Stochastic optimization for the carrier selection problem in humanitarian relief

In this paper, the carrier selection problem is addressed with the purpose of avoiding shortage regarding vehicle necessity and creating a vehicle rental framework agreement. Achieving in-time delivery of relief supplies to the disaster inflicted areas is of utmost significance in terms of humanitarian relief. We propose a new two-stage stochastic model for determining the pre-disaster and post-disaster decisions in order to delivering relief items to the injured survivors. The pre-disaster phase focuses on determining amount of vehicle in the framework of contracts with suppliers, and deciding an appropriate coverage distance with regards to time and cost. The post-disaster phase aims to respond to the requests made by disaster inflicted areas swiftly and cost-effectively. The proposed MILP model considers a scenario-based approach to handle the uncertainty of demand. The L-shaped algorithm is used to solve this model. A real case study is presented with the aim of demonstrating the efficiency of the model. Moreover, numerical analyses are practiced to illustrate the importance and impact of the cost and the number of vehicle rental contracts in the studied problem. Finally, managerial insights have been presented to assist the relief organization management in making appropriate and efficient decisions.