@inproceedings{Prause2024, author = {Prause, Felix}, title = {A Multi-Swap Heuristic for Rolling Stock Rotation Planning with Predictive Maintenance}, booktitle = {Proceedings of the 11th International Network Optimization Conference (INOC), Dublin, Ireland, March 11-23, 2024}, doi = {10.48786/inoc.2024.11}, pages = {58 -- 63}, year = {2024}, abstract = {We present a heuristic solution approach for the rolling stock rotation problem with predictive maintenance (RSRP-PdM). The task of this problem is to assign a sequence of trips to each of the vehicles and to schedule their maintenance such that all trips can be operated. Here, the health states of the vehicles are considered to be random variables distributed by a family of probability distribution functions, and the maintenance services should be scheduled based on the failure probability of the vehicles. The proposed algorithm first generates a solution by solving an integer linear program and then heuristically improves this solution by applying a local search procedure. For this purpose, the trips assigned to the vehicles are split up and recombined, whereby additional deadhead trips can be inserted between the partial assignments. Subsequently, the maintenance is scheduled by solving a shortest path problem in a state-expanded version of a space-time graph restricted to the trips of the individual vehicles. The solution approach is tested and evaluated on a set of test instances based on real-world timetables.}, language = {en} } @inproceedings{LoebelBorndoerferWeider2023, author = {L{\"o}bel, Fabian and Bornd{\"o}rfer, Ralf and Weider, Steffen}, title = {Non-Linear Charge Functions for Electric Vehicle Scheduling with Dynamic Recharge Rates}, volume = {115}, booktitle = {23rd Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2023)}, doi = {10.4230/OASIcs.ATMOS.2023.15}, url = {http://nbn-resolving.de/urn:nbn:de:0030-drops-187765}, pages = {15:1 -- 15:6}, year = {2023}, abstract = {The ongoing electrification of logistics systems and vehicle fleets increases the complexity of associated vehicle routing or scheduling problems. Battery-powered vehicles have to be scheduled to recharge in-service, and the relationship between charging time and replenished driving range is non-linear. In order to access the powerful toolkit offered by mixed-integer and linear programming techniques, this battery behavior has to be linearized. Moreover, as electric fleets grow, power draw peaks have to be avoided to save on electricity costs or to adhere to hard grid capacity limits, such that it becomes desirable to keep recharge rates dynamic. We suggest a novel linearization approach of battery charging behavior for vehicle scheduling problems, in which the recharge rates are optimization variables and not model parameters.}, language = {en} } @inproceedings{KlugReutherSchlechte2022, author = {Klug, Torsten and Reuther, Markus and Schlechte, Thomas}, title = {Does Laziness Pay Off? - A Lazy-Constraint Approach to Timetabling}, volume = {106}, booktitle = {22nd Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2022)}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, doi = {10.4230/OASIcs.ATMOS.2022.11}, pages = {11:1 -- 11:8}, year = {2022}, abstract = {Timetabling is a classical and complex task for public transport operators as well as for railway undertakings. The general question is: Which vehicle is taking which route through the transportation network in which order? In this paper, we consider the special setting to find optimal timetables for railway systems under a moving block regime. We directly set up on our work of [8 ], i.e., we consider the same model formulation and real-world instances of a moving block headway system. In this paper, we present a repair heuristic and a lazy-constraint approach utilizing the callback features of Gurobi, see [3]. We provide an experimental study of the different algorithmic approaches for a railway network with 100 and up to 300 train requests. The computational results show that the lazy-constraint approach together with the repair heuristic significantly improves our previous approaches.}, language = {en} } @inproceedings{EulerBorndoerferStrunketal.2022, author = {Euler, Ricardo and Bornd{\"o}rfer, Ralf and Strunk, Timo and Takkula, Tuomo}, title = {ULD Build-Up Scheduling with Dynamic Batching in an Air Freight Hub}, booktitle = {Operations Research Proceedings 2021}, doi = {10.1007/978-3-031-08623-6_38}, pages = {254 -- 260}, year = {2022}, abstract = {Air freight is usually shipped in standardized unit load devices (ULDs). The planning process for the consolidation of transit cargo from inbound flights or locally emerging shipments into ULDs for outbound flights is called build-up scheduling. More specifically, outbound ULDs must be assigned a time and a workstation subject to both workstation capacity constraints and the availability of shipments which in turn depends on break-down decisions for incoming ULDs. ULDs scheduled for the same outbound flight should be built up in temporal and spatial proximity. This serves both to minimize overhead in transportation times and to allow workers to move freight between ULDs. We propose to address this requirement by processing ULDs for the same outbound flight in batches. For the above build-up scheduling problem, we introduce a multi-commodity network design model. Outbound flights are modeled as commodities; transit cargo is represented by cargo flow volume and unpack and batch decisions are represented as design variables. The model is solved with a standard MIP solver on a set of benchmark data. For instances with a limited number of resource conflicts, near-optimal solutions are found in under two hours for a whole week of operations.}, language = {en} } @inproceedings{MasingLindnerBorndoerfer2022, author = {Masing, Berenike and Lindner, Niels and Bornd{\"o}rfer, Ralf}, title = {Optimal Line Plans in the Parametric City and the Impact of In-Motion Costs}, booktitle = {Operations Research Proceedings 2021}, editor = {Trautmann, Norbert and Dr{\"a}gi, Mario}, publisher = {Springer, Cham}, isbn = {978-3-031-08623-6}, doi = {10.1007/978-3-031-08623-6_44}, pages = {295 -- 301}, year = {2022}, abstract = {Line planning in public transport involves determining vehicle routes and assigning frequencies of service such that travel demands are satisfied. We evaluate how line plans, which are optimal with respect to in-motion costs (IMC), the objective function depending purely on arc-lengths for both user and operator costs, performs with respect to the value of resources consumed (VRC). The latter is an elaborate, socio-economic cost function which includes discomfort caused by delay, boarding and alighting times, and transfers. Even though discomfort is a large contributing factor to VRC and is entirely disregarded in IMC,  we observe that the two cost functions are qualitatively comparable.}, language = {en} } @inproceedings{BlancoBorndoerferMaristanydelasCasas2022, author = {Blanco, Marco and Bornd{\"o}rfer, Ralf and Maristany de las Casas, Pedro}, title = {An A* Algorithm for Flight Planning Based on Idealized Vertical Profiles}, volume = {106}, booktitle = {22nd Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2022)}, doi = {10.4230/OASIcs.ATMOS.2022.1}, pages = {1:1 -- 1:15}, year = {2022}, abstract = {The Flight Planning Problem is to find a minimum fuel trajectory between two airports in a 3D airway network under consideration of the wind. We show that this problem is NP-hard, even in its most basic version. We then present a novel A∗ heuristic, whose potential function is derived from an idealized vertical profile over the remaining flight distance. This potential is, under rather general assumptions, both admissible and consistent and it can be computed efficiently. The method outperforms the state-of-the-art heuristic on real-life instances.}, language = {en} } @inproceedings{GrimmBorndoerferBushe2023, author = {Grimm, Boris and Bornd{\"o}rfer, Ralf and Bushe, Julian}, title = {Assignment Based Resource Constrained Path Generation for Railway Rolling Stock Optimization}, volume = {115}, booktitle = {23rd Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2023)}, publisher = {Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik}, address = {Dagstuhl, Germany}, doi = {https://doi.org/10.4230/OASIcs.ATMOS.2023.13}, pages = {13:1 -- 13:15}, year = {2023}, abstract = {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 Bornd{\"o}rfer et al., 2016] on a test set of real world instances.}, language = {en} } @inproceedings{BorndoerferGrimmSchade2023, author = {Bornd{\"o}rfer, Ralf and Grimm, Boris and Schade, Stanley}, title = {A Robustness Analysis of Long Distance Train Crew Schedules in Germany}, volume = {CCC 1}, booktitle = {Proceedings Of The Fifth Iinternational Conference On Railway Technology: Research, Development and Maintenance}, issn = {2753-3239}, doi = {10.4203/ccc.1.23.17}, year = {2023}, abstract = {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.}, language = {en} } @inproceedings{BortolettoLindnerMasing2022, author = {Bortoletto, Enrico and Lindner, Niels and Masing, Berenike}, title = {Tropical Neighbourhood Search: A New Heuristic for Periodic Timetabling}, volume = {106}, booktitle = {22nd Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2022)}, doi = {10.4230/OASIcs.ATMOS.2022.3}, pages = {3:1 -- 3:19}, year = {2022}, abstract = {Periodic timetabling is a central aspect of both the long-term organization and the day-to-day operations of a public transportation system. The Periodic Event Scheduling Problem (PESP), the combinatorial optimization problem that forms the mathematical basis of periodic timetabling, is an extremely hard problem, for which optimal solutions are hardly ever found in practice. The most prominent solving strategies today are based on mixed-integer programming, and there is a concurrent PESP solver employing a wide range of heuristics [Bornd{\"o}rfer et al., 2020]. We present tropical neighborhood search (tns), a novel PESP heuristic. The method is based on the relations between periodic timetabling and tropical geometry [Bortoletto et al., 2022]. We implement tns into the concurrent solver, and test it on instances of the benchmarking library PESPlib. The inclusion of tns turns out to be quite beneficial to the solver: tns is able to escape local optima for the modulo network simplex algorithm, and the overall share of improvement coming from tns is substantial compared to the other methods available in the solver. Finally, we provide better primal bounds for five PESPlib instances.}, language = {en} } @inproceedings{BortolettoLindnerMasing2023, author = {Bortoletto, Enrico and Lindner, Niels and Masing, Berenike}, title = {Periodic Timetabling with Cyclic Order Constraints}, volume = {115}, booktitle = {23rd Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2023)}, doi = {10.4230/OASIcs.ATMOS.2023.7}, pages = {7:1 -- 7:18}, year = {2023}, abstract = {Periodic timetabling for highly utilized railway networks is a demanding challenge. We formulate an infrastructure-aware extension of the Periodic Event Scheduling Problem (PESP) by requiring that not only events, but also activities using the same infrastructure must be separated by a minimum headway time. This extended problem can be modeled as a mixed-integer program by adding constraints on the sum of periodic tensions along certain cycles, so that it shares some structural properties with standard PESP. We further refine this problem by fixing cyclic orders at each infrastructure element. Although the computational complexity remains unchanged, the mixed-integer programming model then becomes much smaller. Furthermore, we also discuss how to find a minimal subset of infrastructure elements whose cyclic order already prescribes the order for the remaining parts of the network, and how cyclic order information can be modeled in a mixed-integer programming context. In practice, we evaluate the impact of cyclic orders on a real-world instance on the S-Bahn Berlin network, which turns out to be computationally fruitful.}, language = {en} }