Abstract
Gasoline shortages and long lines at the pump spread at stations is a well-known challenge during large-scale evacuations ahead of hurricanes. One of the reasons for this problem is that evacuees rush to fuel up in a panic. Therefore, they attempt to get as much gas as they can without considering their true need and without considering other evacuees. An idealized management of gasoline supply is one in which each evacuee that needs gasoline to successfully evacuate is assigned to a specific gas station along an evacuation route where they would be permitted to fill gas. Each gas station is restricted to a specific amount of gasoline per vehicle. This paper develops a mathematical formulation for such an idealized framework. The objective of the formulation is to maximize the number of evacuees that successfully reach the safe zone. The model takes into account different initial fuel level of evacuees, different evacuation starting times, and dynamic flow demand volume for each path over time. The superiority of the idealized evacuation over a simulated uncontrolled evacuation, in different scenarios, is verified on a small example. The idealized evacuation model is also applied to a real-world hurricane evacuation scenario in the evacuation network of St. Johns County, Florida. A creative efficient solution methodology (simplifying the complex constraints) is developed to solve the model to the optimality for the case study. The model’s objective function and solving time are stress-tested over key input parameters. The results show that the idealized evacuation model manages a high percentage of evacuees to successfully reach the safe zones, even with a short amount of gasoline supplies available in the gas stations.
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This research is funded by National Science Foundation award number CMMI1663101. This support is gratefully acknowledged.
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Sabbaghtorkan, M., Batta, R. & He, Q. On the analysis of an idealized model to manage gasoline supplies in a short-notice hurricane evacuation. OR Spectrum 44, 911–945 (2022). https://doi.org/10.1007/s00291-022-00665-0
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DOI: https://doi.org/10.1007/s00291-022-00665-0