TY - GEN ED - Borndörfer, Ralf ED - Storandt, Sabine T1 - Proceedings of the 18th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems N2 - Running and optimizing transportation systems give rise to very complex and large-scale optimization problems requiring innovative solution techniques and ideas from mathematical optimization, theoretical computer science, and operations research. Since 2000, the series of Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS) workshops brings together researchers and practitioners who are interested in all aspects of algorithmic methods and models for transportation optimization and provides a forum for the exchange and dissemination of new ideas and techniques. The scope of ATMOS comprises all modes of transportation. The 18th ATMOS workshop (ATMOS’18) was held in connection with ALGO’18 and hosted by Aalto University in Helsinki, Finland, on August 23–24, 2018. Topics of interest were all optimization problems for passenger and freight transport, including, but not limited to, demand forecasting, models for user behavior, design of pricing systems, infrastructure planning, multi-modal transport optimization, mobile applications for transport, congestion modelling and reduction, line planning, timetable generation, routing and platform assignment, vehicle scheduling, route planning, crew and duty scheduling, rostering, delay management, routing in road networks, traffic guidance, and electro mobility. Of particular interest were papers applying and advancing techniques like graph and network algorithms, combinatorial optimization, mathematical programming, approximation algorithms, methods for the integration of planning stages, stochastic and robust optimization, online and real-time algorithms, algorithmic game theory, heuristics for real-world instances, and simulation tools. There were twenty-nine submissions from eighteen countries. All of them were reviewed by at least three referees in ninety-one reviews, among them five external ones, and judged on their originality, technical quality, and relevance to the topics of the workshop. Based on the reviews, the program committee selected sixteen submissions to be presented at the workshop (acceptance rate: 55%), which are collected in this volume in the order in which they were presented. Together, they quite impressively demonstrate the range of applicability of algorithmic optimization to transportation problems in a wide sense. In addition, Dennis Huisman kindly agreed to complement the program with an invited talk on Railway Disruption Management: State-of-the-art in practice and new research directions. Based on the reviews, Ralf Borndörfer, Marika Karbstein, Christian Liebchen, and Niels Lindner won the Best Paper Award of ATMOS’18 with their paper A simple way to compute the number of vehicles that Are required to operate a periodic timetable. In addition, we awarded Tomas Lidén the Best VGI Paper Award of ATMOS’18 for his paper Reformulations for railway traffic and maintenance planning. We would like to thank the members of the Steering Committee of ATMOS for giving us the opportunity to serve as Program Chairs of ATMOS’18, all the authors who submitted papers, Dennis Huisman for accepting our invitation to present an invited talk, the members of the Program Committee and the additional reviewers for their valuable work in selecting the papers appearing in this volume, our sponsors MODAL, TomTom, and VGIscience for their support of the prizes, and the local organizers for hosting the workshop as part of ALGO’18. We acknowledge the use of the EasyChair system for the great help in managing the submission and review processes, and Schloss Dagstuhl for publishing the proceedings of ATMOS’18 in its OASIcs series. Y1 - 2018 SN - ISBN 978-3-95977-096-5 U6 - https://doi.org/10.4230/OASIcs.ATMOS.2018.0 PB - Dagstuhl Publishing, Saarbrücken/Wadern, Germany ER - TY - THES A1 - Seidl, Stephan T1 - Ein Benders-Dekompositionsverfahren zur Lösung integrierter Dienst- und Dienstreihenfolgeprobleme Y1 - 2014 ER - TY - THES A1 - Richter, Stephanie T1 - Mathematische Behandlung von Dienstreihenfolgeregeln in der Wochenschemaoptimierung Y1 - 2013 ER - TY - GEN A1 - Borndörfer, Ralf A1 - Dittbrenner, Bastian A1 - Langenhan, Andreas A1 - Seidl, Stephan A1 - Weider, Steffen T1 - Integrierte Dienst- und Dienstreihenfolgeplanung zur Erhöhung der Fahrerzufriedenheit N2 - Wir stellen einen mathematischen Optimierungsansatz zur integrierten Dienst- und Dienstreihenfolgeplanung im öffentlichen Nahverkehr vor, mit dem sich bei konstanten Personalkosten die Fahrerzufriedenheit deutlich steigern lässt. T3 - ZIB-Report - 14-02 KW - duty scheduling KW - duty rostering KW - integrated scheduling KW - Benders' decomposition Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-50270 SN - 1438-0064 ER - TY - CHAP A1 - Borndörfer, Ralf A1 - Reuther, Markus A1 - Schlechte, Thomas A1 - Schulz, Christof A1 - Swarat, Elmar A1 - Weider, Steffen T1 - Duty Rostering in Public Transport - Facing Preferences, Fairness, and Fatigue T2 - Proceedings of Conference on Advanced Systems in Public Transport 2015 (CASPT2015) N2 - Duty rostering problems occur in different application contexts and come in different flavors. They give rise to very large scale integer programs which ypically have lots of solutions and extremely fractional LP relaxations. In such a situation, heuristics can be a viable algorithmic choice. We propose an mprovement method of the Lin-Kernighan type for the solution of duty rostering problems. We illustrate its versatility and solution quality on three different applications in public transit, vehicle routing, and airline rostering with a focus on the management of preferences, fairness, and fatigue, respectively. Y1 - 2015 ER - TY - GEN A1 - Borndörfer, Ralf A1 - Schulz, Christof A1 - Seidl, Stephan A1 - Weider, Steffen T1 - Integration of Duty Scheduling and Rostering to Increase Driver Satisfaction N2 - Integrated treatment of hitherto individual steps in the planning process of public transit companies discloses opportunities to reduce costs and to improve the quality of service. The arising integrated planning problems are complex and their solution requires the development of novel mathematical methods. This article proposes a mathematical optimization approach to integrate duty scheduling and rostering in public transit, which allows to significantly increase driver satisfaction at almost zero cost. This is important in order to to increase the attractiveness of the driver profession. The integration is based on coupling the subproblems by duty templates, which, compared to a coupling by duties, drastically reduces the problem complexity. T3 - ZIB-Report - 15-50 KW - Benders decomposition KW - driver satisfaction KW - duty templates KW - duty scheduling KW - rostering Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-56299 SN - 1438-0064 ER - TY - JOUR A1 - Breugem, Thomas A1 - Schlechte, Thomas A1 - Schulz, Christof A1 - Borndörfer, Ralf T1 - A three-phase heuristic for the Fairness-Oriented Crew Rostering Problem JF - Computers & Operations Research N2 - The Fairness-Oriented Crew Rostering Problem (FCRP) considers the joint optimization of attractiveness and fairness in cyclic crew rostering. Like many problems in scheduling and logistics, the combinatorial complexity of cyclic rostering causes exact methods to fail for large-scale practical instances. In case of the FCRP, this is accentuated by the additionally imposed fairness requirements. Hence, heuristic methods are necessary. We present a three-phase heuristic for the FCRP combining column generation techniques with variable-depth neighborhood search. The heuristic exploits different mathematical formulations to find feasible solutions and to search for improvements. We apply our methodology to practical instances from Netherlands Railways (NS), the main passenger railway operator in the Netherlands Our results show the three-phase heuristic finds good solutions for most instances and outperforms a state-of-the-art commercial solver. Y1 - 2023 U6 - https://doi.org/10.1016/j.cor.2023.106186 VL - 154 SP - 106186 ER -