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hurricane evacuation, fuel shortage, epidemic model, optimal control


Hurricanes are powerful agents of destruction with significant socioeconomic impacts. High-volume mass evacuations, disruptions to the supply chain, and fuel hoarding from non-evacuees have led to localized fuel shortages lasting several days during recent hurricanes. Hurricane Irma in 2017, resulted in the largest evacuation in the nation affecting nearly 6.5 million people and saw widespread fuel shortages throughout the state of Florida. While news reports mention fuel shortages in several past hurricanes, the crowd source platform Gasbuddy has quantified the fuel shortages in the recent hurricanes. The analysis of this fuel shortage data suggested fuel shortages exhibited characteristics of an epidemic. Fundamentally, as fueling stations were depleted, the latent demand spread to neighboring stations and propagated throughout the community, similar to an epidemiological outbreak. In this paper, a Susceptible- Infected –Recovered (SIR) epidemic model was developed to study the evolution of fuel shortage during a hurricane evacuation. Within this framework, an optimal control theory was applied to identify an effective intervention strategy. Further, the study found a linear correlation between traffic demand during the evacuation of Hurricane Irma and the resulting fuel shortage data from Gasbuddy. This correlation was used in conjunction with the State-wide Regional Evacuation Study Program (SRESP) surveys to estimate the evacuation traffic and fuel shortages for potential hurricanes affecting south Florida. The epidemiological SIR dynamics and optimal control methodology was applied to analyze the fuel shortage predictions and to develop an effective refueling strategy.