IDEAS home Printed from https://ideas.repec.org/a/spr/operea/v23y2023i3d10.1007_s12351-023-00786-6.html
   My bibliography  Save this article

Optimisation of seat reservations on trains to minimise transfer distances

Author

Listed:
  • Karsten Weicker

    (HTWK Leipzig University of Applied Sciences)

Abstract

This paper introduces a novel optimisation problem motivated by the real-world application of transferring between trains. The driving idea is to minimise the walking distances of all transferring passengers by optimising the assignment of passengers to railcarriages in the seat reservation process. The focus of this work is on formalising and modelling the problem, which has not been studied before. It aims to provide a framework for future considerations. We present three versions of the problem with increasing difficulty: one-train-one-station, one-train-many-stations, and a general problem with multiple trains and stations. Since the simplest version of the problem is a pure assignment problem in the form of minimum-cost bipartite matching, our problem modelling and algorithmic solution approach remain closely related to maxflow problems as they represent a proven method for assignment problems. However, even the one-train-many-stations problem cannot be solved by transforming it into a standard maximum-flow problem. The main result shown is the NP-hardness of the general problem.

Suggested Citation

  • Karsten Weicker, 2023. "Optimisation of seat reservations on trains to minimise transfer distances," Operational Research, Springer, vol. 23(3), pages 1-31, September.
    • Handle: RePEc:spr:operea:v:23:y:2023:i:3:d:10.1007_s12351-023-00786-6
    DOI: 10.1007/s12351-023-00786-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12351-023-00786-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12351-023-00786-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Clausen, Tommy & Hjorth, Allan Nordlunde & Nielsen, Morten & Pisinger, David, 2010. "The off-line group seat reservation problem," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1244-1253, December.
    2. Zhou, Yu & Wang, Yun & Yang, Hai & Yan, Xuedong, 2019. "Last train scheduling for maximizing passenger destination reachability in urban rail transit networks," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 79-95.
    3. Dennis Huisman & Leo G. Kroon & Ramon M. Lentink & Michiel J. C. M. Vromans, 2005. "Operations Research in passenger railway transportation," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 59(4), pages 467-497, November.
    4. Chu, James C. & Korsesthakarn, Kanticha & Hsu, Yu-Ting & Wu, Hua-Yen, 2019. "Models and a solution algorithm for planning transfer synchronization of bus timetables," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 131(C), pages 247-266.
    5. H. W. Kuhn, 1955. "The Hungarian method for the assignment problem," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 2(1‐2), pages 83-97, March.
    6. Paola Cappanera & Antonio Frangioni, 2003. "Symmetric and Asymmetric Parallelization of a Cost-Decomposition Algorithm for Multicommodity Flow Problems," INFORMS Journal on Computing, INFORMS, vol. 15(4), pages 369-384, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. András Frank, 2005. "On Kuhn's Hungarian Method—A tribute from Hungary," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(1), pages 2-5, February.
    2. Amit Kumar & Anila Gupta, 2013. "Mehar’s methods for fuzzy assignment problems with restrictions," Fuzzy Information and Engineering, Springer, vol. 5(1), pages 27-44, March.
    3. Gianmarco Garrisi & Cristina Cervelló-Pastor, 2019. "Train-Scheduling Optimization Model for Railway Networks with Multiplatform Stations," Sustainability, MDPI, vol. 12(1), pages 1-25, December.
    4. Parvin Ahmadi & Iman Gholampour & Mahmoud Tabandeh, 2018. "Cluster-based sparse topical coding for topic mining and document clustering," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 12(3), pages 537-558, September.
    5. Canca, David & Barrena, Eva, 2018. "The integrated rolling stock circulation and depot location problem in railway rapid transit systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 109(C), pages 115-138.
    6. Chenchen Ma & Jing Ouyang & Gongjun Xu, 2023. "Learning Latent and Hierarchical Structures in Cognitive Diagnosis Models," Psychometrika, Springer;The Psychometric Society, vol. 88(1), pages 175-207, March.
    7. Aidin Rezaeian & Hamidreza Koosha & Mohammad Ranjbar & Saeed Poormoaied, 2024. "The assignment of project managers to projects in an uncertain dynamic environment," Annals of Operations Research, Springer, vol. 341(2), pages 1107-1134, October.
    8. Wang, Tao & Huang, Li & Tian, Junfang & Zhang, Jing & Yuan, Zijian & Zheng, Jianfeng, 2024. "Bus dwell time estimation and overtaking maneuvers analysis: A stochastic process approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 186(C).
    9. Tran Hoang Hai, 2020. "Estimation of volatility causality in structural autoregressions with heteroskedasticity using independent component analysis," Statistical Papers, Springer, vol. 61(1), pages 1-16, February.
    10. Caplin, Andrew & Leahy, John, 2020. "Comparative statics in markets for indivisible goods," Journal of Mathematical Economics, Elsevier, vol. 90(C), pages 80-94.
    11. Biró, Péter & Gudmundsson, Jens, 2021. "Complexity of finding Pareto-efficient allocations of highest welfare," European Journal of Operational Research, Elsevier, vol. 291(2), pages 614-628.
    12. Péter Biró & Flip Klijn & Xenia Klimentova & Ana Viana, 2021. "Shapley-Scarf Housing Markets: Respecting Improvement, Integer Programming, and Kidney Exchange," Working Papers 1235, Barcelona School of Economics.
    13. Michal Brylinski, 2014. "eMatchSite: Sequence Order-Independent Structure Alignments of Ligand Binding Pockets in Protein Models," PLOS Computational Biology, Public Library of Science, vol. 10(9), pages 1-15, September.
    14. Lin, Zhiyuan & Kwan, Raymond S.K., 2016. "A branch-and-price approach for solving the train unit scheduling problem," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 97-120.
    15. David Schindl & Nicolas Zufferey, 2015. "A learning tabu search for a truck allocation problem with linear and nonlinear cost components," Naval Research Logistics (NRL), John Wiley & Sons, vol. 62(1), pages 32-45, February.
    16. Chiwei Yan & Helin Zhu & Nikita Korolko & Dawn Woodard, 2020. "Dynamic pricing and matching in ride‐hailing platforms," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(8), pages 705-724, December.
    17. Fanrong Xie & Anuj Sharma & Zuoan Li, 2022. "An alternate approach to solve two-level priority based assignment problem," Computational Optimization and Applications, Springer, vol. 81(2), pages 613-656, March.
    18. Yan, Pengyu & Lee, Chung-Yee & Chu, Chengbin & Chen, Cynthia & Luo, Zhiqin, 2021. "Matching and pricing in ride-sharing: Optimality, stability, and financial sustainability," Omega, Elsevier, vol. 102(C).
    19. Kroon, L.G. & Huisman, D. & Abbink, E.J.W. & Fioole, P-J. & Fischetti, M. & Maróti, G. & Schrijver, A. & Steenbeek, A. & Ybema, R., 2008. "The new Dutch timetable: The OR revolution," Econometric Institute Research Papers EI 2008-19, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    20. Zheng, Hankun & Sun, Huijun & Kang, Liujiang & Dai, Peiling & Wu, Jianjun, 2023. "Multi-route coordination for bus systems in response to road disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:operea:v:23:y:2023:i:3:d:10.1007_s12351-023-00786-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.