Allocation of Railway Rolling Stock for Passenger Trains

Erwin Abbink (), Bianca van den Berg (), Leo Kroon () and Marc Salomon ()
Additional contact information
Erwin Abbink: NS Reizigers, Department of Logistics, Utrecht, The Netherlands
Bianca van den Berg: Cap Gemini Ernst & Young, Utrecht, The Netherlands
Leo Kroon: NS Reizigers, Department of Logistics, Utrecht, The Netherlands, and Rotterdam School of Management, Erasmus University Rotterdam, Rotterdam, The Netherlands
Marc Salomon: Department of Economics and Econometrics, Tilburg University, Tilburg, The Netherlands, and McKinsey & Company, Amsterdam, The Netherlands

Transportation Science, 2004, vol. 38, issue 1, 33-41

Abstract: For a commercially operating railway company, providing a high level of service for the passengers is of utmost importance. The latter requires high punctuality of the trains and an adequate rolling stock capacity. Unfortunately, the latter is currently (in 2002) one of the bottlenecks in the service provision by the main Dutch railway operator NS Reizigers. Especially during the morning rush hours, many passengers cannot be transported according to the usual service standards because of a shortage of the rolling stock capacity. On the other hand, a more effective allocation of the available rolling stock capacity seems to be feasible, because there are also several trains with some slack capacity.The effectiveness of the rolling stock capacity is determined mainly by the allocation of the train types and subtypes to the lines. Therefore, we describe in this paper a model that can be used to find an optimal allocation of train types and subtypes to the lines. This optimal allocation is more effective than the manually planned one, which is accomplished by minimizing the shortages of capacity during the rush hours.The model is implemented in the modeling language OPL Studio 3.1, solved by CPLEX 7.0, and tested on several scenarios based on the 2001–2002 timetable of NS Reizigers. The results of the model were received positively, both by the planners and by the management in practice, because these results showed that a significant service improvement over the manually planned allocation can be achieved within a shorter throughput time of the involved part of the planning process.

Keywords: rail transportation; railway systems; rolling stock planning; capacity allocation (search for similar items in EconPapers)
Date: 2004
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

Downloads: (external link)
http://dx.doi.org/10.1287/trsc.1030.0044 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ortrsc:v:38:y:2004:i:1:p:33-41

Access Statistics for this article

More articles in Transportation Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().