Pre-positioning and real-time disaster response operations: Optimization with mobile phone location data

Abstract

Uncertainty of disaster information severely hinders efficiency of disaster relief operations. This paper explores how mobile phone location data are applied to capture rapidly accurate disaster information and proposes a preparedness-response two-stage scenario-based stochastic programming model with mobile phone location data for integrated pre-positioning and real-time response operation optimization. The Dantzig-Wolfe decomposition approach based on Lagrange duality and branch-and-bound algorithm are adopted to solve this model. The applicability of the model is proved via a real-world case study on the Haiti earthquake. Numerical experiments are performed to offer important managerial implications and insights in disaster management, especially for large-scale disasters.