Modeling Disruption in the Rail-Road Network and Identifying Critical Terminals

Using optimization and regression methods, this research developed intermodal transportation routes in the event of terminal disruptions. The proposed mixed integer linear programming model explicitly takes into account the discrete unit flows of carriers within the intermodal rail network including time-varying demand and capacity. The objective of this study is to optimize the rerouting decisions for carrier services in rail-road intermodal transportation networks. Numerical experiments are conducted with several problems of varying sizes and characteristics. CPLEX solves the optimization model and reports the most effective results. A case study of multimodal transportation networks in Iran demonstrated the effectiveness of the proposed strategies. The results of this study demonstrate that it is important to identify the vulnerable rail-roadway links in an intermodal freight transportation network in order to minimize delays in meeting freight demand and, thus, increase the reliability of the multimodal freight network in Iran. By using road strategy to reduce costs, the transportation costs will decrease by 0.85% and 4.8%, respectively, under 25% and 100% disruption conditions; therefore, road transportation is a more economical strategy for reducing costs in conditions of rail terminal disruption.