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A Decomposition Method for Multiperiod Railway Network Expansion—With a Case Study for Germany

Author

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  • Andreas Bärmann

    (Department Mathematik, Friedrich–Alexander–Universität Erlangen–Nürnberg, 91058 Erlangen, Germany)

  • Alexander Martin

    (Department Mathematik, Friedrich–Alexander–Universität Erlangen–Nürnberg, 91058 Erlangen, Germany)

  • Hanno Schülldorf

    (DB Analytics, Deutsche Bahn AG, 60329 Frankfurt am Main, Germany)

Abstract

In this work, we report about the results of a joint research project between Friedrich–Alexander–Universität Erlangen–Nürnberg and Deutsche Bahn AG on the optimal expansion of the German railway network until 2030. The need to increase the throughput of the network is given by company-internal demand forecasts that indicate an increase in rail freight traffic of about 50% over the next two decades. Our focus is to compute an optimal investment strategy into line capacities given an available annual budget, i.e., we are to choose the most profitable lines to upgrade with respect to the demand scenario under consideration and to provide a schedule according to which the chosen measures are implemented. This leads to a multiperiod network design problem—a class of problems that has received increasing interest over the past decade. We develop a mixed-integer programming formulation to model the situation and solve it via a novel decomposition approach that we call multiple-knapsack decomposition. The method can both be used as a quick heuristic and allows for the extension to an exact algorithm for the problem. We demonstrate its potential by solving a real-world problem instance provided by Deutsche Bahn AG and use the results as the basis for a broad case study for the expansion of the German railway network until 2030.

Suggested Citation

  • Andreas Bärmann & Alexander Martin & Hanno Schülldorf, 2017. "A Decomposition Method for Multiperiod Railway Network Expansion—With a Case Study for Germany," Transportation Science, INFORMS, vol. 51(4), pages 1102-1121, November.
  • Handle: RePEc:inm:ortrsc:v:51:y:2017:i:4:p:1102-1121
    DOI: 10.1287/trsc.2017.0747
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    References listed on IDEAS

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    1. Hugo M. Repolho & António P. Antunes & Richard L. Church, 2013. "Optimal Location of Railway Stations: The Lisbon-Porto High-Speed Rail Line," Transportation Science, INFORMS, vol. 47(3), pages 330-343, August.
    2. Petersen, E. R. & Taylor, A. J., 2001. "An investment planning model for a new North-Central railway in Brazil," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(9), pages 847-862, November.
    3. Gendreau, Michel & Potvin, Jean-Yves & Smires, Ali & Soriano, Patrick, 2006. "Multi-period capacity expansion for a local access telecommunications network," European Journal of Operational Research, Elsevier, vol. 172(3), pages 1051-1066, August.
    4. Garcia, Bruno-Laurent & Mahey, Philippe & LeBlanc, Larry J., 1998. "Iterative improvement methods for a multiperiod network design problem," European Journal of Operational Research, Elsevier, vol. 110(1), pages 150-165, October.
    5. Marí­n, íngel & Jaramillo, Patricia, 2008. "Urban rapid transit network capacity expansion," European Journal of Operational Research, Elsevier, vol. 191(1), pages 45-60, November.
    6. Blanco, Víctor & Puerto, Justo & Ramos, Ana B., 2011. "Expanding the Spanish high-speed railway network," Omega, Elsevier, vol. 39(2), pages 138-150, April.
    7. Baxter, Matthew & Elgindy, Tarek & Ernst, Andreas T. & Kalinowski, Thomas & Savelsbergh, Martin W.P., 2014. "Incremental network design with shortest paths," European Journal of Operational Research, Elsevier, vol. 238(3), pages 675-684.
    8. Byung Kim & Wonkyu Kim & Byung Song, 2008. "Sequencing and scheduling highway network expansion using a discrete network design model," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(3), pages 621-642, September.
    9. Michael Kuby & Zhongyi Xu & Xiaodong Xie, 2001. "Railway network design with multiple project stages and time sequencing," Journal of Geographical Systems, Springer, vol. 3(1), pages 25-47, May.
    10. Kalinowski, Thomas & Matsypura, Dmytro & Savelsbergh, Martin W.P., 2015. "Incremental network design with maximum flows," European Journal of Operational Research, Elsevier, vol. 242(1), pages 51-62.
    11. Daniel Bienstock & Olga Raskina & Iraj Saniee & Qiong Wang, 2006. "Combined Network Design and Multiperiod Pricing: Modeling, Solution Techniques, and Computation," Operations Research, INFORMS, vol. 54(2), pages 261-276, April.
    12. Alejandro Toriello & George Nemhauser & Martin Savelsbergh, 2010. "Decomposing inventory routing problems with approximate value functions," Naval Research Logistics (NRL), John Wiley & Sons, vol. 57(8), pages 718-727, December.
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    Cited by:

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    3. Haque, Khademul & Mishra, Sabyasachee & Golias, Mihalis M., 2021. "Multi-period transportation network investment decision making and policy implications using econometric framework," Research in Transportation Economics, Elsevier, vol. 89(C).

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