TY - GEN A1 - Prause, Felix A1 - Borndörfer, Ralf T1 - Construction of a Test Library for the Rolling Stock Rotation Problem with Predictive Maintenance N2 - 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 the RSRP-PdM. T3 - ZIB-Report - 23-20 KW - Rolling Stock Rotation Planning KW - Predictive Maintenance KW - Test Library Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-91734 SN - 1438-0064 ER - TY - GEN A1 - Prause, Felix A1 - Borndörfer, Ralf A1 - Grimm, Boris A1 - Tesch, Alexander T1 - Approximating the RSRP with Predictive Maintenance N2 - We study the solution of the rolling stock rotation problem with predictive maintenance (RSRP-PM) by an iterative refinement approach that is based on a state-expanded event-graph. In this graph, the states are parameters of a failure distribution, and paths correspond to vehicle rotations with associated health state approximations. An optimal set of paths including maintenance can be computed by solving an integer linear program. Afterwards, the graph is refined and the procedure repeated. An associated linear program gives rise to a lower bound that can be used to determine the solution quality. Computational results for two instances derived from real world timetables of a German railway company are presented. The results show the effectiveness of the approach and the quality of the solutions. T3 - ZIB-Report - 23-04 KW - Rolling Stock Rotation Planning KW - Predictive Maintenance KW - Integer Linear Programming KW - Heuristic KW - Lower Bound Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-89531 SN - 1438-0064 ER -