Stochastic optimization for the carrier selection problem in humanitarian relief

Abstract

In this paper, the carrier selection problem is addressed to reduce the probability of the occurring carrier shortage by creating a carrier rental agreement. We propose a new two-stage stochastic model for determining the pre-disaster and post-disaster decisions in order to deliver relief items to the injured survivors of the disaster. The pre-disaster phase focuses on determining the amount of carrier rental in the framework of contracts with suppliers, and also deciding an appropriate coverage distance with regards to time and cost. The postdisaster phase aims to respond to the requests made by disaster inflicted areas swiftly and cost-effectively. The proposed mixed-integer linear programming model considers a scenario-based approach to handle the uncertainty of demand. Additionally, a real case study is presented to demonstrate the efficiency of the model. Moreover, numerical analyses are practiced to illustrate the importance and impact of the cost and the number of carrier rental contracts in the studied problem. Finally, The L-shaped algorithm is used to solve this model in different test instances and the result shows the applicability of the applied algorithm.