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Construction of a Test Library for the Rolling Stock Rotation Problem with Predictive Maintenance

In: Operations Research Proceedings 2023

Author

Listed:
  • Felix Prause

    (Zuse Institute Berlin)

  • Ralf Borndörfer

    (Zuse Institute Berlin)

Abstract

We describe the development of a test library for the rolling stock rotation problem with predictive maintenance (RSRP-PdM). Our approach involves the utilization of genuine timetables from a private German railroad company. The generated instances incorporate probability distribution functions for modeling the health states of the vehicles and the considered trips possess varying degradation functions. RSRP-PdM involves assigning trips to a fleet of vehicles and scheduling their maintenance based on their individual health states. The goal is to minimize the total costs consisting of operational costs and the expected costs associated with vehicle failures. The failure probability is dependent on the health states of the vehicles, which are assumed to be random variables distributed by a family of probability distributions. Each distribution is represented by the parameters characterizing it and during the operation of the trips, these parameters get altered. Our approach incorporates non-linear degradation functions to describe the inference of the parameters but also linear ones could be applied. The resulting instances consist of the timetables of the individual lines that use the same vehicle type. Overall, we employ these assumptions and utilize open-source data to create a library of instances with varying difficulty. Our approach is vital for evaluating and comparing algorithms designed to solve RSRP-PdM.

Suggested Citation

  • Felix Prause & Ralf Borndörfer, 2025. "Construction of a Test Library for the Rolling Stock Rotation Problem with Predictive Maintenance," Lecture Notes in Operations Research, in: Guido Voigt & Malte Fliedner & Knut Haase & Wolfgang Brüggemann & Kai Hoberg & Joern Meissner (ed.), Operations Research Proceedings 2023, chapter 0, pages 281-286, Springer.
  • Handle: RePEc:spr:lnopch:978-3-031-58405-3_36
    DOI: 10.1007/978-3-031-58405-3_36
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