An analytical approach to planning for and managing random disruption in rail intermodal networks

Rail-truck intermodal transportation relies on intermodal trains for long-haul movement and trucks for highway delivery. It accounts for a significant portion of freight traffic in North America, making its reliable operation vital to the economy. However, these networks are vulnerable to disruptions, highlighting the need to ensure their resilience under such conditions. This article proposes two optimization models: the first addresses terminal location, train service design and freight routing under normal operations; the second incorporates disruptions at intermodal terminals with varying severity levels. To account for disruption uncertainty, we define disruption scenarios and employ a two-stage stochastic programming approach and introduce recovery strategies to maintain shipment continuity. In addition, we outline a solution heuristic for larger problem instances. The proposed optimization programs are applied to a case study based on the USA, and the resulting analyses highlight the importance of incorporating disruption especially given the impact on train services and routing of containers, highlight the role of terminal utilization under normal operating conditions on the decision to repair terminals under disruption and the impact on service legs, and reiterates the significance of designing train services to maintain a balanced offering and ensure connectedness.