Robust approach for air cargo freight forwarder selection under disruption

Airlines select a group of strategic freight forwarders as their partners to retain an information advantage and maintain stable sources of air cargo. Cargo supply disruption is a critical factor for airlines when they select freight forwarders. In the present study, we propose a distributional robust model to select freight forwarders under supply disruptions, which allows cargo supply disruptions to be correlated. We first analyze the structural properties of the model and then reformulate it into a tractable form. In a real-world case study, the decision model is executed in the air cargo service chain, which consists of six flights and dozens of forwarders. The case study illustrates how our approach is used by the airline to identify reliable freight forwarders in the service chain and provide comprehensive forwarder selection strategies. We also illustrate the comparative advantages of our new approach over traditional methods: the forwarder selection strategy is capable of considering the bargaining power of freight forwarders and computational efficiency. Given these advantages, this new distributional robust optimization model can serve as a promising approach for solving freight forwarder selection problems.