Robust Shelter Locations for Evacuation Planning with Demand Uncertainty

TLDR: In this paper, a robust approach for determining optimal locations of public shelters and their capacities, from a given set of potential sites during evacuation planning under demand uncertainty is presented, where a planning authority determines the number of shelters, their locations, and capacities whereas evacuees choose a shelter to evacuate and the routes to access it.

Abstract: This article presents a robust approach for determining optimal locations of public shelters and their capacities, from a given set of potential sites during evacuation planning under demand uncertainty. Demand uncertainty in the article refers to the uncertainty associated with the number of people using the public shelters during evacuation. It is assumed that a planning authority determines the number of shelters, their locations, and capacities whereas evacuees choose a shelter to evacuate and the routes to access it. The proposed model is formulated as a mathematical program with complementarity constraints and is solved by a cutting-plane scheme. A numerical example on the Sioux Falls network demonstrates that robust plans are able to achieve nearly the same level of performance with a significant lower cost as compared to a conservative plan, which assumes the highest demand of each origin node.