimization and road traffic simulation are integrated into one algorithm. The new model is evaluated by recording total evacuation time to 64 case studies that are based on parts of Houston and Galveston cities. For the same case studies, the constant travel time solution is run through the traffic simulation model and the resulted evacuation time is recorded. In all of these case studies the new model outperformed the constant travel time solution with a reduction in total evacuation time that ranged between 1% and 79%.
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