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Solving large scale crew scheduling problems by using iterative partitioning

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  • Abbink, E.J.W.

Abstract

This paper deals with large-scale crew scheduling problems arising at the Dutch railway operator, Netherlands Railways (NS). NS operates about 30,000 trains a week. All these trains need a driver and a certain number of conductors. No available crew scheduling algorithm can solve such huge instances at once. A common approach to deal with these huge weekly instances, is to split them into several daily instances and solve those separately. However, we found out that this can be rather inefficient. In this paper, we discuss several methods to partition huge instances into several smaller ones. These smaller instances are then solved with the commercially available crew scheduling algorithm TURNI. We compare these partitioning methods with each other, and we report several results where we applied different partitioning methods after each other. The results show that all methods significantly improve the solution. With the best approach, we were able to cut down crew costs with about 2\\% (about 6 million euro per year).

Suggested Citation

  • 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.
  • Handle: RePEc:ems:eureir:11701
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    References listed on IDEAS

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    1. 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.
    2. Hartog, A. & Huisman, D. & Abbink, E.J.W. & Kroon, L.G., 2006. "Decision support for crew rostering at NS," Econometric Institute Research Papers EI 2006-04, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
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    5. Karla L. Hoffman & Manfred Padberg, 1993. "Solving Airline Crew Scheduling Problems by Branch-and-Cut," Management Science, INFORMS, vol. 39(6), pages 657-682, June.
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    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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    Cited by:

    1. Piotr Gołębiowski & Marianna Jacyna & Andrzej Stańczak, 2021. "The Assessment of Energy Efficiency versus Planning of Rail Freight Traffic: A Case Study on the Example of Poland," Energies, MDPI, vol. 14(18), pages 1-18, September.
    2. 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.
    3. 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.
    4. 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.

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