A Risk-Averse Shelter Location and Evacuation Routing Assignment Problem in an Uncertain Environment

This study develops a planning model to decide where to place shelters and how to route evacuees during disasters when demand is uncertain. It focuses on minimizing total evacuation time while avoiding congestion and overcrowding. The model accounts for real-world uncertainty by testing different demand scenarios and prioritizing solutions that still perform well under worst-case conditions. Results show that coordinated, system-level routing spreads traffic more evenly and reduces evacuation time compared to people choosing routes on their own. However, more risk-averse plans may increase overall travel time slightly in exchange for more reliable performance during extreme events.