An optimization approach for resilient and sustainable planning of intermodal transport

Despite heightened concerns about freight network disruptions and their environmental impact, a critical knowledge gap persists in designing and operating resilient intermodal transport networks that simultaneously achieve two objectives: (a) economic performance and (b) low carbon emissions. This paper addresses this gap by introducing a novel bi-objective two-stage stochastic formulation for the network design and planning problem under disruption risks. In addition to covering both economic and emissions objectives, the model specifies the best set of actions to prepare for and respond to disruptions. These actions include the optimal number of vehicles from each transportation mode, the flow of containers on the transportation links, and the best route to deliver orders. To generate the non-dominated solutions, an augmented ε-constraint method is used on the data from a case study of the UK transportation network. The proposed approach contributes to the existing literature by focusing on the design and planning of intermodal networks that are not only resilient to disruptions, but are also cost-efficient, sustainable, and responsive. Numerical results reveal the potential of the proposed approach to significantly decrease carbon emissions by 62% with only a marginal increase in costs. The analysis of numerical results also shows a 16% cost savings resulting from strategic investments in appropriate preparedness and recovery actions. Additionally, the study indicates that despite a road mode capacity utilization of 98% to meet demands in disruption scenarios, it serves less than 9% of demand to align with environmentally sustainable objective.