Different types of hazards occur quite often in different parts of the globe. These hazards may cause significant property damages, monetary losses, and human fatalities.Emergency evacuation can be extremely challenging in rural areas that may not have emergency shelters with adequate capacity in their vicinity, and transportation infrastructure may not be able to handle a large number of evacuees. Furthermore, a frequent occurrence of pandemics makes emergency evacuation planning even more challenging. Rushing to the closest emergency shelter may not be the best choice, because the closest shelters may operate at the capacity level. Overcrowded emergency shelters are expected to have a high risk of virus transmission under pandemic settings. Therefore, this project proposes a new bi-objective optimization model for emergency evacuation planning, aiming not only to minimize the total travel time of evacuees to the assigned emergency shelters but also to minimize the risk of virus transmission in the assigned emergency shelters as well. A custom multi-objective optimization algorithm is developed to solve the proposed bi-objective optimization model. Various case studies are conducted to demonstrate applicability of the proposed methodology for real-life emergency evacuation scenarios. Evacuation of populations residing in rural counties is directly considered during the numerical experiments. The findings from this research can be used to better prepare rural populations for approaching natural hazards and ensure their safety throughout the evacuation process.
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