Increasing the effectiveness of the capacity usage at rolling stock service locations

Journal Article (2022)
Author(s)

Madeleine E.M.A. van Hövell (Student TU Delft)

R.M.P. Goverde (TU Delft - Transport and Planning)

N Bešinović (TU Delft - Transport and Planning)

M.M. de Weerdt (TU Delft - Algorithmics)

Transport and Planning
Copyright
© 2022 Madeleine E.M.A. van Hövell, R.M.P. Goverde, Nikola Bešinović, M.M. de Weerdt
DOI related publication
https://doi.org/10.1016/j.jrtpm.2022.100297
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 Madeleine E.M.A. van Hövell, R.M.P. Goverde, Nikola Bešinović, M.M. de Weerdt
Transport and Planning
Volume number
21
Pages (from-to)
1-15
Reuse Rights

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Abstract

Trains consist of one or more railway vehicles called rolling stock, which need interior and exterior cleaning and small technical checks on a daily basis. These services are executed at service locations (SLs). Scheduling rolling stock servicing tasks during an operational day is important to guarantee the fulfilment of servicing deadlines. Public transport companies face large scheduling problems, especially those with 24-hour-a-day operation. The expected increase in transport frequencies enhances the need for improving scheduling servicing tasks during an operational day. Therefore, the Rolling Stock Servicing Scheduling Problem (RS-SSP) is modelled comprising a MILP model. Complying with the planned timetable, the RS-SSP maximises the RS units being serviced during daytime. The RS-SSP allows RS exchanges between RS units having completed servicing and operating RS units requiring servicing. Due to this RS Exchange Concept, the number of RS units visiting the SL during daytime can be increased. The proposed RS-SSP model has been tested on a real-life case from the Dutch railways. For multiple scenarios, the model was able to exchange all running RS. Consequently, the capacity usage at SLs can be increased by the RS-SSP by shifting some of the excessive workload to daytime, and thus solving the capacity shortages.