Evacuating and Sheltering Aging Populations: A GIS- and Optimization-Based Methodolog

Evacuating individuals and allocating space in shelters are complex tasks that depend on disaster characteristics, roadway network characteristics, the demographics and socioeconomic status of people in the affected region, as well as the effectiveness of the emergency plans. This problem becomes even more challenging when special needs (access and functional needs) populations and those with pets are considered since they may require more time in the event of an evacuation along with more space in shelters. Satisfying the needs of aging victims during emergency evacuations is critical and requires extra attention in the presence of highly uncertain disaster conditions. During Irma, it was very hard to manage the evacuation of aging people who had disabilities and mobility restrictions, did have special needs or pets. This study develops a Geographical Information Systems (GIS)-based methodology to measure and assess the transportation accessibility of these critical facilities through a diverse set of case study applications in the State of Florida. This research presents a timely evaluation and assessment of aging-focused evacuations towards providing better decision support during emergency transportation operations. This analysis is applied on a case study application set in Florida with a focus on the delays, evacuation travel times and critical bottlenecks, which can be vital for aging victims' safety and survival. This study also emphasizes the use of GIS-based maps and modeling scenarios in support of emergency evacuation operations, in order to both satisfy the needs of aging people and account for real-world disruptions such as road closures. Additionally, a variety of scenarios are constructed to simulate evacuating 65+ and 85+ populations living in the evacuation zone, providing dynamic congested travel times. Finally, a capacitated p-median optimization model is implemented to maximize the accessibility and capacity of the existing shelters for 85+ populations with special needs (access and functional needs) or pets. Results indicate that the location and allocations of people to shelters are sensitive to demographics and roadway conditions, and the accessibility to shelters can be improved for this group of people based on optimization model results. A contribution of the research will be the evaluation of emergency evacuation performance of the transportation network under multiple disaster scenarios and the detailed modeling of key transportation facilities where special needs would take place. By exploring the use of multi-layered approach for emergency operations, this research will also increase the performance in evacuating aging people who has limitations.