TY - CHAP A1 - Enke, Harry A1 - Fiedler, Norman A1 - Fischer, Thomas A1 - Gnadt, Timo A1 - Ketzan, Erik A1 - Ludwig, Jens A1 - Rathmann, Torsten A1 - Stöckle, Gabriel A1 - Schintke, Florian ED - Enke, Harry ED - Ludwig, Jens T1 - Leitfaden zum Forschungsdaten-Management T2 - Leitfaden zum Forschungsdaten-Management Y1 - 2013 PB - Verlag Werner Hülsbusch, Glückstadt ER - TY - BOOK A1 - Abbink, Erwin A1 - Bärmann, Andreas A1 - Bešinovic, Nikola A1 - Bohlin, Markus A1 - Cacchiani, Valentina A1 - Caimi, Gabrio A1 - de Fabris, Stefano A1 - Dollevoet, Twan A1 - Fischer, Frank A1 - Fügenschuh, Armin A1 - Galli, Laura A1 - Goverde, Rob M.P. A1 - Hansmann, Ronny A1 - Homfeld, Henning A1 - Huisman, Dennis A1 - Johann, Marc A1 - Klug, Torsten A1 - Törnquist Krasemann, Johanna A1 - Kroon, Leo A1 - Lamorgese, Leonardo A1 - Liers, Frauke A1 - Mannino, Carlo A1 - Medeossi, Giorgio A1 - Pacciarelli, Dario A1 - Reuther, Markus A1 - Schlechte, Thomas A1 - Schmidt, Marie A1 - Schöbel, Anita A1 - Schülldorf, Hanno A1 - Stieber, Anke A1 - Stiller, Sebastian A1 - Toth, Paolo A1 - Zimmermann, Uwe ED - Borndörfer, Ralf ED - Klug, Torsten ED - Lamorgese, Leonardo ED - Mannino, Carlo ED - Reuther, Markus ED - Schlechte, Thomas T1 - Handbook of Optimization in the Railway Industry N2 - This book promotes the use of mathematical optimization and operations research methods in rail transportation. The editors assembled thirteen contributions from leading scholars to present a unified voice, standardize terminology, and assess the state-of-the-art. There are three main clusters of articles, corresponding to the classical stages of the planning process: strategic, tactical, and operational. These three clusters are further subdivided into five parts which correspond to the main phases of the railway network planning process: network assessment, capacity planning, timetabling, resource planning, and operational planning. Individual chapters cover: Simulation Capacity Assessment Network Design Train Routing Robust Timetabling Event Scheduling Track Allocation Blocking Shunting Rolling Stock Crew Scheduling Dispatching Delay Propagation Y1 - 2018 SN - 978-3-319-72152-1 U6 - https://doi.org/10.1007/978-3-319-72153-8 VL - 268 PB - Springer Verlag ER - TY - JOUR A1 - Heinze, Rieke A1 - Dipankar, Anurag A1 - Henken, Cintia Carbajal A1 - Moseley, Christopher A1 - Sourdeval, Odran A1 - Trömel, Silke A1 - Xie, Xinxin A1 - Adamidis, Panos A1 - Ament, Felix A1 - Baars, Holger A1 - Barthlott, Christian A1 - Behrendt, Andreas A1 - Blahak, Ulrich A1 - Bley, Sebastian A1 - Brdar, Slavko A1 - Brueck, Matthias A1 - Crewell, Susanne A1 - Deneke, Hartwig A1 - Di Girolamo, Paolo A1 - Evaristo, Raquel A1 - Fischer, Jürgen A1 - Frank, Christopher A1 - Friederichs, Petra A1 - Göcke, Tobias A1 - Gorges, Ksenia A1 - Hande, Luke A1 - Hanke, Moritz A1 - Hansen, Akio A1 - Hege, Hans-Christian A1 - Hose, Corinna A1 - Jahns, Thomas A1 - Kalthoff, Norbert A1 - Klocke, Daniel A1 - Kneifel, Stefan A1 - Knippertz, Peter A1 - Kuhn, Alexander A1 - van Laar, Thriza A1 - Macke, Andreas A1 - Maurer, Vera A1 - Mayer, Bernhard A1 - Meyer, Catrin I. A1 - Muppa, Shravan K. A1 - Neggers, Roeland A. J. A1 - Orlandi, Emiliano A1 - Pantillon, Florian A1 - Pospichal, Bernhard A1 - Röber, Niklas A1 - Scheck, Leonhard A1 - Seifert, Axel A1 - Seifert, Patric A1 - Senf, Fabian A1 - Siligam, Pavan A1 - Simmer, Clemens A1 - Steinke, Sandra A1 - Stevens, Bjorn A1 - Wapler, Kathrin A1 - Weniger, Michael A1 - Wulfmeyer, Volker A1 - Zängl, Günther A1 - Zhang, Dan A1 - Quaas, Johannes T1 - Large-eddy simulations over Germany using ICON: a comprehensive evaluation JF - Quarterly Journal of the Royal Meteorological Society N2 - Large-eddy simulations (LES) with the new ICOsahedral Non-hydrostatic atmosphere model (ICON) covering Germany are evaluated for four days in spring 2013 using observational data from various sources. Reference simulations with the established Consortium for Small-scale Modelling (COSMO) numerical weather prediction model and further standard LES codes are performed and used as a reference. This comprehensive evaluation approach covers multiple parameters and scales, focusing on boundary-layer variables, clouds and precipitation. The evaluation points to the need to work on parametrizations influencing the surface energy balance, and possibly on ice cloud microphysics. The central purpose for the development and application of ICON in the LES configuration is the use of simulation results to improve the understanding of moist processes, as well as their parametrization in climate models. The evaluation thus aims at building confidence in the model's ability to simulate small- to mesoscale variability in turbulence, clouds and precipitation. The results are encouraging: the high-resolution model matches the observed variability much better at small- to mesoscales than the coarser resolved reference model. In its highest grid resolution, the simulated turbulence profiles are realistic and column water vapour matches the observed temporal variability at short time-scales. Despite being somewhat too large and too frequent, small cumulus clouds are well represented in comparison with satellite data, as is the shape of the cloud size spectrum. Variability of cloud water matches the satellite observations much better in ICON than in the reference model. In this sense, it is concluded that the model is fit for the purpose of using its output for parametrization development, despite the potential to improve further some important aspects of processes that are also parametrized in the high-resolution model. Y1 - 2017 U6 - https://doi.org/10.1002/qj.2947 VL - 143 IS - 702 SP - 69 EP - 100 ER - TY - JOUR A1 - Schimunek, Johannes A1 - Seidl, Philipp A1 - Elez, Katarina A1 - Hempel, Tim A1 - Le, Tuan A1 - Noé, Frank A1 - Olsson, Simon A1 - Raich, Lluís A1 - Winter, Robin A1 - Gokcan, Hatice A1 - Gusev, Filipp A1 - Gutkin, Evgeny M. A1 - Isayev, Olexandr A1 - Kurnikova, Maria G. A1 - Narangoda, Chamali H. A1 - Zubatyuk, Roman A1 - Bosko, Ivan P. A1 - Furs, Konstantin V. A1 - Karpenko, Anna D. A1 - Kornoushenko, Yury V. A1 - Shuldau, Mikita A1 - Yushkevich, Artsemi A1 - Benabderrahmane, Mohammed B. A1 - Bousquet-Melou, Patrick A1 - Bureau, Ronan A1 - Charton, Beatrice A1 - Cirou, Bertrand C. A1 - Gil, Gérard A1 - Allen, William J. A1 - Sirimulla, Suman A1 - Watowich, Stanley A1 - Antonopoulos, Nick A1 - Epitropakis, Nikolaos A1 - Krasoulis, Agamemnon A1 - Itsikalis, Vassilis A1 - Theodorakis, Stavros A1 - Kozlovskii, Igor A1 - Maliutin, Anton A1 - Medvedev, Alexander A1 - Popov, Petr A1 - Zaretckii, Mark A1 - Eghbal-Zadeh, Hamid A1 - Halmich, Christina A1 - Hochreiter, Sepp A1 - Mayr, Andreas A1 - Ruch, Peter A1 - Widrich, Michael A1 - Berenger, Francois A1 - Kumar, Ashutosh A1 - Yamanishi, Yoshihiro A1 - Zhang, Kam Y. J. A1 - Bengio, Emmanuel A1 - Bengio, Yoshua A1 - Jain, Moksh J. A1 - Korablyov, Maksym A1 - Liu, Cheng-Hao A1 - Marcou, Gilles A1 - Glaab, Enrico A1 - Barnsley, Kelly A1 - Iyengar, Suhasini M. A1 - Ondrechen, Mary Jo A1 - Haupt, V. Joachim A1 - Kaiser, Florian A1 - Schroeder, Michael A1 - Pugliese, Luisa A1 - Albani, Simone A1 - Athanasiou, Christina A1 - Beccari, Andrea A1 - Carloni, Paolo A1 - D’Arrigo, Giulia A1 - Gianquinto, Eleonora A1 - Goßen, Jonas A1 - Hanke, Anton A1 - Joseph, Benjamin P. A1 - Kokh, Daria B. A1 - Kovachka, Sandra A1 - Manelfi, Candida A1 - Mukherjee, Goutam A1 - Muñiz-Chicharro, Abraham A1 - Musiani, Francesco A1 - Nunes-Alves, Ariane A1 - Paiardi, Giulia A1 - Rossetti, Giulia A1 - Sadiq, S. Kashif A1 - Spyrakis, Francesca A1 - Talarico, Carmine A1 - Tsengenes, Alexandros A1 - Wade, Rebecca C. A1 - Copeland, Conner A1 - Gaiser, Jeremiah A1 - Olson, Daniel R. A1 - Roy, Amitava A1 - Venkatraman, Vishwesh A1 - Wheeler, Travis J. A1 - Arthanari, Haribabu A1 - Blaschitz, Klara A1 - Cespugli, Marco A1 - Durmaz, Vedat A1 - Fackeldey, Konstantin A1 - Fischer, Patrick D. A1 - Gorgulla, Christoph A1 - Gruber, Christian A1 - Gruber, Karl A1 - Hetmann, Michael A1 - Kinney, Jamie E. A1 - Padmanabha Das, Krishna M. A1 - Pandita, Shreya A1 - Singh, Amit A1 - Steinkellner, Georg A1 - Tesseyre, Guilhem A1 - Wagner, Gerhard A1 - Wang, Zi-Fu A1 - Yust, Ryan J. A1 - Druzhilovskiy, Dmitry S. A1 - Filimonov, Dmitry A. A1 - Pogodin, Pavel V. A1 - Poroikov, Vladimir A1 - Rudik, Anastassia V. A1 - Stolbov, Leonid A. A1 - Veselovsky, Alexander V. A1 - De Rosa, Maria A1 - De Simone, Giada A1 - Gulotta, Maria R. A1 - Lombino, Jessica A1 - Mekni, Nedra A1 - Perricone, Ugo A1 - Casini, Arturo A1 - Embree, Amanda A1 - Gordon, D. Benjamin A1 - Lei, David A1 - Pratt, Katelin A1 - Voigt, Christopher A. A1 - Chen, Kuang-Yu A1 - Jacob, Yves A1 - Krischuns, Tim A1 - Lafaye, Pierre A1 - Zettor, Agnès A1 - Rodríguez, M. Luis A1 - White, Kris M. A1 - Fearon, Daren A1 - Von Delft, Frank A1 - Walsh, Martin A. A1 - Horvath, Dragos A1 - Brooks III, Charles L. A1 - Falsafi, Babak A1 - Ford, Bryan A1 - García-Sastre, Adolfo A1 - Yup Lee, Sang A1 - Naffakh, Nadia A1 - Varnek, Alexandre A1 - Klambauer, Günter A1 - Hermans, Thomas M. T1 - A community effort in SARS-CoV-2 drug discovery JF - Molecular Informatics KW - COVID-19 KW - drug discovery KW - machine learning KW - SARS-CoV-2 Y1 - 2023 U6 - https://doi.org/https://doi.org/10.1002/minf.202300262 VL - 43 IS - 1 SP - e202300262 ER - TY - JOUR A1 - Fischer, Kristina A1 - Gerber, Anja A1 - Koprucki, Thomas A1 - Noback, Andres A1 - Reidelbach, Marco A1 - Schrade, Torsten A1 - Thiery, Florian T1 - Windows on Data: Federating Research Data with FAIR Digital Objects and Linked Open Data JF - 2nd Conference on Research Data Infrastructure (CoRDI) Y1 - 2025 U6 - https://doi.org/10.5281/zenodo.16736222 ER - TY - CHAP A1 - Fischer, Frank A1 - Schlechte, Thomas ED - D'Angelo, Gianlorenzo ED - Dollevoet, Twan T1 - Strong Relaxations for the Train Timetabling Problem using Connected Configurations T2 - 17th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2017) N2 - The task of the train timetabling problem or track allocation problem is to find conflict free schedules for a set of trains with predefined routes in a railway network. Especially for non-periodic instances models based on time expanded networks are often used. Unfortunately, the linear programming relaxation of these models is often extremely weak because these models do not describe combinatorial relations like overtaking possibilities very well. In this paper we extend the model by so called connected configuration subproblems. These subproblems perfectly describe feasible schedules of a small subset of trains (2-3) on consecutive track segments. In a Lagrangian relaxation approach we solve several of these subproblems together in order to produce solutions which consist of combinatorially compatible schedules along the track segments. The computational results on a mostly single track corridor taken from the INFORMS RAS Problem Solving Competition 2012 data indicate that our new solution approach is rather strong. Indeed, for this instance the solution of the Lagrangian relaxation is already integral. Y1 - 2017 SN - 978-3-95977-042-2 U6 - https://doi.org/10.4230/OASIcs.ATMOS.2017.11 VL - 59 ER - TY - CHAP A1 - Fischer, Frank A1 - Grimm, Boris A1 - Klug, Torsten A1 - Schlechte, Thomas T1 - A Re-optimization Approach for Train Dispatching T2 - Operations Research Proceedings 2016 N2 - The Train Dispatching Problem (TDP) is to schedule trains through a network in a cost optimal way. Due to disturbances during operation existing track allocations often have to be re-scheduled and integrated into the timetable. This has to be done in seconds and with minimal timetable changes to guarantee smooth and conflict free operation. We present an integrated modeling approach for the re-optimization task using Mixed Integer Programming. Finally, we provide computational results for scenarios provided by the INFORMS RAS Problem Soling Competition 2012. Y1 - 2017 U6 - https://doi.org/10.1007/978-3-319-55702-1_85 SP - 645 EP - 651 ER - TY - GEN A1 - Fischer, Frank A1 - Schlechte, Thomas T1 - Strong Relaxations for the Train Timetabling Problem using Connected Configurations N2 - The task of the train timetabling problem or track allocation problem is to find conflict free schedules for a set of trains with predefined routes in a railway network. Especially for non-periodic instances models based on time expanded networks are often used. Unfortunately, the linear programming relaxation of these models is often extremely weak because these models do not describe combinatorial relations like overtaking possibilities very well. In this paper we extend the model by so called connected configuration subproblems. These subproblems perfectly describe feasible schedules of a small subset of trains (2-3) on consecutive track segments. In a Lagrangian relaxation approach we solve several of these subproblems together in order to produce solutions which consist of combinatorially compatible schedules along the track segments. The computational results on a mostly single track corridor taken from the INFORMS RAS Problem Solving Competition 2012 data indicate that our new solution approach is rather strong. Indeed, for this instance the solution of the Lagrangian relaxation is already integral. T3 - ZIB-Report - 17-46 Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-64743 SN - 1438-0064 ER - TY - GEN A1 - Fischer, Frank A1 - Grimm, Boris A1 - Klug, Torsten A1 - Schlechte, Thomas T1 - A Re-optimization Approach for Train Dispatching N2 - The Train Dispatching Problem (TDP) is to schedule trains through a network in a cost optimal way. Due to disturbances during operation existing track allocations often have to be re-scheduled and integrated into the timetable. This has to be done in seconds and with minimal timetable changes to guarantee smooth and conflict free operation. We present an integrated modeling approach for the re-optimization task using Mixed Integer Programming. Finally, we provide computational results for scenarios provided by the INFORMS RAS Problem Soling Competition 2012. T3 - ZIB-Report - 16-49 Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-60493 SN - 1438-0064 ER - TY - GEN A1 - Fischer, Frank A1 - Schlechte, Thomas T1 - Comparing two dual relaxations of large scale train timetabling problems N2 - Railway transportation and in particular train timetabling is one of the basic and source application areas of combinatorial optimization and integer programming. We will discuss two well established modeling techniques for the train timetabling problem. In this paper we focus on one major ingredient - the bounding by dual relaxations. We compare two classical dual relaxations of large scale time expanded train timetabling problems - the Lagrangean Dual and Lagrangean Decomposition. We discuss the convergence behavior and show limitations of the Lagrangean Decomposition approach for a configuration based model. We introduce a third dualization approach to overcome those limitations. Finally, we present promising preliminary computational experiments that show that our new approach indeed has superior convergence properties. T3 - ZIB-Report - 15-43 Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-56068 SN - 1438-0064 ER - TY - CHAP A1 - Caimi, Gabrio A1 - Fischer, Frank A1 - Schlechte, Thomas T1 - Railway Track Allocation T2 - Handbook of Optimization in the Railway Industry N2 - This chapter addresses the classical task to decide which train runs on which track in a railway network. In this context a track allocation defines the precise routing of trains through a railway network, which usually has only a limited capacity. Moreover, the departure and arrival times at the visited stations of each train must simultaneously meet several operational and safety requirements. The problem to find the 'best possible' allocation for all trains is called the track allocation problem (TTP). Railway systems can be modeled on a very detailed scale covering the behavior of individual trains and the safety system to a large extent. However, those microscopic models are too big and not scalable to large networks, which make them inappropriate for mathematical optimization on a network wide level. Hence, most network optimization approaches consider simplified, so called macroscopic, models. In the first part we take a look at the challenge to construct a reliable and condensed macroscopic model for the associated microscopic model and to facilitate the transition between both models of different scale. In the main part we focus on the optimization problem for macroscopic models of the railway system. Based on classical graph-theoretical tools the track allocation problem is formulated to determine conflict-free paths in corresponding time-expanded graphs. We present standard integer programming model formulations for the track allocation problem that model resource or block conflicts in terms of packing constraints. In addition, we discuss the role of maximal clique inequalities and the concept of configuration networks. We will also present classical decomposition approaches like Lagrangian relaxation and bundle methods. Furthermore, we will discuss recently developed techniques, e.g., dynamic graph generation. Finally, we will discuss the status quo and show a vision of mathematical optimization to support real world track allocation, i.e. integrated train routing and scheduling, in a data-dominated and digitized railway future. Y1 - 2018 SN - 978-3-319-72152-1 U6 - https://doi.org/https://doi.org/10.1007/978-3-319-72153-8 VL - 268 SP - 141 EP - 160 PB - Springer International Publishing ER - TY - CHAP A1 - Fischer, Frank A1 - Schlechte, Thomas T1 - Comparing two dual relaxations of large scale train timetabling problems T2 - Proceedings of Conference on Advanced Systems in Public Transport 2015 N2 - Railway transportation and in particular train timetabling is one of the basic and source application areas of combinatorial optimization and integer programming. We will discuss two well established modeling techniques for the train timetabling problem. In this paper we focus on one major ingredient - the bounding by dual relaxations. We compare two classical dual relaxations of large scale time expanded train timetabling problems - the Lagrangean Dual and Lagrangean Decomposition. We discuss the convergence behavior and show limitations of the Lagrangean Decomposition approach for a configuration based model. We introduce a third dualization approach to overcome those limitations. Finally, we present promising preliminary computational experiments that show that our new approach indeed has superior convergence properties. Y1 - 2015 ER -