As the relevance of rail transport continues to grow, efficient operational planning becomes increasingly critical. This is also evident at stations, where unused trains must be moved to the yard and returned to the platform when needed. To achieve this, available drivers must be assigned to trains in a way that respects the time constraints of their shifts. This thesis explores the approach of combining the shunt routing problem (SRP), where times for routes of shunt trains are calculated, with the drivers' problem, which deals with creating feasible driver schedules. The resulting Constraint Programming (CP) model is based on an existing CP model for the SRP. This combined model is tested on four stations in the Netherlands and solves the problem in under 200 seconds for the Vlissingen and Enkhuizen stations, while higher runtimes for Enschede and Amersfoort are observed.
Experiments with an alternative model structure highlight how the linking of the train and driver variables influences runtime significantly. Several variable and value selection strategies are examined on multiple variables, improving performance for certain instances. Furthermore, the analysis reveals that runtime is highly dependent on the station and instance characteristics.
By combining the SRP with the drivers’ problem, this thesis delivers a functional CP model applicable across all stations and contributes to a deeper understanding of the integration of the two problems.