TY - JOUR A1 - Grimm, Boris A1 - Hoogervorst, Rowan A1 - Borndörfer, Ralf T1 - A Comparison of Two Models for Rolling Stock Scheduling JF - Transportation Science N2 - A major step in the planning process of passenger railway operators is the assignment of rolling stock, that is, train units, to the trips of the timetable. A wide variety of mathematical optimization models have been proposed to support this task, which we discuss and argue to be justified in order to deal with operational differences between railway operators, and hence different planning requirements, in the best possible way. Our investigation focuses on two commonly used models, the composition model and the hypergraph model, that were developed for Netherlands Railways (NS) and DB Fernverkehr AG (DB), respectively. We compare these models in two distinct problem settings, an NS setting and DB-light setting and consider different model variants to tune the models to these settings. We prove that in both of these settings, the linear programming bounds of the two models are equally strong as long as a number of reasonable assumptions are met. However, through a numerical evaluation on NS and DB-light instances, we show that the numerical performance of the models strongly depends on the instances. Although the composition model is the most compact and fastest model for the NS instances, an adjusted version of this model grows quickly for the DB-light instances and is then outperformed by the considered hypergraph model variants. Moreover, we show that a depot-extended version of the hypergraph model is able to combine strengths of both models and show good performance on both the NS and DB-light instances. Y1 - 2025 U6 - https://doi.org/10.1287/trsc.2024.0505 VL - 59 IS - 5 ER - TY - THES A1 - Bushe, Julian T1 - Rolling Stock Rotation Optimization with Maintenance Paths N2 - Die Planung vom Zugumläufen ist eine der wichtigsten Aufgaben für Eisenbahnun- ternehmen. Dabei spielt auch die Einhaltung von vorgegebenen Wartungsintervallen eine zentrale Rolle für die Sicherheit und Zuverlässigkeit der Schienenfahrzeuge. Wir zeigen, wie man dieses Umlaufplanungsproblem unter Beachtung von Wartungsbe- dingungen mathematisch formuliert, modelliert und löst — sowohl in der Theorie als auch im Anwendungsfall mit Szenarien der DB Fernverkehr AG, einer Konzern- tochter der Deutschen Bahn für den Schienenpersonenfernverkehr. Markus Reuther hat sich in seiner Dissertation [11] mit diesem Problem beschäftigt und es mit Hilfe eines passenden Hypergraphen als gemischt-ganzzahliges Programm modelliert. Neben der Modellierung präsentiert Reuther in seiner Arbeit neuartige algorithmische Ideen, darunter den sogenannten Coarse-to-Fine -Ansatz, bei dem zunächst Teile des Problems auf einer weniger detaillierten ( coarse ) Ebene gelöst werden und diese Lösung dann verwendet wird, um auf effiziente Art und Weise eine Lösung für das ursprüngliche Problem zu finden. Zur Wartungsplanung nutzt Reuther einen Fluss im Hypergraphen, der den Ressourcenverbrauch der Fahrzeuge modelliert. In der linearen Relaxierung des Modells führt dies dazu, dass die Zahl der notwendigen Wartungen systematisch unterschätzt wird. Dadurch bleibt in vielen Fällen eine große Lücke zwischen dem Zielfunktionswert einer optimalen Lösung des ganzzahligen Problems und der untere Schranke, die uns die lineare Relaxierung liefert. Wir nehmen uns in dieser Arbeit dieses Problems an. Wir entwickeln ein auf Pfaden basierendes ganzzahliges Modell für das Umlaufplanungsproblem und zeigen, dass die untere Schranke mindestens so scharf oder schärfer ist als die untere Schranke, die das Modell von Reuther liefert. Um das Modell zu lösen, entwickeln wir einen Algorithmus, der Spaltengenerierung mit dem Coarse-to-Fine-Ansatz von Reuther verbindet. Weiterhin entwickeln wir eine Spaltenauswahlregel zur Beschleunigung des Algorithmus. Das Modell und alle in der Arbeit vorgestellten Algorithmen wur- den im Rahmen der Arbeit implementiert und mit Anwendungsszenarien der DB Fernverkehr AG getestet. Unsere Tests zeigen, dass unser Modell für fast alle Szena- rien deutlich schärfere untere Schranken liefert als das Modell von Reuther. In den getesteten Instanzen konnten wir durch die Verbesserung der unteren Schranke bis zu 99% der Optimalitätslücke schließen. In einem Drittel der Fälle konnten wir durch unseren Ansatz auch für das ganzzahlige Programm verbesserte Zielfunktionswerte erreichen Y1 - 2021 ER - TY - JOUR A1 - Borndörfer, Ralf A1 - Eßer, Thomas A1 - Frankenberger, Patrick A1 - Huck, Andreas A1 - Jobmann, Christoph A1 - Krostitz, Boris A1 - Kuchenbecker, Karsten A1 - Moorhagen, Kai A1 - Nagl, Philipp A1 - Peterson, Michael A1 - Reuther, Markus A1 - Schang, Thilo A1 - Schoch, Michael A1 - Schülldorf, Hanno A1 - Schütz, Peter A1 - Therolf, Tobias A1 - Waas, Kerstin A1 - Weider, Steffen T1 - Deutsche Bahn Schedules Train Rotations Using Hypergraph Optimization JF - Informs Journal on Applied Analytics N2 - Deutsche Bahn (DB) operates a large fleet of rolling stock (locomotives, wagons, and train sets) that must be combined into trains to perform rolling stock rotations. This train composition is a special characteristic of railway operations that distinguishes rolling stock rotation planning from the vehicle scheduling problems prevalent in other industries. DB models train compositions using hyperarcs. The resulting hypergraph models are ad-dressed using a novel coarse-to-fine method that implements a hierarchical column genera-tion over three levels of detail. This algorithm is the mathematical core of DB’s fleet em-ployment optimization (FEO) system for rolling stock rotation planning. FEO’s impact within DB’s planning departments has been revolutionary. DB has used it to support the company’s procurements of its newest high-speed passenger train fleet and its intermodal cargo locomotive fleet for cross-border operations. FEO is the key to successful tendering in regional transport and to construction site management in daily operations. DB’s plan-ning departments appreciate FEO’s high-quality results, ability to reoptimize (quickly), and ease of use. Both employees and customers benefit from the increased regularity of operations. DB attributes annual savings of 74 million euro, an annual reduction of 34,000 tons of CO2 emissions, and the elimination of 600 coupling operations in cross-border operations to the implementation of FEO. Y1 - 2021 U6 - https://doi.org/10.1287/inte.2020.1069 VL - 51 IS - 1 SP - 42 EP - 62 ER - TY - JOUR A1 - Sahin, Guvenc A1 - Ahmadi, Amin A1 - Borndörfer, Ralf A1 - Schlechte, Thomas T1 - Multi-period line planning with resource transfers JF - Transportation Research Part C: Emerging Technologies N2 - Urban transportation systems are subject to a high level of variation and fluctuation in demand over the day. When this variation and fluctuation are observed in both time and space, it is crucial to develop line plans that are responsive to demand. A multi-period line planning approach that considers a changing demand during the planning horizon is proposed. If such systems are also subject to limitations of resources, a dynamic transfer of resources from one line to another throughout the planning horizon should also be considered. A mathematical modelling framework is developed to solve the line planning problem with a cost-oriented approach considering transfer of resources during a finite length planning horizon of multiple periods. We use real-life public transportation network data for our computational results. We analyze whether or not multi-period solutions outperform single period solutions in terms of feasibility and relevant costs. The importance of demand variation on multi-period solutions is investigated. We evaluate the impact of resource transfer constraints on the effectiveness of solutions. We also study the effect of period lengths along with the problem parameters that are significant for and sensitive to the optimality of solutions. Y1 - 2020 U6 - https://doi.org/10.1016/j.trc.2020.102726 VL - 119 SP - 102726 ER - TY - THES A1 - Löbel, Fabian T1 - Implementing the Network Simplex for Hypergraphs N2 - The well-known network simplex algorithm is a powerful tool to solve flow problems on graphs. Based on a recent dissertation by Isabel Beckenbach, we develop the necessary theory to extend the network simplex to capacitated flow problems on hypergraphs and implement this new variant. We then attempt to solve instances arising from real-life vehicle rotation planning problems. Y1 - 2020 ER - TY - JOUR A1 - Beckenbach, Isabel T1 - Von Graphen zu Hypergraphen JF - OR News Y1 - 2020 SN - 1437-2045 IS - 70 ER - TY - CHAP A1 - Grimm, Boris A1 - Borndörfer, Ralf A1 - Bushe, Julian T1 - Assignment Based Resource Constrained Path Generation for Railway Rolling Stock Optimization T2 - 23rd Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2023) N2 - The fundamental task of every passenger railway operator is to offer an attractive railway timetable to the passengers while operating it as cost efficiently as possible. The available rolling stock has to be assigned to trips so that all trips are operated, operational requirements are satisfied, and the operating costs are minimum. This so-called Rolling Stock Rotation Problem (RSRP) is well studied in the literature. In this paper we consider an acyclic version of the RSRP that includes vehicle maintenance. As the latter is an important aspect, maintenance services have to be planned simultaneously to ensure the rotation’s feasibility in practice. Indeed, regular maintenance is important for the safety and reliability of the rolling stock as well as enforced by law in many countries. We present a new integer programming formulation that links a hyperflow to model vehicle compositions and their coupling decisions to a set of path variables that take care of the resource consumption of the individual vehicles. To solve the model we developed different column generation algorithms which are compared to each other as well as to the MILP flow formulation of [Ralf Borndörfer et al., 2016] on a test set of real world instances. Y1 - 2023 U6 - https://doi.org/https://doi.org/10.4230/OASIcs.ATMOS.2023.13 VL - 115 SP - 13:1 EP - 13:15 PB - Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik CY - Dagstuhl, Germany ER - TY - CHAP A1 - Borndörfer, Ralf A1 - Grimm, Boris A1 - Schade, Stanley T1 - A Robustness Analysis of Long Distance Train Crew Schedules in Germany T2 - Proceedings Of The Fifth Iinternational Conference On Railway Technology: Research, Development and Maintenance N2 - Nowadays railway networks are highly complex and often very fragile systems. A wide variety of individual operations that influence each other have to go hand in hand to end up with a smoothly and efficiently running system. Many of these operations suffer from uncertainty as trains could be delayed, the signaling system be disrupted or scheduled crews could be ill. Usually these opartions could be organized hierarchically from long term strategical decisions to real time decision management. Each stage in the hierarchy defines a different mathematical optimization problem, which is solved sequentially. At every stage the knowledge about preceding or succeeding planning stages may vary and also the interaction between two stages in this chain of problems may vary from almost no interaction to highly dependent situations. This paper deals with a topic that is an example for the latter case, namely the interaction between vehicle schedules, vehicle punctuality, and crew schedules. To reduce the number of potential rescheduling actions we developed a software tool in cooperation with our practical partner DB Fernverkehr AG (DBF) to predict a certain set of critical crew schedules. This tool evaluates, predicts, and determines "bottlenecks" in the crew schedule in the sense of potentially required rescheduling actions due to likely delays. The approach was tested on real life crew and train timetable data of DBF and can be regarded as the computation of key performance indicators, which is often desired. For our experiments we had access to the operated timetable and crew schedule of DBF for periods of two and six weeks in 2019. Y1 - 2023 U6 - https://doi.org/10.4203/ccc.1.23.17 SN - 2753-3239 VL - CCC 1 ER -