@article{GilgKlugMartienssenetal., author = {Gilg, Brady and Klug, Torsten and Martienssen, Rosemarie and Paat, Joseph and Schlechte, Thomas and Schulz, Christof and Seymen, Senan and Tesch, Alexander}, title = {Conflict-free railway track assignment at depots}, series = {Journal of Rail Transport Planning \& Management}, journal = {Journal of Rail Transport Planning \& Management}, doi = {10.1016/j.jrtpm.2017.12.004}, abstract = {Managing rolling stock with no passengers aboard is a critical component of railway operations. One aspect of managing rolling stock is to park the rolling stock on a given set of tracks at the end of a day or service. Depending on the parking assignment, shunting may be required in order for a parked train to depart or for an incoming train to park. Given a collection of tracks M and a collection of trains T with a fixed arrival-departure timetable, the train assignment problem (TAP) is to determine the maximum number of trains from T that can be parked on M according to the timetable and without the use of shunting. Hence, efficiently solving the TAP allows to quickly compute feasible parking schedules that do not require further shunting adjustments. In this paper, we show that the TAP is NP-hard and present two integer programming models for solving the TAP. We compare both models on a theoretical level. Moreover, to our knowledge, we consider the first approach that integrates track lengths along with the three most common types of parking tracks FIFO, LIFO and FREE tracks in a common model. Furthermore, to optimize against uncertainty in the arrival times of the trains we extend our models by stochastic and robust modeling techniques. We conclude by giving computational results for both models, observing that they perform well on real timetables.}, language = {en} } @article{Tesch, author = {Tesch, Alexander}, title = {Kompakte MIP Modelle f{\"u}r das Ressourcenbeschr{\"a}nkte Projektplanungsproblem}, series = {OR News}, volume = {58}, journal = {OR News}, pages = {19 -- 21}, language = {de} } @article{Tesch, author = {Tesch, Alexander}, title = {A Polyhedral Study of Event-Based Models for the Resource-Constrained Project Scheduling Problem}, series = {Journal of Scheduling}, journal = {Journal of Scheduling}, abstract = {We consider event-based Mixed-Integer Programming (MIP) models for the Resource-Constrained Project Scheduling Problem (RCPSP) that represent an alternative to the common time-indexed model (DDT) of Pritsker et al. (1969) for the case where the underlying time horizon is large or job processing times are subject to huge variations. In contrast to the time-indexed model, the size of event-based models does not depend on the time horizon. For two event-based formulations OOE and SEE of Kon{\´e} et al. (2011) we present new valid inequalities that dominate the original formulation. Additionally, we introduce a new event-based model: the Interval Event-Based Model (IEE). We deduce linear transformations between all three models that yield the strict domination order IEE > SEE > OOE for their linear programming (LP) relaxations, meaning that IEE has the strongest linear relaxation among the event-based models. We further show that the popular DDT formulation can be retrieved from IEE by certain polyhedral operations, thus giving a unifying view on a complete branch of MIP formulations for the RCPSP. In addition, we analyze the computational performance of all presented models on test instances of the PSPLIB (Kolisch and Sprecher 1997).}, language = {en} } @article{PrauseBorndoerferGrimmetal., author = {Prause, Felix and Bornd{\"o}rfer, Ralf and Grimm, Boris and Tesch, Alexander}, title = {Approximating rolling stock rotations with integrated predictive maintenance}, series = {Journal of Rail Transport Planning \& Management}, volume = {30}, journal = {Journal of Rail Transport Planning \& Management}, doi = {https://doi.org/10.1016/j.jrtpm.2024.100434}, pages = {100434}, abstract = {We study the solution of the rolling stock rotation problem with predictive maintenance (RSRP-PdM) 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 six 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.}, language = {en} }