TY - CHAP A1 - Borndörfer, Ralf A1 - Löbel, Andreas A1 - Löbel, Fabian A1 - Weider, Steffen T1 - Solving the Electric Bus Scheduling Problem by an Integrated Flow and Set Partitioning Approach T2 - 24th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2024) N2 - Attractive and cost-efficient public transport requires solving computationally difficult optimization problems from network design to crew rostering. While great progress has been made in many areas, new requirements to handle increasingly complex constraints are constantly coming up. One such challenge is a new type of resource constraints that are used to deal with the state-of-charge of battery-electric vehicles, which have limited driving ranges and need to be recharged in-service. Resource constrained vehicle scheduling problems can classically be modelled in terms of either a resource constrained (multi-commodity) flow problem or in terms of a path-based set partition problem. We demonstrate how a novel integrated version of both formulations can be leveraged to solve resource constrained vehicle scheduling with replenishment in general and the electric bus scheduling problem in particular by Lagrangian relaxation and the proximal bundle method. Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0030-drops-211992 VL - 123 SP - 11:1 EP - 11:16 PB - Schloss Dagstuhl -- Leibniz-Zentrum für Informatik CY - Dagstuhl, Germany ER - TY - GEN A1 - Löbel, Fabian A1 - Borndörfer, Ralf A1 - Weider, Steffen T1 - Non-Linear Battery Behavior in Electric Vehicle Scheduling Problems N2 - The currently most popular approach to handle non-linear battery behavior for electric vehicle scheduling is to use a linear spline interpolation of the charge curve. We show that this can lead to approximate models that underestimate the charge duration and overestimate the state of charge, which is not desirable. While the error is of second order with respect to the interpolation step size, the associated mixed-integer linear programs do not scale well with the number of spline segments. It is therefore recommendable to use coarse interpolation grids adapted to the curvature of the charge curve, and to include sufficient safety margins to ensure solutions of approximate models remain feasible subjected to the exact charge curve. T3 - ZIB-Report - 23-24 KW - Electric Vehicle Scheduling KW - Non-Linear Charging Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-92441 SN - 1438-0064 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 - CHAP A1 - Löbel, Fabian A1 - Borndörfer, Ralf A1 - Weider, Steffen T1 - Non-Linear Charge Functions for Electric Vehicle Scheduling with Dynamic Recharge Rates T2 - 23rd Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2023) N2 - 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. Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0030-drops-187765 VL - 115 SP - 15:1 EP - 15:6 ER - TY - GEN A1 - Schlechte, Thomas A1 - Blome, Christian A1 - Gerber, Stefan A1 - Hauser, Stefan A1 - Kasten, Jens A1 - Müller, Gilbert A1 - Schulz, Christof A1 - Thüring, Michel A1 - Weider, Steffen T1 - The Bouquet of Features in Rolling Stock Rotation Planning T2 - Conference Proceedings RailBelgrade 2023 N2 - Rolling stock is one of the major assets for a railway transportation company. Hence, their utilization should be as efficiently and effectively as possible. Railway undertakings are facing rolling stock scheduling challenges in different forms - from rather idealized weekly strategic problems to very concrete operational ones. Thus, a vast of optimization models with different features and objectives exist. Thorlacius et al. (2015) provides a comprehensive and valuable collection on technical requirements, models, and methods considered in the scientific literature. We contribute with an update including recent works. The main focus of the paper is to present a classification and elaboration of the major features which our solver R-OPT is able to handle. Moreover, the basic optimization model and algorithmic ingredients of R-OPT are discussed. Finally, we present computational results for a cargo application at SBB CARGO AG and other railway undertakings for passenger traffic in Europe to show the capabilities of R-OPT. Y1 - 2023 UR - https://easychair.org/publications/preprint/Nms6 ER -