Document Open Access Logo

Vehicle Capacity-Aware Rerouting of Passengers in Delay Management

Authors Matthias Müller-Hannemann , Ralf Rückert, Sebastian S. Schmidt



PDF
Thumbnail PDF

File

OASIcs.ATMOS.2019.7.pdf
  • Filesize: 477 kB
  • 14 pages

Document Identifiers

Author Details

Matthias Müller-Hannemann
  • Institut für Informatik, Martin-Luther-Universität Halle-Wittenberg, Von-Seckendorff-Platz 1, D 06120 Halle (Saale), Germany
Ralf Rückert
  • Institut für Informatik, Martin-Luther-Universität Halle-Wittenberg, Von-Seckendorff-Platz 1, D 06120 Halle (Saale), Germany
Sebastian S. Schmidt
  • Institut für Informatik, Martin-Luther-Universität Halle-Wittenberg, Von-Seckendorff-Platz 1, D 06120 Halle (Saale), Germany

Acknowledgements

The authors wish to thank Deutsche Bahn for providing test data.

Cite AsGet BibTex

Matthias Müller-Hannemann, Ralf Rückert, and Sebastian S. Schmidt. Vehicle Capacity-Aware Rerouting of Passengers in Delay Management. In 19th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2019). Open Access Series in Informatics (OASIcs), Volume 75, pp. 7:1-7:14, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2019)
https://doi.org/10.4230/OASIcs.ATMOS.2019.7

Abstract

Due to the significant growth in passenger numbers, higher vehicle load factors and crowding become more and more of an issue in public transport. For safety reasons and because of an unsatisfactory discomfort, standing of passengers is rather limited in high-speed long-distance trains. In case of delays and (partially) cancelled trains, many passengers have to be rerouted. State-of-the-art rerouting merely focuses on minimizing delay at the destination of affected passengers but neglects limited vehicle capacities and crowding. Not considering capacities allows using highly efficient shortest path algorithms like RAPTOR or the connection scan algorithm (CSA). In this paper, we study the more complicated scenario where passengers compete for scarce capacities. This can be modeled as a piece-wise linear, convex cost multi-source multi-commodity unsplittable flow problem where each passenger group which has to be rerouted corresponds to a commodity. We compare a path-based integer linear programming (ILP) model with a heuristic greedy approach. In experiments with instances from German long-distance train traffic, we quantify the importance of considering vehicle capacities in case of train cancellations. We observe a tradeoff: The ILP approach slightly outperforms the greedy approach and both are much better than capacity unaware rerouting in quality, while the greedy algorithm runs more than three times faster.

Subject Classification

ACM Subject Classification
  • Applied computing → Transportation
  • Theory of computation → Discrete optimization
  • Mathematics of computing → Network flows
Keywords
  • Delay management
  • passenger flows
  • vehicle capacities
  • rerouting

Metrics

  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    0
    PDF Downloads

References

  1. Ittai Abraham, Daniel Delling, Andrew V. Goldberg, and Renato F. Werneck. Alternative Routes in Road Networks. J. Experimental Algorithmics, 18:1.3:1.1-1.3:1.17, 2013. URL: https://doi.org/10.1145/2444016.2444019.
  2. Ravindra K. Ahuja, Thomas L. Magnanti, and James B. Orlin. Network flows. Prentice Hall, Inc., 1993. Google Scholar
  3. Cynthia Barnhart, Christopher A. Hane, and Pamela H. Vance. Using Branch-and-Price-and-Cut to Solve Origin-Destination Integer Multicommodity Flow Problems. Oper. Res., 48(2):318-326, 2000. URL: https://doi.org/10.1287/opre.48.2.318.12378.
  4. Hannah Bast, Daniel Delling, Andrew V. Goldberg, Matthias Müller-Hannemann, Thomas Pajor, Peter Sanders, Dorothea Wagner, and Renato F. Werneck. Route Planning in Transportation Networks. In Lasse Kliemann and Peter Sanders, editors, Algorithm Engineering - Selected Results and Surveys, volume 9220 of Lecture Notes in Computer Science, pages 19-80. Springer, 2016. URL: https://doi.org/10.1007/978-3-319-49487-6_2.
  5. Daniel Delling, Thomas Pajor, and Renato F. Werneck. Round-Based Public Transit Routing. Transportation Science, 49(3):591-604, 2015. URL: https://doi.org/10.1287/trsc.2014.0534.
  6. Julian Dibbelt, Thomas Pajor, Ben Strasser, and Dorothea Wagner. Intriguingly Simple and Fast Transit Routing. In Vincenzo Bonifaci, Camil Demetrescu, and Alberto Marchetti-Spaccamela, editors, Experimental Algorithms, SEA 2013, volume 7933 of Lecture Notes in Computer Science, pages 43-54. Springer, 2013. URL: https://doi.org/10.1007/978-3-642-38527-8_6.
  7. Julian Dibbelt, Thomas Pajor, Ben Strasser, and Dorothea Wagner. Connection Scan Algorithm. ACM Journal of Experimental Algorithmics, 23:1.7:1-1.7:56, 2018. URL: https://doi.org/10.1145/3274661.
  8. Twan Dollevoet and Dennis Huisman. Fast heuristics for delay management with passenger rerouting. Public Transport, 6(1-2):67-84, 2014. URL: https://doi.org/10.1007/s12469-013-0076-6.
  9. Twan Dollevoet, Dennis Huisman, Marie Schmidt, and Anita Schöbel. Delay Management with Re-Routing of Passengers. Transportation Science, 46(1):74-89, 2012. URL: https://doi.org/10.1287/trsc.1110.0375.
  10. Twan Dollevoet, Dennis Huisman, Marie Schmidt, and Anita Schöbel. Delay propagation and delay management in transportation networks. In Ralf Borndörfer, Torsten Klug, Leonardo Lamorgese, Carlo Mannino, Markus Reuther, and Thomas Schlechte, editors, Handbook of Optimization in the Railway Industry, pages 285-317. Springer International Publishing, 2018. Google Scholar
  11. David Eppstein. Finding the K Shortest Paths. SIAM J. Comput., 28(2):652-673, 1999. URL: https://doi.org/10.1137/S0097539795290477.
  12. Bernard Fortz, Luís Gouveia, and Martim Joyce-Moniz. Models for the piecewise linear unsplittable multicommodity flow problems. European Journal of Operational Research, 261(1):30-42, 2017. URL: https://doi.org/10.1016/j.ejor.2017.01.051.
  13. Luke Haywood, Martin Koning, and Guillaume Monchambert. Crowding in public transport: Who cares and why? Transportation Research Part A: Policy and Practice, 100:215-227, 2017. Google Scholar
  14. Zhiyuan Huang, Ruihua Xu, Wei D. Fan, Feng Zhou, and Wei Liu. Service-Oriented Load Balancing Approach to Alleviating Peak-Hour Congestion in a Metro Network Based on Multi-Path Accessibility. Sustainability, 11:1293, 2019. URL: https://doi.org/10.3390/su11051293.
  15. Zheng Li and David A. Hensher. Crowding in Public Transport: A review of objective and subjective measures. Journal of Public Transportation, 16:107-134, 2013. Google Scholar
  16. Matthias Müller-Hannemann and Ralf Rückert. Dynamic Event-Activity Networks in Public Transportation - Timetable Information and Delay Management. Datenbank-Spektrum, 17:131-137, 2017. URL: https://doi.org/10.1007/s13222-017-0252-y.
  17. Matthias Müller-Hannemann, Frank Schulz, Dorothea Wagner, and Christos Zaroliagis. Timetable Information: Models and Algorithms. In Algorithmic Methods for Railway Optimization, volume 4395 of Lecture Notes in Computer Science, pages 67-89. Springer, 2007. Google Scholar
  18. Adam J. Pel, Nick H. Bel, and Marits Pieters. Including passengers’ response to crowding in the Dutch national train passenger assignment model. Transportation Research Part A: Policy and Practice, 66:111-126, 2014. URL: https://doi.org/10.1016/j.tra.2014.05.007.
  19. Ralf Rückert, Martin Lemnian, Christoph Blendinger, Steffen Rechner, and Matthias Müller-Hannemann. PANDA: a software tool for improved train dispatching with focus on passenger flows. Public Transport, 9(1):307-324, 2017. URL: https://doi.org/10.1007/s12469-016-0140-0.
  20. Marie Schmidt. Simultaneous optimization of delay management decisions and passenger routes. Public Transport, 5:125-147, 2013. URL: https://doi.org/10.1007/s12469-013-0069-5.
  21. Anita Schöbel. A Model for the Delay Management Problem based on Mixed-Integer Programming. Electronic Notes in Theoretical Computer Science, 50(1), 2001. Google Scholar
  22. Anita Schöbel. Customer-oriented optimization in public transportation. Springer, Berlin, 2006. Google Scholar
  23. I-Lin Wang. Multicommodity Network Flows: A Survey, Part II: Solution Methods. International Journal of Operations Research, 15:155-173, 2018. Google Scholar
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail