EETTlib-Energy-efficient train timetabling library

Bärmann A, Gemander P, Hager L, Noeth F, Schneider O (2022)

Publication Type: Journal article

Publication year: 2022

Journal

Networks Wiley-Blackwell

DOI: 10.1002/net.22117

Abstract

We introduce EETTlib, an instance library for the Energy-Efficient Train Timetabling problem. The task in this problem is to adjust a given timetable draft such that the energy consumption of the resulting railway traffic is minimized. To this end, the departure times of the trains can be slightly, and their velocity profiles on each trip can be modified. We provide real-world data originating from two research projects in this field, one with Deutsche Bahn AG, the most important railway company in Germany, the other with VAG Verkehrs-Aktiengesellschaft, the operator of public transport in the city of Nurnberg, Germany. In both cases, our library contains representative data on the relevant operational constraints and supports various possible choices for the objective function with respect to energy-efficiency. The resulting benchmark instances can be used by the scheduling and timetabling community to improve their models and algorithms. They are available under .

Authors with CRIS profile

Andreas Bärmann Lehrstuhl für Analytics & Mixed-Integer Optimization Lukas Hager Lehrstuhl für Analytics & Mixed-Integer Optimization

Involved external institutions

Fraunhofer-Institut für Integrierte Schaltungen (IIS) DE Germany (DE) VAG Verkehrs-Aktiengesellschaft Nürnberg DE Germany (DE)

How to cite

APA:

Bärmann, A., Gemander, P., Hager, L., Noeth, F., & Schneider, O. (2022). EETTlib-Energy-efficient train timetabling library. Networks. https://dx.doi.org/10.1002/net.22117

MLA:

Bärmann, Andreas, et al. "EETTlib-Energy-efficient train timetabling library." Networks (2022).

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