TY - JOUR A1 - Witzig, Jakob A1 - Beckenbach, Isabel A1 - Eifler, Leon A1 - Fackeldey, Konstantin A1 - Gleixner, Ambros A1 - Grever, Andreas A1 - Weber, Marcus T1 - Mixed-Integer Programming for Cycle Detection in Non-reversible Markov Processes JF - Multiscale Modeling and Simulation N2 - In this paper, we present a new, optimization-based method to exhibit cyclic behavior in non-reversible stochastic processes. While our method is general, it is strongly motivated by discrete simulations of ordinary differential equations representing non-reversible biological processes, in particular molecular simulations. Here, the discrete time steps of the simulation are often very small compared to the time scale of interest, i.e., of the whole process. In this setting, the detection of a global cyclic behavior of the process becomes difficult because transitions between individual states may appear almost reversible on the small time scale of the simulation. We address this difficulty using a mixed-integer programming model that allows us to compute a cycle of clusters with maximum net flow, i.e., large forward and small backward probability. For a synthetic genetic regulatory network consisting of a ring-oscillator with three genes, we show that this approach can detect the most productive overall cycle, outperforming classical spectral analysis methods. Our method applies to general non-equilibrium steady state systems such as catalytic reactions, for which the objective value computes the effectiveness of the catalyst. KW - Markov State Models KW - NESS KW - Non-reversible Markov Processes KW - Mixed-Integer Programming Y1 - 2018 U6 - https://doi.org/10.1137/16M1091162 SN - 1438-0064 VL - 16 IS - 1 SP - 248 EP - 265 ER - TY - CHAP A1 - Schade, Stanley A1 - Strehler, Martin ED - Goerigk, Marc ED - Werneck, Renato T1 - The Maximum Flow Problem for Oriented Flows T2 - 16th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2016) N2 - In several applications of network flows, additional constraints have to be considered. In this paper, we study flows, where the flow particles have an orientation. For example, cargo containers with doors only on one side and train coaches with 1st and 2nd class compartments have such an orientation. If the end position has a mandatory orientation, not every path from source to sink is feasible for routing or additional transposition maneuvers have to be made. As a result, a source-sink path may visit a certain vertex several times. We describe structural properties of optimal solutions, determine the computational complexity, and present an approach for approximating such flows. Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0030-drops-65318 UR - http://drops.dagstuhl.de/opus/volltexte/2016/6531 SN - 978-3-95977-021-7 SN - 2190-6807 N1 - Keywords: network flow with orientation, graph expansion, approximation, container logistics, train routing VL - 54 SP - 1 EP - 13 PB - Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik CY - Dagstuhl, Germany ER - TY - CHAP A1 - Maher, Stephen J. A1 - Miltenberger, Matthias A1 - Pedroso, João Pedro A1 - Rehfeldt, Daniel A1 - Schwarz, Robert A1 - Serrano, Felipe T1 - PySCIPOpt: Mathematical Programming in Python with the SCIP Optimization Suite T2 - Mathematical Software – ICMS 2016 N2 - SCIP is a solver for a wide variety of mathematical optimization problems. It is written in C and extendable due to its plug-in based design. However, dealing with all C specifics when extending SCIP can be detrimental to development and testing of new ideas. This paper attempts to provide a remedy by introducing PySCIPOpt, a Python interface to SCIP that enables users to write new SCIP code entirely in Python. We demonstrate how to intuitively model mixed-integer linear and quadratic optimization problems and moreover provide examples on how new Python plug-ins can be added to SCIP. Y1 - 2016 U6 - https://doi.org/10.1007/978-3-319-42432-3_37 VL - 9725 SP - 301 EP - 307 PB - Springer ER - TY - GEN A1 - Borndörfer, Ralf A1 - Klug, Torsten A1 - Lamorgese, Leonardo A1 - Mannino, Carlo A1 - Reuther, Markus A1 - Schlechte, Thomas T1 - Recent Success Stories on Optimization of Railway Systems N2 - Planning and operating railway transportation systems is an extremely hard task due to the combinatorial complexity of the underlying discrete optimization problems, the technical intricacies, and the immense size of the problem instances. Because of that, however, mathematical models and optimization techniques can result in large gains for both railway cus- tomers and operators, e.g., in terms of cost reductions or service quality improvements. In the last years a large and growing group of researchers in the OR community have devoted their attention to this domain devel- oping mathematical models and optimization approaches to tackle many of the relevant problems in the railway planning process. However, there is still a gap to bridge between theory and practice, with a few notable exceptions. In this paper we address three success stories, namely, long-term freight train routing (part I), mid-term rolling stock rotation planning (part II), and real-time train dispatching (part III). In each case, we describe real-life, successful implementations. We will dis- cuss the individual problem setting, survey the optimization literature, and focus on particular aspects addressed by the mathematical models. We demonstrate on concrete applications how mathematical optimization can support railway planning and operations. This gives proof that math- ematical optimization can support the planning of rolling stock resources. Thus, mathematical models and optimization can lead to a greater effi- ciency of railway operations and will serve as a powerful and innovative tool to meet recent challenges of the railway industry. T3 - ZIB-Report - 14-47 KW - railway planning KW - railway operations KW - capacity optimization Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-53726 SN - 1438-0064 ER - TY - GEN A1 - Fügenschuh, Armin A1 - Junosza-Szaniawski, Konstanty A1 - Klug, Torsten A1 - Kwasiborski, Slawomir A1 - Schlechte, Thomas T1 - Fastest, average and quantile schedule N2 - We consider problems concerning the scheduling of a set of trains on a single track. For every pair of trains there is a minimum headway, which every train must wait before it enters the track after another train. The speed of each train is also given. Hence for every schedule - a sequence of trains - we may compute the time that is at least needed for all trains to travel along the track in the given order. We give the solution to three problems: the fastest schedule, the average schedule, and the problem of quantile schedules. The last problem is a question about the smallest upper bound on the time of a given fraction of all possible schedules. We show how these problems are related to the travelling salesman problem. We prove NP-completeness of the fastest schedule problem, NP-hardness of quantile of schedules problem, and polynomiality of the average schedule problem. We also describe some algorithms for all three problems. In the solution of the quantile problem we give an algorithm, based on a reverse search method, generating with polynomial delay all Eulerian multigraphs with the given degree sequence and a bound on the number of such multigraphs. A better bound is left as an open question. T3 - ZIB-Report - 14-49 KW - eulerian multigraphs KW - scheduling Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-53592 SN - 1438-0064 ER - TY - JOUR A1 - Maher, Stephen J. T1 - A novel passenger recovery approach for the integrated airline recovery problem JF - Computers & Operations Research N2 - Schedule disruptions require airlines to intervene through the process of recovery; this involves modifications to the planned schedule, aircraft routings, crew pairings and passenger itineraries. Passenger recovery is generally considered as the final stage in this process, and hence passengers experience unnecessarily large impacts resulting from flight delays and cancellations. Most recovery approaches considering passengers involve a separately defined module within the problem formulation. However, this approach may be overly complex for recovery in many aviation and general transportation applications. This paper presents a unique description of the cancellation variables that models passenger recovery by prescribing the alternative travel arrangements for passengers in the event of flight cancellations. The results will demonstrate that this simple, but effective, passenger recovery approach significantly reduces the operational costs of the airline and increases passenger flow through the network. The integrated airline recovery problem with passenger reallocation is solved using column-and-row generation to achieve high quality solutions in short runtimes. An analysis of the column-and-row generation solution approach is performed, identifying a number of enhancement techniques to further improve the solution runtimes. Y1 - 2015 U6 - https://doi.org/10.1016/j.cor.2014.11.005 VL - 57 SP - 123 EP - 137 ER - TY - GEN A1 - Fügenschuh, Armin A1 - Humpola, Jesco T1 - A Unified View on Relaxations for a Nonlinear Network Flow Problem N2 - We consider a nonlinear nonconvex network flow problem that arises, for example, in natural gas or water transmission networks. Given is such network with active and passive components, that is, valves, compressors, pressure regulators (active) and pipelines (passive), and a desired amount of flow at certain specified entry and exit nodes of the network. Besides flow conservation constraints in the nodes the flow must fulfill nonlinear nonconvex pressure loss constraints on the arcs subject to potential values (i.e., pressure levels) in both end nodes of each arc. The problem is how to numerically compute this flow and pressures. We review an existing approach of Maugis (1977) and extend it to the case of networks with active elements (for example, compressors). We further examine different ways of relaxations for the nonlinear network flow model. We compare different approaches based on nonlinear optimization numerically on a set of test instances. T3 - ZIB-Report - 13-31 KW - Nonlinear Network Flow KW - Mixed-Integer Nonlinear Programming KW - Relaxations Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-18857 ER - TY - CHAP A1 - Lindner, Niels A1 - Masing, Berenike A1 - Liebchen, Christian T1 - Integrierte Baufahrplanoptimierung auf dem Netz der S-Bahn Berlin T2 - HEUREKA'24 - Optimierung in Verkehr und Transport N2 - Zur Instandhaltung von Eisenbahnnetzen sind regelmäßig Baumaßnahmen erforderlich. Diese erfordern stets Anpassungen der Fahrpläne. Um den Fahrgästen trotz der Baumaßnahme weiterhin einen möglichst großen Teil des Regelangebotes bieten zu können, bewegen sich die resultierenden Baufahrpläne insbesondere in Schnellbahnnetzen mit ihren dichten Zugfolgen häufig nahe der Kapazitätsgrenze der Infrastruktur. Etablierte Verfahren zur Taktfahrplanoptimierung können diesen Anforderungen nicht genügen, da in der Praxis Anpassungen von Laufwegen der Linien, sowie der Gleisbelegungen häufig Teil der realisierten Lösungen sind. Für diese Aufgabe haben die Autoren zuletzt ein Optimierungsmodell vorgestellt, welches diese Möglichkeiten ausschöpft. In dem vorliegenden Beitrag wird erstmalig dessen Anwendung auf ein unmittelbar der Praxis der Baufahrplanung entnommenes Beispiel aus dem Netz der Berliner S-Bahn im Detail beschrieben. Y1 - 2024 VL - 002/140 ER - TY - CHAP A1 - Lindner, Niels A1 - Masing, Berenike T1 - SAT-Generated Initial Solutions for Integrated Line Planning and Turn-Sensitive Periodic Timetabling with Track Choice T2 - hEART 2024: 12th Symposium of the European Association for Research in Transportation N2 - Periodic timetabling is a challenging planning task in public transport. As safety requirements are crucial, track allocation is indispensable for validating the practical feasibility of a railway timetable. For busy stations with limited capacities, this requires a detailed planning of turn-arounds. It is therefore desirable to integrate timetabling not only with track allocation, but also with vehicle scheduling and line planning. This is captured by the Integrated Line Planning and Turn-Sensitive Periodic Timetabling Problem with Track Choice, whose MIP formulation has been demonstrated to be effective for construction site railway rescheduling, as long as a good quality initial solution is available. In this paper, we discuss how to generate such a solution by extending the SAT formulation of the Periodic Event Scheduling Problem with track choice, track occupation, and minimum service frequency components. The SAT approach is superior to pure MIP on real-world instances of the S-Bahn Berlin network. KW - Periodic Timetabling KW - Railway Timetabling KW - Railway Track Allocation KW - Boolean Satisfiability Problem KW - Rescheduling KW - Line Planning Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-98066 UR - https://transp-or.epfl.ch/heart/2024/abstracts/hEART_2024_paper_3685.pdf ER - TY - CHAP A1 - Lindner, Niels A1 - Liebchen, Christian A1 - Masing, Berenike T1 - Forward Cycle Bases and Periodic Timetabling T2 - 21st Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2021) N2 - Periodic timetable optimization problems in public transport can be modeled as mixed-integer linear programs by means of the Periodic Event Scheduling Problem (PESP). In order to keep the branch-and-bound tree small, minimum integral cycle bases have been proven successful. We examine forward cycle bases, where no cycle is allowed to contain a backward arc. After reviewing the theory of these bases, we describe the construction of an integral forward cycle basis on a line-based event-activity network. Adding turnarounds to the instance R1L1 of the benchmark library PESPlib, we computationally evaluate three types of forward cycle bases in the Pareto sense, and come up with significant improvements concerning dual bounds. Y1 - 2021 U6 - https://doi.org/10.4230/OASIcs.ATMOS.2021.2 VL - 96 SP - 2:1 EP - 2:14 ER -