Stochastic optimization for joint decision making of inventory and procurement in humanitarian relief

Abstract

This paper presents a two-stage stochastic programming model for integrating decisions on pre-disaster inventory level and post-disaster procurement quantity with supplier selection in humanitarian relief. Three features are considered in the model, including lead time discount, return price, and equity. Given the uncertainty about the disaster type and occurrence location, a scenario-based approach is applied to represent the uncertain demand. Conditional Value-at-Risk is employed to measure risk at different confidence levels. Based on a real-world example where a surge in demand was incurred by a snowstorm, earthquake, flood and typhoon in China in 2008, a case study is presented to investigate the applicability of the proposed model, and its implications are discussed based on numerical studies. The model can assist relief agencies in managing supplies for disaster response.