Improving the scheduling of railway maintenance projects by minimizing passenger delays subject to event requests of railway operators

Y.R. de Weert, K. Gkiotsalitis*, E.C. van Berkum

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


In the Netherlands, it is expected that passenger activities on railway networks will double by 2050. To manage the passenger demand, railway capacity planning needs to be adapted. One fundamental aspect of the railway capacity planning is the scheduling of large maintenance projects. These maintenance requests should not be scheduled during major events to avoid the disruption of service. To do so, passenger operators can submit event request, i.e., a time period and location in which no maintenance project should be scheduled. Currently, these event requests are considered as hard constraints and the flexibility in maintenance scheduling decreases resulting in conflicts. In this study, the focus is on scheduling maintenance projects to minimize passenger delays while relaxing the hard constraints of event requests. This problem is addressed by introducing a Mixed Integer Linear Program (MILP) that minimizes passenger delays while scheduling maintenance projects, which includes capacity constraints for alternative services in event request areas during maintenance projects. The computational complexity of the proposed model is reduced by adding valid inequalities from the Single Machine Scheduling problem and using a simulated annealing meta-heuristic to find a favorable initial solution guess. Then, the MILP is solved to global optimality with Branch-and-Bound. A case study on the Dutch railway network shows improvements when event requests are not considered as hard constraints and an increase in the flexibility to schedule maintenance projects. This allows decision makers to choose from a set of optimal maintenance schedules with different characteristics.
Original languageEnglish
Article number106580
JournalComputers & operations research
Early online date8 Feb 2024
Publication statusE-pub ahead of print/First online - 8 Feb 2024


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