Periodic Timetabling with Cyclic Order Constraints

Authors Enrico Bortoletto , Niels Lindner , Berenike Masing



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Author Details

Enrico Bortoletto
  • Zuse Institute Berlin, Germany
Niels Lindner
  • Freie Universität Berlin, Germany
Berenike Masing
  • Zuse Institute Berlin, Germany

Acknowledgements

We thank DB Netz AG for providing real-world data and timetabling parameters for the S-Bahn Berlin network.

Cite AsGet BibTex

Enrico Bortoletto, Niels Lindner, and Berenike Masing. Periodic Timetabling with Cyclic Order Constraints. In 23rd Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2023). Open Access Series in Informatics (OASIcs), Volume 115, pp. 7:1-7:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
https://doi.org/10.4230/OASIcs.ATMOS.2023.7

Abstract

Periodic timetabling for highly utilized railway networks is a demanding challenge. We formulate an infrastructure-aware extension of the Periodic Event Scheduling Problem (PESP) by requiring that not only events, but also activities using the same infrastructure must be separated by a minimum headway time. This extended problem can be modeled as a mixed-integer program by adding constraints on the sum of periodic tensions along certain cycles, so that it shares some structural properties with standard PESP. We further refine this problem by fixing cyclic orders at each infrastructure element. Although the computational complexity remains unchanged, the mixed-integer programming model then becomes much smaller. Furthermore, we also discuss how to find a minimal subset of infrastructure elements whose cyclic order already prescribes the order for the remaining parts of the network, and how cyclic order information can be modeled in a mixed-integer programming context. In practice, we evaluate the impact of cyclic orders on a real-world instance on the S-Bahn Berlin network, which turns out to be computationally fruitful.

Subject Classification

ACM Subject Classification
  • Applied computing → Transportation
  • Mathematics of computing → Permutations and combinations
  • Mathematics of computing → Combinatorial optimization
Keywords
  • Periodic Timetabling
  • Railway Timetabling
  • Periodic Event Scheduling Problem
  • Cyclic Orders
  • Mixed-Integer Programming

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References

  1. R. Borndörfer, N. Lindner, and S. Roth. A concurrent approach to the periodic event scheduling problem. Journal of Rail Transport Planning & Management, 15:100175, 2020. Best Papers of RailNorrköping 2019. URL: https://doi.org/10.1016/j.jrtpm.2019.100175.
  2. E. Bortoletto, N. Lindner, and B. Masing. Tropical Neighbourhood Search: A New Heuristic for Periodic Timetabling. In M. D'Emidio and N. Lindner, editors, 22nd Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2022), volume 106 of Open Access Series in Informatics (OASIcs), pages 3:1-3:19, Dagstuhl, Germany, 2022. Schloss Dagstuhl - Leibniz-Zentrum für Informatik. URL: https://doi.org/10.4230/OASIcs.ATMOS.2022.3.
  3. F. Fuchs, A. Trivella, and F. Corman. Enhancing the interaction of railway timetabling and line planning with infrastructure awareness. Transportation Research Part C: Emerging Technologies, 142:103805, September 2022. URL: https://doi.org/10.1016/j.trc.2022.103805.
  4. M. Goerigk. PESPlib - A benchmark library for periodic event scheduling, 2012. URL: http://num.math.uni-goettingen.de/~m.goerigk/pesplib/.
  5. P. Großmann, S. Hölldobler, N. Manthey, K. Nachtigall, J. Opitz, and P. Steinke. Solving Periodic Event Scheduling Problems with SAT. In H. Jiang, W. Ding, M. Ali, and X. Wu, editors, Advanced Research in Applied Artificial Intelligence, Lecture Notes in Computer Science, pages 166-175, Berlin, Heidelberg, 2012. Springer. URL: https://doi.org/10.1007/978-3-642-31087-4_18.
  6. C. Liebchen. Periodic timetable optimization in public transport. PhD thesis, Technische Universität Berlin, Berlin, 2006. Google Scholar
  7. C. Liebchen and R. H. Möhring. The Modeling Power of the Periodic Event Scheduling Problem: Railway Timetables — and Beyond. In F. Geraets, L. Kroon, A. Schoebel, D. Wagner, and C. D. Zaroliagis, editors, Algorithmic Methods for Railway Optimization, Lecture Notes in Computer Science, pages 3-40, Berlin, Heidelberg, 2007. Springer. URL: https://doi.org/10.1007/978-3-540-74247-0_1.
  8. C. Liebchen and L. Peeters. Integral cycle bases for cyclic timetabling. Discrete Optimization, 6(1):98-109, February 2009. URL: https://doi.org/10.1016/j.disopt.2008.09.003.
  9. R. M. Lusby, J. Larsen, M. Ehrgott, and D. Ryan. Railway track allocation: models and methods. OR Spectrum, 33(4):843-883, October 2011. URL: https://doi.org/10.1007/s00291-009-0189-0.
  10. B. Masing, N. Lindner, and C. Liebchen. Periodic Timetabling with Integrated Track Choice for Railway Construction Sites. Technical Report 22-26, Zuse Institute Berlin, 2022. URL: https://nbn-resolving.org/urn:nbn:de:0297-zib-88626.
  11. N. Megiddo. Partial and complete cyclic orders. Bulletin of the American Mathematical Society, 82(2):274-276, 1976. Google Scholar
  12. K. Nachtigall. Periodic Network Optimization and Fixed Interval Timetables. Habilitation Thesis, Universität Hildesheim, 1998. Google Scholar
  13. K. Nachtigall and J. Opitz. Solving Periodic Timetable Optimisation Problems by Modulo Simplex Calculations. In M. Fischetti and P. Widmayer, editors, 8th Workshop on Algorithmic Approaches for Transportation Modeling, Optimization, and Systems (ATMOS'08), volume 9 of OpenAccess Series in Informatics (OASIcs), Dagstuhl, Germany, 2008. Schloss Dagstuhl–Leibniz-Zentrum fuer Informatik. URL: https://doi.org/10.4230/OASIcs.ATMOS.2008.1588.
  14. M. A. Odijk. Construction of periodic timetables, part 1: A cutting plane algorithm. Technical Report 94-61, TU Delft, 1994. Google Scholar
  15. L. Peeters. Cyclic Railway Timetable Optimization. PhD thesis, Erasmus Universiteit Rotterdam, January 2003. Google Scholar
  16. Allianz pro Schiene e. V. Das Schienennetz in Deutschland, 2023. Retrieved on 08/07/2023. URL: https://www.allianz-pro-schiene.de/themen/infrastruktur/schienennetz/.
  17. P. Serafini and W. Ukovich. A mathematical model for periodic scheduling problems. SIAM J. Discret. Math., 2:550-581, 1989. Google Scholar
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