Abstract
Deutsche Bahn, one of the largest European railway companies, offers mainly two products to commercial and industrial customers for freight transportation. Customers with high demand order unit trains , that are pulled by one or two locomotives from their respective origins to their destinations. In contrast, customers with less demand order a limited amount of single cars , that are first pulled to a classification yard. There they are grouped together with single cars from other customers into a train unit. On the way from their respective origins via intermediate yards to their destinations, the cars are reclassified several times, which is a time-consuming and personnel-intensive procedure. To support the strategic long-term planning process of the single car freight routing, a mathematical optimization tool based on mixed-integer nonlinear programming was developed and is in practice use since 2011. However, real-world constraints have changed over the last years. For example, unit trains and single cars are no longer strictly separated products, but they are more and more integrated: In some unit trains there are still residual capacities that can be used for single cars. For some of these additional new requirements, the existing optimization tool has to be extended slightly by formulating new additional mathematical constraints. For some other requirements, a substantial redevelopment will be necessary in the future. The purpose of this chapter is to review the existing single car routing model, to discuss how it is used in real-life, and to demonstrate how it can be extended to meet the new requirements in the present and future.
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Fügenschuh, A., Homfeld, H., Johann, M., Schülldorf, H., Stieber, A. (2018). Use of Optimization Tools for Routing in Rail Freight Transport. In: Borndörfer, R., Klug, T., Lamorgese, L., Mannino, C., Reuther, M., Schlechte, T. (eds) Handbook of Optimization in the Railway Industry. International Series in Operations Research & Management Science, vol 268. Springer, Cham. https://doi.org/10.1007/978-3-319-72153-8_8
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