A computational framework for dimensioning a railway freight transportation plan

Railways are essential for a fossil-free transportation system, yet the strategic planning tools for freight transportation on a long-term horizon remain scarce. Strategic freight transport models usually predict annual transportation demand, but the implications for railway capacity usage remain unclear. This missing link between national freight transportation models and strategic railway capacity management is a barrier for strategic decision-making in national transport and railway system planning. We propose a computational framework that includes a macroscopic Mixed Integer Linear Programming (MILP) model integrating fleet-sizing, flow assignment, and train scheduling problems, addressing this gap in strategic planning. The framework generates a cyclic national-scale rail freight transportation plan containing the flows of locomotives and loaded and empty wagons to fulfill a given transport demand. Using the entire Swedish rail network with real-world demand data, we show that our framework can produce national freight transportation plans that fulfill all demands and bounds on railway capacity and vehicle circulations. The framework allows for comparison of scenarios with different transport demand and capacity supply. The results highlight its potential as a tool for strategic decision-making in national freight transport planning. • Computational pipeline to create railway freight transportation plans. • Optimization model linking fleet sizing, flow assignment, and scheduling. • Produces cyclic large-scale plans that meet all freight transport needs. • Allows adding railway system dynamics in strategic freight models.