EETTlib—Energy‐efficient train timetabling library. Issue 1 (21st July 2022)

• Record Type: Journal Article
• Authors: Bärmann, Andreas; Gemander, Patrick; Hager, Lukas; Nöth, Frederik; Schneider, Oskar
• Is Part Of: Networks. Volume 81:Issue 1(2023)
• Page Start: 51
• Page End: 74
• Publication Date: 2022-07-21
• Subjects: benchmark library -- clique problem -- energy consumption -- multiple‐choice constraints -- project scheduling problem -- railway timetabling; Network analysis (Planning) -- Periodicals; 658.4032
• DOI: 10.1002/net.22117
• Languages: English
• ISSNs: 0028-3045

Abstract

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 Nürnberg, 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 https://www.eettlib.fau.de .