Prepositioning Emergency Supplies to Support Disaster Relief: A Stochastic Programming Approach

This paper studies the strategic problem of designing emergency supply networks to support disaster relief over a planning horizon. This problem addresses decisions on the location and number of distribution centers needed, their capacity, and the quantity of each emergency item to keep in stock in time. To tackle the problem, a scenario based approach is proposed involving three phases: disasters scenario generation, design generation and design evaluation. Disasters are modeled as stochastic processes and a Monte Carlo procedure is derived to generate plausible catastrophic scenarios. Based on this detailed representation of disasters, a multi-phase modeling framework is proposed to design the emergency supply network. The two-stage stochastic programming formulation proposed is solved using a sample average approximation method. This scenario based solution approach is tested with a case inspired from realworld data to generate plausible scenarios, to produce a set of alternative designs and then to evaluate them on a set of performance measures in order to select the best design.