Prepositioning Disaster Relief Supplies Using Robust Optimization

Systems Conversation with Maria Mayorga, North Carolina State University

Emergency disaster managers are concerned with responding to disasters in a timely and effective manner. The effectiveness of response operations can be improved by prepositioning relief supplies in anticipation of disasters. They study the problem of determining the location and amount of disaster relief supplies to be prepositioned. These supplies are stocked when the locations of affected areas and the amount of relief items needed are uncertain. Furthermore, a proportion of the prepositioned inventory, which is also uncertain, might be damaged by the disaster. They propose a two-stage robust optimization model. The location and amount of prepositioned relief supplies are decided in the first stage before a disaster occurs. In the second stage, a limited amount of relief supplies can be procured post-disaster and prepositioned supplies are distributed to affected areas. The objective is to minimize the total cost of supplying disaster relief materials. They solve the proposed robust optimization model using a column-and-constraint generation algorithm. Two optimization criteria are considered: total absolute cost and regret. A case study of the hurricane season in the southeast U.S. is used to gain insights on the effects of optimization criteria and critical model parameters to relief supply prepositioning strategy.