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Faculty of Mechanical Engineering
Studenten im Sommer auf dem Campus Nord, rote Zahnräder im Hintergrund © Roland Baege​/​TU Dortmund

KOSMOS: Hub Location Planning in Rail Freight Traffic

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  • Mathematical Optimization

Background

Growing volumes in (international) freight traffic give the chance to increase rail freight transportation. However, the current network structure and in particular, central corridors are already highly utilized.   Building up new infrastructure elements is highly cost intensive and therefore, has a strategic planning horizon.

These difficulties motivated the joint research project „Komplexe Optimierungsstrategien für Mobilität und Verkehr auf der Schiene (KOSMOS)“ funded by the Federal Ministry of Education and Research (BMBF). Under the aegis of Prof. Dr. Zimmermann (Institute for Mathematical Optimization, TU Braunschweig), five chairs and institutes worked together with the project partner Deutsche Bahn on several research projects in order to improve rail (freight) traffic.  The ITL took part in this research project within the project “Hub-Location-Planung im Schienenverkehr”.

Procedure

In cooperation with Deutsche Bahn, we defined the system to be optimized. The main characteristics and restrictions of wagonload traffic were considered. However, the current hierarchical structures of wagonload traffic were not considered aiming at a more flexible system. Based on this system description, we developed mathematical optimization models for the hub location problem in German wagonload traffic. In order to solve real-sized instances, we developed efficient solution approaches to solve real-sized instances.  Currently, the approaches are implemented in the systems of Deutsche Bahn. The cooperation allowed us to develop models and solution approaches for real-life applications.

Targeted results

The aim of the research was to develop new mathematical models for a real-life location and network design problem in wagonload traffic. Based on the model, efficient matheuristics which combine meta-heuristic and exact solution approaches were developed. The matheuristic is able to find good solutions for real-sized data sets.

Contact: Prof. Dr.-Ing. Uwe Clausen

Funding and partners

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