Optimization of Freight Dispatching in Rail-Based Intermodal Freight Networks

At today’s seminar, Paul Bossong a PhD student researcher from the Technical University of Darmstadt, presented his latest work on improving freight dispatching in rail-based intermodal freight networks (IFT). His talk highlighted the growing importance of efficient intermodal logistics systems, where standardized load units are moved across scheduled freight trains and terminals under tight operational constraints.

Paul explained that dispatching in these networks is exceptionally complex: planners must simultaneously consider train schedules, shipment delivery deadlines, and multiple capacity limits at both wagon and train levels. In real-world operations, these constraints often interact in ways that make manual or simplified decision-making insufficient.

Using a case study from a German intermodal operator, Paul demonstrated the real impact of optimized dispatching. His findings show that advanced optimization can reduce delivery times by around 15%, while also lowering the number of required train connections by up to 8%—a significant improvement for operators seeking to balance speed and resource efficiency.

A gap in current research, Paul noted, is that most existing models focus either on network-level or train-level dispatching, but not both together. To address this, he developed a multi-commodity network flow (MCNF) model that integrates temporal, spatial, and capacity constraints specific to intermodal freight transport. This comprehensive modeling approach more closely reflects real operational conditions.

To solve large-scale, real-world instances efficiently, Paul introduced a greedy heuristic and a column generation (CG) algorithm. His computational study—built on publicly available real-world data—showed that this solution framework consistently identifies highquality dispatching plans, outperforming a leading commercial solver by up to 32% within 36–77% of the computation time.

Paul’s broader research focuses on optimizing intermodal freight systems through automation, digitization, and rigorous quantitative analysis. With a background in industrial engineering and deep expertise in intermodal transportation systems, his work contributes valuable insights to improving the performance and sustainability of modern freight networks.