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 - 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 - GEN A1 - Fischer, Alexander A1 - Cordes, Frank A1 - Schütte, Christof T1 - Hybrid Monte Carlo with Adaptive Temperature in a Mixed-Canonical Ensemble: Efficient Conformational Analysis of RNA N2 - A hybrid Monte Carlo method with adaptive temperature choice is presented, which exactly generates the distribution of a mixed-canonical ensemble composed of two canonical ensembles at low and high temperature. The analysis of resulting Markov chains with the reweighting technique shows an efficient sampling of the canonical distribution at low temperature, whereas the high temperature component facilitates conformational transitions, which allows shorter simulation times. \\The algorithm was tested by comparing analytical and numerical results for the small n-butane molecule before simulations were performed for a triribonucleotide. Sampling the complex multi-minima energy landscape of these small RNA segments, we observed enforced crossing of energy barriers. T3 - ZIB-Report - SC-97-67 Y1 - 1997 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-3364 ER - TY - JOUR A1 - Fischer, Alexander A1 - Cordes, Frank A1 - Schütte, Christof T1 - Hybrid Monte Carlo with Adaptive Temperature in Mixed–Canonical Ensemble: Efficient conformational analysis of RNA JF - J. Comp. Chem. Y1 - 1998 U6 - https://doi.org/10.1002/(SICI)1096-987X(19981130)19:15<1689::AID-JCC2>3.0.CO;2-J VL - 19 IS - 15 SP - 1689 EP - 1697 ER - TY - JOUR A1 - Fischer, Alexander A1 - Cordes, Frank A1 - Schütte, Christof T1 - Hybrid Monte Carlo with adaptive temperature in mixed-canonical ensemble JF - J. Comp. Chem. Y1 - 1998 UR - http://publications.imp.fu-berlin.de/97/ U6 - https://doi.org/10.1002/(SICI)1096-987X(19981130)19:15<1689::AID-JCC2>3.0.CO;2-J VL - 19 IS - 15 SP - 1689 EP - 1697 ER - TY - JOUR A1 - Fischer, Alexander A1 - Cordes, Frank A1 - Schütte, Christof T1 - Hybrid Monte Carlo with adaptive temperature choice JF - Comp. Phys. Comm. Y1 - 1999 UR - http://publications.imp.fu-berlin.de/93/ U6 - https://doi.org/10.1016/S0010-4655(99)00274-X VL - 121 SP - 37 EP - 39 ER - TY - GEN A1 - Fischer, Alexander A1 - Schütte, Christof A1 - Deuflhard, Peter A1 - Cordes, Frank T1 - Hierarchical Uncoupling-Coupling of Metastable Conformations N2 - Uncoupling-coupling Monte Carlo (UCMC) combines uncoupling techniques for finite Markov chains with Markov chain Monte Carlo methodology. UCMC aims at avoiding the typical metastable or trapping behavior of Monte Carlo techniques. From the viewpoint of Monte Carlo, a slowly converging long-time Markov chain is replaced by a limited number of rapidly mixing short-time ones. Therefore, the state space of the chain has to be hierarchically decomposed into its metastable conformations. This is done by means of combining the technique of conformation analysis as recently introduced by the authors, and appropriate annealing strategies. We present a detailed examination of the uncoupling-coupling procedure which uncovers its theoretical background, and illustrates the hierarchical algorithmic approach. Furthermore, application of the UCMC algorithm to the $n$-pentane molecule allows us to discuss the effect of its crucial steps in a typical molecular scenario. T3 - ZIB-Report - 01-03 KW - almost invariant sets KW - bridge sampling KW - metastability KW - hierarchical annealing KW - hybrid Monte Carlo KW - $n$-pentane molecule KW - ratio of normalizing co Y1 - 2001 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-6296 ER - TY - CHAP A1 - Fischer, Alexander A1 - Schütte, Christof A1 - Deuflhard, Peter A1 - Cordes, Frank ED - Schlick, T. ED - Gan, H. T1 - Hierarchical Uncoupling-Coupling of Metastable Conformations T2 - Computational Methods for Macromolecules Y1 - 2002 UR - http://www.zib.de/PaperWeb/abstracts/ZR-01-03 IS - 24 SP - 235 EP - 259 PB - Springer ER - TY - CHAP A1 - Fischer, Alexander A1 - Schütte, Christof A1 - Deuflhard, Peter A1 - Cordes, Frank ED - Schlick, T. ED - Gan, H. T1 - Hierarchical Uncoupling-Coupling of Metastable Conformations T2 - Computational Methods for Macromolecules Y1 - 2002 UR - http://publications.imp.fu-berlin.de/128/ VL - 24 SP - 235 EP - 259 PB - Springer 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 -