Robust Evacuation Planning for Urban Areas

Abstract

This article summarizes the findings of my Ph.D. thesis finished in 2017, which focuses on the mass evacuation of urban areas. The main task of evacuation planning is the guidance of the evacuees through the street network to reduce casualty risks and increase the performance of the evacuation process. Usually the capacities of the street network are assumed as in daily-traffic. However, such rare and unique situations induce disaster-related or traffic-related factors which affect the capacities of the street network negatively. The contribution of this work lies in designing a deterministic optimization model that is more robust against these capacity uncertainties. Therefore, we adopt an idea that has already been successfully applied to robust network design: The robustness of the street network is enhanced by a better utilization of the available network capacities and by reducing interdependencies in the network. Thus, evacuation performance (e.g., the total evacuation time) is not our only objective and we are willing to sacrifice some of it to enhance the robustness in the face of unpredictable capacity disruptions. A new innovative bi-objective evacuation model and individual solution methods are presented. These methods and the new robust concept are evaluated in an extensive computational study.