@misc{OPUS4-7166, title = {Proceedings of the 18th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems}, editor = {Bornd{\"o}rfer, Ralf and Storandt, Sabine}, publisher = {Dagstuhl Publishing, Saarbr{\"u}cken/Wadern, Germany}, isbn = {ISBN 978-3-95977-096-5}, doi = {10.4230/OASIcs.ATMOS.2018.0}, year = {2018}, abstract = {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 Bornd{\"o}rfer, 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 Lid{\´e}n 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.}, language = {en} } @masterthesis{Seidl2014, type = {Bachelor Thesis}, author = {Seidl, Stephan}, title = {Ein Benders-Dekompositionsverfahren zur L{\"o}sung integrierter Dienst- und Dienstreihenfolgeprobleme}, year = {2014}, language = {de} } @masterthesis{Richter2013, type = {Bachelor Thesis}, author = {Richter, Stephanie}, title = {Mathematische Behandlung von Dienstreihenfolgeregeln in der Wochenschemaoptimierung}, year = {2013}, language = {de} } @misc{BorndoerferDittbrennerLangenhanetal.2014, author = {Bornd{\"o}rfer, Ralf and Dittbrenner, Bastian and Langenhan, Andreas and Seidl, Stephan and Weider, Steffen}, title = {Integrierte Dienst- und Dienstreihenfolgeplanung zur Erh{\"o}hung der Fahrerzufriedenheit}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-50270}, year = {2014}, abstract = {Wir stellen einen mathematischen Optimierungsansatz zur integrierten Dienst- und Dienstreihenfolgeplanung im {\"o}ffentlichen Nahverkehr vor, mit dem sich bei konstanten Personalkosten die Fahrerzufriedenheit deutlich steigern l{\"a}sst.}, language = {de} } @inproceedings{BorndoerferReutherSchlechteetal.2015, author = {Bornd{\"o}rfer, Ralf and Reuther, Markus and Schlechte, Thomas and Schulz, Christof and Swarat, Elmar and Weider, Steffen}, title = {Duty Rostering in Public Transport - Facing Preferences, Fairness, and Fatigue}, booktitle = {Proceedings of Conference on Advanced Systems in Public Transport 2015 (CASPT2015)}, year = {2015}, abstract = {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.}, language = {en} } @misc{BorndoerferSchulzSeidletal.2015, author = {Bornd{\"o}rfer, Ralf and Schulz, Christof and Seidl, Stephan and Weider, Steffen}, title = {Integration of Duty Scheduling and Rostering to Increase Driver Satisfaction}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-56299}, year = {2015}, abstract = {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.}, language = {en} } @article{BreugemSchlechteSchulzetal.2023, author = {Breugem, Thomas and Schlechte, Thomas and Schulz, Christof and Bornd{\"o}rfer, Ralf}, title = {A three-phase heuristic for the Fairness-Oriented Crew Rostering Problem}, volume = {154}, journal = {Computers \& Operations Research}, doi = {10.1016/j.cor.2023.106186}, pages = {106186}, year = {2023}, abstract = {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.}, language = {en} }