Scheduling trains is a very important element of value chain decision-making. Train scheduling models are often quite complex given the very long distances trains may travel combined with very accurate train timings and different physical train characteristics. This talks addresses a novel formulation for train scheduling using a mixed-integer linear programming formulation originally developed for Process Industries: the Unit-Operation-Port-State Superstructure (UOPSS), which allows the train scheduling model to be seamlessly integrated with adjacent production, storage and distribution elements of the value chain. This model has been implemented in the Hatch Rail Optimizer (HRO) software and applied in industrial settings.