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The New Dutch Timetable: The OR Revolution

Author

Listed:
  • Leo Kroon

    (Department of Logistics, Netherlands Railways (NS), NL-3500 HA Utrecht, and Rotterdam School of Management, Erasmus University Rotterdam, NL-3000 DR Rotterdam, The Netherlands)

  • Dennis Huisman

    (Department of Logistics, Netherlands Railways (NS), NL-3500 HA Utrecht, and Econometric Institute, Erasmus University Rotterdam, NL-3000 DR Rotterdam, The Netherlands)

  • Erwin Abbink

    (Department of Logistics, Netherlands Railways (NS), NL-3500 HA Utrecht, The Netherlands)

  • Pieter-Jan Fioole

    (Department of Logistics, Netherlands Railways (NS), NL-3500 HA Utrecht, The Netherlands)

  • Matteo Fischetti

    (Department of Information Engineering, University of Padova, and Double-Click sas, I-35131 Padova, Italy)

  • Gábor Maróti

    (Rotterdam School of Management, Erasmus University Rotterdam, NL-3000 DR Rotterdam, The Netherlands)

  • Alexander Schrijver

    (Center for Mathematics and Computer Science (CWI), Amsterdam, and University of Amsterdam, NL-1098 SJ Amsterdam, The Netherlands)

  • Adri Steenbeek

    (Safiro Software Solutions, NL-1303 AJ Almere, The Netherlands)

  • Roelof Ybema

    (Department of Logistics, Netherlands Railways (NS), NL-3500 HA Utrecht, The Netherlands)

Abstract

In December 2006, Netherlands Railways introduced a completely new timetable. Its objective was to facilitate the growth of passenger and freight transport on a highly utilized railway network and improve the robustness of the timetable, thus resulting in fewer operational train delays. Modifications to the existing timetable, which was constructed in 1970, were not an option; additional growth would require significant investments in the rail infrastructure. Constructing a railway timetable from scratch for about 5,500 daily trains was a complex problem. To support this process, we generated several timetables using sophisticated operations research techniques. Furthermore, because rolling-stock and crew costs are principal components of the costs of a passenger railway operator, we used innovative operations research tools to devise efficient schedules for these two resources. The new resource schedules and the increased number of passengers resulted in an additional annual profit of €40 million ($60 million); the additional revenues generated approximately €10 million of this profit. We expect this profit to increase to €70 million ($105 million) annually in the coming years. However, the benefits of the new timetable for the Dutch society as a whole are much greater: more trains are transporting more passengers on the same railway infrastructure, and these trains are arriving and departing on schedule more than they ever have in the past. In addition, the rail transport system will be able to handle future transportation demand growth and thus allow cities to remain accessible to more people. Therefore, we expect that many will switch from car transport to rail transport, thus reducing the emission of greenhouse gases.

Suggested Citation

  • Leo Kroon & Dennis Huisman & Erwin Abbink & Pieter-Jan Fioole & Matteo Fischetti & Gábor Maróti & Alexander Schrijver & Adri Steenbeek & Roelof Ybema, 2009. "The New Dutch Timetable: The OR Revolution," Interfaces, INFORMS, vol. 39(1), pages 6-17, February.
    • Handle: RePEc:inm:orinte:v:39:y:2009:i:1:p:6-17
    DOI: 10.1287/inte.1080.0409
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    References listed on IDEAS

    as
    1. Abbink, E.J.W., 2008. "Solving large scale crew scheduling problems by using iterative partitioning," Econometric Institute Research Papers EI 2008-03, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. 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.
    3. Fioole, Pieter-Jan & Kroon, Leo & Maroti, Gabor & Schrijver, Alexander, 2006. "A rolling stock circulation model for combining and splitting of passenger trains," European Journal of Operational Research, Elsevier, vol. 174(2), pages 1281-1297, October.
    4. Jurjen S. Hooghiemstra & Leo G. Kroon & Michiel A. Odijk & Marc Salomon & Peter J. Zwaneveld, 1999. "Decision Support Systems Support the Search for Win-Win Solutions in Railway Network Design," Interfaces, INFORMS, vol. 29(2), pages 15-32, April.
    5. Abbink, E.J.W. & Albino, L. & Dollevoet, T.A.B. & Huisman, D. & Roussado, J. & Saldanha, R.L., 2010. "Solving Large Scale Crew Scheduling Problems in Practice," Econometric Institute Research Papers EI 2010-63, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Zwaneveld, Peter J. & Kroon, Leo G. & van Hoesel, Stan P. M., 2001. "Routing trains through a railway station based on a node packing model," European Journal of Operational Research, Elsevier, vol. 128(1), pages 14-33, January.
    7. Erwin Abbink & Matteo Fischetti & Leo Kroon & Gerrit Timmer & Michiel Vromans, 2005. "Reinventing Crew Scheduling at Netherlands Railways," Interfaces, INFORMS, vol. 35(5), pages 393-401, October.
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