A Two-Stage Chance Constrained Approach with Application to Stochastic Intermodal Service Network Design Problems

Compared with traditional freight transportation, intermodal freight transportation is more competitive which can combine the advantages of different transportation modes. As a consequence, operational research on intermodal freight transportation has received more attention and developed rapidly, but it is still a young research field. In this paper, a stochastic intermodal service network design problem is introduced in a sea-rail transportation system, which considers stochastic travel time, stochastic transfer time, and stochastic container demand. Given candidate train and ship services, we develop a two-stage chance constrained programming model for this problem with the objective of minimising the expected total cost. The first stage allows for the selection of operated services, while the second stage focuses on the determination of intermodal container routes where capacity and on-time delivery chance constraints are presented. A hybrid heuristic algorithm, incorporating sample average approximation and ant colony optimisation, is employed to solve this model. The proposed model is applied to a realistic intermodal sea-rail network, which demonstrates the performance of the model and algorithm as well as the influence of stochasticity on transportation plans. Hence, the proposed methodology can improve effectively the performance of intermodal service network design scheme under stochastic conditions and provide managerial insights for decision-makers.