TY - CHAP A1 - Bargmann, Dagmar A1 - Ebbers, Mirko A1 - Heinecke, Nina A1 - Koch, Thorsten A1 - Kühl, Veronika A1 - Pelzer, Antje A1 - Pfetsch, Marc A1 - Rövekamp, Jessica A1 - Spreckelsen, Klaus T1 - State-of-the-art in evaluating gas network capacities T2 - Evaluating Gas Network Capacities Y1 - 2015 SN - 9781611973686 SP - 65 EP - 84 PB - Society for Industrial and Applied Mathematics ER - TY - CHAP A1 - Schewe, Lars A1 - Koch, Thorsten A1 - Martin, Alexander A1 - Pfetsch, Marc T1 - Mathematical optimization for evaluating gas network capacities T2 - Evaluating Gas Network Capacities Y1 - 2015 SN - 9781611973686 SP - 87 EP - 102 PB - Society for Industrial and Applied Mathematics ER - TY - GEN A1 - Humpola, Jesco T1 - Sufficient Pruning Conditions for MINLP in Gas Network Design N2 - One quarter of Europe’s energy demand is provided by natural gas distributed through a vast pipeline network covering the whole of Europe. At a cost of 1 million Euros per kilometer the extension of the European pipeline network is already a multi billion Euro business. Therefore, automatic planning tools that support the decision process are desired. We model the topology extension problem in gas networks by a mixed-integer nonlinear program (MINLP). This gives rise to a so-called active transmission problem, a continuous nonlinear non-convex feasibility problem which emerges from the MINLP model by fixing all integral variables. In this article we offer novel sufficient conditions for proving the infeasibility of this active transmission problem. These conditions can be expressed in the form of a mixed-integer program (MILP), i.e., the infeasibility of a non-convex NLP can be certified by solving an MILP. These results provide an efficient bounding procedure in a branch-and-bound algorithm. Our computational results demonstrate a substantial speed-up for the necessary computations. T3 - ZIB-Report - 15-04 KW - Network Design KW - Mixed-Integer Nonlinear Programming KW - Infeasibility Detection Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-53489 ER - TY - THES A1 - Humpola, Jesco T1 - Gas Network Optimization by MINLP N2 - One quarter of Europe's energy demand is provided by natural gas distributed through a vast pipeline network covering the whole of Europe. At a cost of 1 million Euros per kilometer the extension of the European pipeline network is already a multi billion Euro business. The challenging question is how to expand and operate the network in order to facilitate the transportation of specified gas quantities at minimum cost. This task can be formulated as a mathematical optimization problem that reflects to real-world instances of enormous size and complexity. The aim of this thesis is the development of novel theory and optimization algorithms which make it possible to solve these problems. Gas network topology optimization problems can be modeled as nonlinear mixed-integer programs (MINLPs). Such an MINLP gives rise to a so-called active transmission problem (ATP), a continuous nonlinear non-convex feasibility problem which emerges from the MINLP model by fixing all integral variables. The key to solving the ATP as well as the overall gas network topology optimization problem and the main contribution of this thesis is a novel domain relaxation of the variable bounds and constraints in combination with a penalization in the objective function. In case the domain relaxation does not yield a primal feasible solution for the ATP we offer novel sufficient conditions for proving the infeasibility of the ATP. These conditions can be expressed in the form of an MILP, i.e., the infeasibility of a non-convex NLP can be certified by solving an MILP. These results provide an efficient bounding procedure in a branch-and-bound algorithm. If the gas network consists only of pipes and valves, the ATP turns into a passive transmission problem (PTP). Although its constraints are non-convex, its domain relaxation can be proven to be convex. Consequently, the feasibility of the PTP can be checked directly in an efficient way. Another advantage of the passive case is that the solution of the domain relaxation gives rise to a cutting plane for the overall topology optimization problem that expresses the infeasibility of the PTP. This cut is obtained by a Benders argument from the Lagrange function of the domain relaxation augmented by a specially tailored pc-regularization. These cuts provide tight lower bounds for the passive gas network topology optimization problem. The domain relaxation does not only provide certificates of infeasibility and cutting planes, it can also be used to construct feasible primal solutions. We make use of parametric sensitivity analysis in order to identify binary variables to be switched based on dual information. This approach allows for the first time to compute directly MINLP solutions for large-scale gas network topology optimization problems. All the research in this thesis has been realized within the collaborative research project "Forschungskooperation Netzoptimierung (ForNe)". The developed software is in use by the cooperation partner Open Grid Europe GmbH. Parts of this thesis have been published in book chapters, journal articles and technical reports. An overview of the topics and solution approaches within the research project is given by Martin et al. (2011) and Fügenschuh et al. (2013). Gas network operation approaches and solution methods are described in detail by Pfetsch et al. (2014) and with a special focus on topology optimization in Fügenschuh et al. (2011). The primal heuristic presented in this thesis is published by Humpola et al. (2014b). The method for pruning nodes of the branch-and-bound tree for an approximation of the original problem is described in Fügenschuh and Humpola (2013) and Humpola et al. (2014a). The Benders like inequality is introduced by Humpola and Fügenschuh (2013). N2 - Ein Viertel des europäischen Energiebedarfs wird durch Gas gedeckt, das durch ein europaweites Pipelinesystem verteilt wird. Aufgrund von Ausbaukosten von 1 Mio. Euro pro Kilometer ist der Netzausbau ein Milliardenunterfangen. Die größte Herausforderung besteht darin zu entscheiden, wie das Netzwerk kostengünstig ausgebaut und genutzt werden kann, um notwendige Gasmengen zu transportieren. Diese Aufgabe kann mit Hilfe eines mathematischen Optimierungsproblems formuliert werden, wobei anwendungsnahe Instanzen eine enorme Größe und Komplexität aufweisen. Ziel der vorliegenden Arbeit ist die Entwicklung neuer mathematischer Theorien und damit einhergehender Optimierungsalgorithmen, die es ermöglichen, derartige Probleme zu lösen. Die Optimierung der Topologie eines Gasnetzwerks kann mit Hilfe eines nichtlinearen gemischt-ganzzahligen Programms (MINLP) modelliert werden. Durch Fixierung aller ganzzahligen Variablen ergibt sich ein kontinuierliches Zulässigkeitsproblem, das als aktives Transmissionsproblem (ATP) bezeichnet wird. Die zentrale Methode um dieses ATP zu lösen, ist eine neuartige Relaxierung, welche Variablenschranken und einige Nebenbedingungen relaxiert und in der Zielfunktion bestraft. Diese Relaxierung bildet den Kern der in dieser Arbeit vorgestellten Theorie und ermöglicht so die effiziente Lösung der Topologieoptimierung eines Gasnetzwerkes. Für den Fall, dass die Relaxierung keine Primallösung für das ATP liefert, ist es uns gelungen, hinreichende Bedingungen für die Unzulässigkeit des ATP zu formulieren, die durch ein MILP dargestellt werden. Kurz gefasst kann die Unzulässigkeit eines nicht-konvexen NLP durch Lösung eines MILP bewiesen werden. Beide Methoden liefern effiziente Schranken in einem branch-and-bound Lösungsverfahren. Besteht ein Gasnetzwerk nur aus Rohren und Schiebern, dann wird das ATP als passives Transmissionsproblem (PTP) bezeichnet. Obwohl die Nebenbedingungen des PTP nicht konvex sind, konnten wir zeigen, dass seine Relaxierung konvex ist. Daher kann die Unzulässigkeit des PTP direkt auf effiziente Weise geprüft werden. Außerdem können mit Hilfe der Relaxierung in diesem speziellen Fall Schnittebenen für das Topologieoptimierungsproblem aufgestellt werden. Diese repräsentieren die Unzulässigkeit des PTP und folgen aus der Lagrange Funktion der Relaxierung zusammen mit einer speziellen Erweiterung, der sogenannten pc-Regularisierung. Abgesehen von den genannten Klassifizierungen kann die Relaxierung auch genutzt werden, um primale Lösungen zu konstruieren. Hier nutzen wir die parametrische Sensitivitätsanalyse, um mit Hilfe dualer Informationen Binärvariablen des ATP zu identifizieren, deren Werte angepasst werden müssen. Dieser Ansatz erlaubt es zum ersten Mal, direkt MINLP Lösungen für das Topologieoptimierungsproblem realer Gasnetzwerke zu berechnen. Die Resultate dieser Arbeit wurden im Rahmen des Forschungsprojekts "Forschungskooperation Netzoptimierung (ForNe)" erarbeitet. Die entwickelte Software wird vom Kooperationspartner Open Grid Europe GmbH aktiv genutzt. Teile dieser Arbeit sind in Buchkapiteln, Journalen und technischen Berichten publiziert. Eine Übersicht über die Themen und Lösungsansätze im ForNe-Projekt veröffentlichten Martin u. a. (2011) und Fügenschuh u. a. (2013). Für Lösungsmethoden für die operative Nutzung von Gasnetzwerken verweisen wir auf Pfetsch u. a. (2014). Ansätze für eine Topologieoptimierung wurden von Fügenschuh u. a. (2011) beschrieben. Die in dieser Arbeit präsentierte primale Heuristik ist publiziert von Humpola u. a. (2014b). Die genannte Methode, um Knoten innerhalb des branch-and-bound Baums abzuschneiden, wurde für eine Approximation des Topologieproblems von Fügenschuh und Humpola (2013) und Humpola u. a. (2014a) beschrieben. Ein Bericht über die Ungleichungen nach Benders ist in Humpola und Fügenschuh (2013) nachzulesen. T2 - Gas Netzwerk Optimierung mittels MINLP Y1 - 2014 UR - http://opus4.kobv.de/opus4-tuberlin/frontdoor/index/index/docId/5904 ER - TY - CHAP A1 - Hiller, Benjamin A1 - Humpola, Jesco A1 - Lehmann, Thomas A1 - Lenz, Ralf A1 - Morsi, Antonio A1 - Pfetsch, Marc A1 - Schewe, Lars A1 - Schmidt, Martin A1 - Schwarz, Robert A1 - Schweiger, Jonas A1 - Stangl, Claudia A1 - Willert, Bernhard T1 - Computational results for validation of nominations T2 - Evaluating Gas Network Capacities N2 - The different approaches to solve the validation of nomination problem presented in the previous chapters are evaluated computationally in this chapter. Each approach is analyzed individually, as well as the complete solvers for these problems. We demonstrate that the presented approaches can successfully solve large-scale real-world instances. Y1 - 2015 SN - 9781611973686 VL - SIAM-MOS series on Optimization ER - TY - CHAP A1 - Humpola, Jesco A1 - Fügenschuh, Armin A1 - Hiller, Benjamin A1 - Koch, Thorsten A1 - Lehmann, Thomas A1 - Lenz, Ralf A1 - Schwarz, Robert A1 - Schweiger, Jonas T1 - The Specialized MINLP Approach T2 - Evaluating Gas Network Capacities N2 - We propose an approach to solve the validation of nominations problem using mixed-integer nonlinear programming (MINLP) methods. Our approach handles both the discrete settings and the nonlinear aspects of gas physics. Our main contribution is an innovative coupling of mixed-integer (linear) programming (MILP) methods with nonlinear programming (NLP) that exploits the special structure of a suitable approximation of gas physics, resulting in a global optimization method for this type of problem. Y1 - 2015 SN - 9781611973686 VL - SIAM-MOS series on Optimization ER - TY - BOOK A1 - Koch, Thorsten A1 - Hiller, Benjamin A1 - Pfetsch, Marc A1 - Schewe, Lars T1 - Evaluating Gas Network Capacities Y1 - 2015 SN - 978-1-611973-68-6 PB - SIAM 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 - 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 - GEN A1 - Humpola, Jesco A1 - Fügenschuh, Armin T1 - A New Class of Valid Inequalities for Nonlinear Network Design Problems N2 - We consider a nonlinear nonconvex network design problem that arises in the extension of natural gas 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. Assume that there does not exist a feasible flow that fulfills all physical constraints and meets the desired entry and exit amounts. Then a natural question is where to extend the network by adding pipes in the most economic way such that this flow becomes feasible. Answering this question is computationally demanding because of the difficult problem structure. We use mixed-integer nonlinear programming techniques that rely on an outer approximation of the overall problem, and a branching on decision variables. We formulate a new class of valid inequalities (or cutting planes) which reduce the overall solution time when added to the formulation. We demonstrate the computational merits of our approach on test instances. T3 - ZIB-Report - 13-06 KW - Network Design KW - Mixed-Integer Nonlinear Programming KW - Cutting Planes Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-17771 SN - 1438-0064 ER - TY - GEN A1 - Fügenschuh, Armin A1 - Geißler, Björn A1 - Gollmer, Ralf A1 - Hayn, Christine A1 - Henrion, Rene A1 - Hiller, Benjamin A1 - Humpola, Jesco A1 - Koch, Thorsten A1 - Lehmann, Thomas A1 - Martin, Alexander A1 - Mirkov, Radoslava A1 - Morsi, Antonio A1 - Römisch, Werner A1 - Rövekamp, Jessica A1 - Schewe, Lars A1 - Schmidt, Martin A1 - Schultz, Rüdiger A1 - Schwarz, Robert A1 - Schweiger, Jonas A1 - Stangl, Claudia A1 - Steinbach, Marc A1 - Willert, Bernhard T1 - Mathematical Optimization for Challenging Network Planning Problems in Unbundled Liberalized Gas Markets N2 - The recently imposed new gas market liberalization rules in Germany lead to a change of business of gas network operators. While previously network operator and gas vendor where united, they were forced to split up into independent companies. The network has to be open to any other gas trader at the same conditions, and free network capacities have to be identified and publicly offered in a non-discriminatory way. We show that these new paradigms lead to new and challenging mathematical optimization problems. In order to solve them and to provide meaningful results for practice, all aspects of the underlying problems, such as combinatorics, stochasticity, uncertainty, and nonlinearity, have to be addressed. With such special-tailored solvers, free network capacities and topological network extensions can, for instance, be determined. T3 - ZIB-Report - 13-13 KW - Gas Market Liberalization KW - Entry-Exit Model KW - Gas Network Access Regulation KW - Mixed-Integer Nonlinear Nonconvex Stochastic Optimization Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-17821 SN - 1438-0064 ER - TY - GEN A1 - Pfetsch, Marc A1 - Fügenschuh, Armin A1 - Geißler, Björn A1 - Geißler, Nina A1 - Gollmer, Ralf A1 - Hiller, Benjamin A1 - Humpola, Jesco A1 - Koch, Thorsten A1 - Lehmann, Thomas A1 - Martin, Alexander A1 - Morsi, Antonio A1 - Rövekamp, Jessica A1 - Schewe, Lars A1 - Schmidt, Martin A1 - Schultz, Rüdiger A1 - Schwarz, Robert A1 - Schweiger, Jonas A1 - Stangl, Claudia A1 - Steinbach, Marc A1 - Vigerske, Stefan A1 - Willert, Bernhard T1 - Validation of Nominations in Gas Network Optimization: Models, Methods, and Solutions N2 - In this article we investigate methods to solve a fundamental task in gas transportation, namely the validation of nomination problem: Given a gas transmission network consisting of passive pipelines and active, controllable elements and given an amount of gas at every entry and exit point of the network, find operational settings for all active elements such that there exists a network state meeting all physical, technical, and legal constraints. We describe a two-stage approach to solve the resulting complex and numerically difficult mixed-integer non-convex nonlinear feasibility problem. The first phase consists of four distinct algorithms facilitating mixed-integer linear, mixed-integer nonlinear, reduced nonlinear, and complementarity constrained methods to compute possible settings for the discrete decisions. The second phase employs a precise continuous nonlinear programming model of the gas network. Using this setup, we are able to compute high quality solutions to real-world industrial instances whose size is significantly larger than networks that have appeared in the literature previously. T3 - ZIB-Report - 12-41 Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-16531 SN - 1438-0064 ER - TY - GEN 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 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. T3 - ZIB-Report - 16-64 KW - SCIP, Mathematical optimization, Python, Modeling Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-61348 SN - 1438-0064 ER - TY - GEN A1 - Gamrath, Gerald A1 - Koch, Thorsten A1 - Maher, Stephen J. A1 - Rehfeldt, Daniel A1 - Shinano, Yuji T1 - SCIP-Jack – A solver for STP and variants with parallelization extensions N2 - The Steiner tree problem in graphs is a classical problem that commonly arises in practical applications as one of many variants. While often a strong relationship between different Steiner tree problem variants can be observed, solution approaches employed so far have been prevalently problem-specific. In contrast, this paper introduces a general-purpose solver that can be used to solve both the classical Steiner tree problem and many of its variants without modification. This versatility is achieved by transforming various problem variants into a general form and solving them by using a state-of-the-art MIP-framework. The result is a high-performance solver that can be employed in massively parallel environments and is capable of solving previously unsolved instances. T3 - ZIB-Report - 16-41 KW - Steiner tree problem KW - SCIP-Jack KW - Steiner tree variants KW - maximum-weight connected subgraph KW - prize-collecting Steiner tree Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-60170 SN - 1438-0064 ER - TY - JOUR A1 - Humpola, Jesco A1 - Serrano, Felipe T1 - Sufficient pruning conditions for MINLP in gas network design JF - EURO Journal on Computational Optimization N2 - One-quarter of Europe’s energy demand is provided by natural gas distributed through a vast pipeline network covering the whole of Europe. At a cost of 1 million Euros per kilometer the extension of the European pipeline network is already a multi-billion Euro business. Therefore, automatic planning tools that support the decision process are desired. We model the topology optimization problem in gas networks by a mixed-integer nonlinear program (MINLP). This gives rise to a so-called active transmission problem, a continuous nonlinear non-convex feasibility problem which emerges from the MINLP model by fixing all integral variables. We offer novel sufficient conditions for proving the infeasibility of this active transmission problem. These conditions can be expressed in the form of a mixed-integer program (MILP), i.e., the infeasibility of a non-convex continuous nonlinear program (NLP) can be certified by solving an MILP. This result provides an efficient pruning procedure in a branch-and-bound algorithm. Our computational results demonstrate a substantial speedup for the necessary computations. Y1 - 2017 U6 - https://doi.org/10.1007/s13675-016-0077-8 VL - 5 IS - 1-2 SP - 239 EP - 261 PB - Springer Berlin Heidelberg ER - TY - CHAP A1 - Gotzes, Uwe A1 - Heinecke, Nina A1 - Hiller, Benjamin A1 - Rövekamp, Jessica A1 - Koch, Thorsten T1 - Regulatory rules for gas markets in Germany and other European countries T2 - Evaluating gas network capacities Y1 - 2015 SN - 978-1-611973-68-6 SP - 45 EP - 64 PB - Society for Industrial and Applied Mathematics ER - TY - GEN A1 - Walther, Tom A1 - Hiller, Benjamin A1 - Saitenmacher, René T1 - Polyhedral 3D Models for compressors in gas networks N2 - Compressor machines are crucial elements in a gas transmission network, required to compensate for the pressure loss caused by friction in the pipes. Modelling all physical and technical details of a compressor machine involves a large amount of nonlinearity, which makes it hard to use such models in the optimization of large-scale gas networks. In this paper, we are going to describe a modelling approach for the operating range of a compressor machine, starting from a physical reference model and resulting in a polyhedral representation in the 3D space of mass flow throughput as well as in- and outlet pressure. T3 - ZIB-Report - 17-66 KW - gas compressor modeling, polyhedral model, accuracy, z factor Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-65864 SN - 1438-0064 ER - TY - THES A1 - Schweiger, Jonas T1 - Exploiting structure in non-convex quadratic optimization and gas network planning under uncertainty N2 - The amazing success of computational mathematical optimization over the last decades has been driven more by insights into mathematical structures than by the advance of computing technology. In this vein, we address applications, where nonconvexity in the model and uncertainty in the data pose principal difficulties. The first part of the thesis deals with non-convex quadratic programs. Branch&Bound methods for this problem class depend on tight relaxations. We contribute in several ways: First, we establish a new way to handle missing linearization variables in the well-known Reformulation-Linearization-Technique (RLT). This is implemented into the commercial software CPLEX. Second, we study the optimization of a quadratic objective over the standard simplex or a knapsack constraint. These basic structures appear as part of many complex models. Exploiting connections to the maximum clique problem and RLT, we derive new valid inequalities. Using exact and heuristic separation methods, we demonstrate the impact of the new inequalities on the relaxation and the global optimization of these problems. Third, we strengthen the state-of-the-art relaxation for the pooling problem, a well-known non-convex quadratic problem, which is, for example, relevant in the petrochemical industry. We propose a novel relaxation that captures the essential non-convex structure of the problem but is small enough for an in-depth study. We provide a complete inner description in terms of the extreme points as well as an outer description in terms of inequalities defining its convex hull (which is not a polyhedron). We show that the resulting valid convex inequalities significantly strengthen the standard relaxation of the pooling problem. The second part of this thesis focuses on a common challenge in real world applications, namely, the uncertainty entailed in the input data. We study the extension of a gas transport network, e.g., from our project partner Open Grid Europe GmbH. For a single scenario this maps to a challenging non-convex MINLP. As the future transport patterns are highly uncertain, we propose a robust model to best prepare the network operator for an array of scenarios. We develop a custom decomposition approach that makes use of the hierarchical structure of network extensions and the loose coupling between the scenarios. The algorithm used the single-scenario problem as black-box subproblem allowing the generalization of our approach to problems with the same structure. The scenario-expanded version of this problem is out of reach for today's general-purpose MINLP solvers. Yet our approach provides primal and dual bounds for instances with up to 256 scenarios and solves many of them to optimality. Extensive computational studies show the impact of our work. N2 - Der bemerkenswerte Erfolg der angewandten mathematischen Optimierung in den letzten Dekaden ist mehr auf Einsichten in mathematische Strukturen zurückzuführen, als auf eine Steigerung der Rechenleistung. In diesem Sinne adressieren wir Anwendungen, in denen Nichtkonvexität und Unsicherheit in den Daten die Hauptschwierigkeiten darstellen. Der erste Teil dieser Arbeit beschäftigt sich mit nichtkonvexen quadratischen Optimierungsproblemen. Relaxierungen sind integraler Bestandteil von \BranchAndBound{}-Lösungsmethoden für diese Problemkategorie. Wir leisten folgende Beiträge: Erstens beschreiben wir eine neue Art fehlende Linearisierungsvariablen, in der so genannten Reformulation-Linearization-Technique (RLT), zu behandeln. Diese wird inzwischen in der kommerziellen Software CPLEX verwendet. Zweitens beschäftigen wir uns mit der Optimierung einer quadratischen Zielfunktion über die Standardsimplex oder einen so genannten Knapsack-Constraint. Solche grundlegenden Strukturen sind Teil vieler komplexer Modelle. Wir benutzen bekannte Verbindungen zum maximalen Cliquenproblem sowie zu RLT, um neue gültige Ungleichungen herzuleiten, die die Relaxierung verstärken. Drittens beschäftigen wir uns mit dem Pooling Problem, das z.B. in der Erdölindustrie relevant ist. Wie leiten eine neue Relaxierung her, die die wesentliche nicht-konvexe Struktur des Problems erfasst, aber klein genug für eine grundlegende Untersuchung ist. Wir geben eine innere Beschreibung in Form der Extrempunkte, sowie eine äußere Beschreibung in Form von Ungleichungen, die die konvexe Hülle (welche im Allgemeinen kein Polyeder ist) beschreiben, an. Wir zeigen, dass neuen die Ungleichungen die Relaxierung des Pooling Problems erheblich verstärken. Der zweite Teil der Arbeit befasst sich mit einer weiteren Herausforderung in realen Anwendungen, nämlich Unsicherheit in den Eingabedaten. Konkret untersuchen wir die Optimierung des Ausbaus eines Gastransportnetzes, wie z.B. von unserem Projektpartner Open Grid Europe GmbH. Dieses Problem ist bereits bei gegebenen Eingabedaten ein schweres nicht-konvexes gemischt-ganzzahliges Optimierungsproblem. Da zukünftige Nutzungsmuster des Netzes mit großer Unsicherheit behaftet sind, beschreiben wir ein robustes Modell, um den Netzbetreiber gegen verschiedene Szenarien abzusichern. Wir entwickeln einen speziellen Dekompositionsalgorithmus unter Berücksichtigung der hierarchischen Struktur der Ausbauten und der schwachen Kopplung zwischen den Szenarien. Unser Ansatz liefert primale und duale Schranken für Instanzen mit bis zu 256 Szenarien und löst viele beweisbar optimal. Umfangreiche Rechnungen bestätigen die Effizient der vorgestellten Methoden. KW - Nonconvexity KW - Uncertainty KW - Quadratic Programming KW - Relaxations KW - Cutting Planes KW - Standard Quadratic Programming KW - Pooling Problem KW - Gas Network Planning KW - Robust Optimization KW - Decomposition KW - Computations Y1 - 2017 UR - http://dx.doi.org/10.14279/depositonce-6015 ER - TY - JOUR A1 - Schmidt, Martin A1 - Assmann, Denis A1 - Burlacu, Robert A1 - Humpola, Jesco A1 - Joormann, Imke A1 - Kanelakis, Nikolaos A1 - Koch, Thorsten A1 - Oucherif, Djamal A1 - Pfetsch, Marc A1 - Schewe, Lars A1 - Schwarz, Robert A1 - Sirvent, Matthias T1 - GasLib – A Library of Gas Network Instances JF - Data Y1 - 2017 U6 - https://doi.org/10.3390/data2040040 VL - 2 IS - 4 ER - TY - JOUR A1 - Humpola, Jesco A1 - Lehmann, Thomas A1 - Fügenschuh, Armin T1 - A primal heuristic for optimizing the topology of gas networks based on dual information JF - EURO Journal on Computational Optimization N2 - We present a novel heuristic to identify feasible solutions of a mixed-integer nonlinear programming problem arising in natural gas transportation: the selection of new pipelines to enhance the network's capacity to a desired level in a cost-efficient way. We solve this problem in a linear programming based branch-and-cut approach, where we deal with the nonlinearities by linear outer approximation and spatial branching. At certain nodes of the branching tree, we compute a KKT point of a nonlinear relaxation. Based on the information from the KKT point we alter some of the binary variables in a locally promising way exploiting our problem-specific structure. On a test set of real-world instances, we are able to increase the chance of identifying feasible solutions by some order of magnitude compared to standard MINLP heuristics that are already built in the general-purpose MINLP solver SCIP. Y1 - 2015 U6 - https://doi.org/10.1007/s13675-014-0029-0 VL - 3 IS - 1 SP - 53 EP - 78 ER - TY - GEN A1 - Hiller, Benjamin A1 - Walther, Tom T1 - Modelling compressor stations in gas networks N2 - Gas networks are an important application area for optimization. When considering long-range transmission, compressor stations play a crucial role in these applications. The purpose of this report is to collect and systematize the models used for compressor stations in the literature. The emphasis is on recent work on simple yet accurate polyhedral models that may replace more simplified traditional models without increasing model complexity. The report also describes an extension of the compressor station data available in GasLib (http://gaslib.zib.de/) with the parameters of these models. T3 - ZIB-Report - 17-67 KW - MINLP model KW - compressor station KW - gas compressor modeling KW - nonlinear model KW - polyhedral model Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-67443 SN - 1438-0064 ER - TY - CHAP A1 - Hiller, Benjamin A1 - Saitenmacher, René A1 - Walther, Tom T1 - Analysis of operating modes of complex compressor stations T2 - Proceedings of Operations Research 2016 N2 - We consider the modeling of operation modes for complex compressor stations (i.e., ones with several in- or outlets) in gas networks. In particular, we propose a refined model that allows to precompute tighter relaxations for each operation mode. These relaxations may be used to strengthen the compressor station submodels in gas network optimization problems. We provide a procedure to obtain the refined model from the input data for the original model. Y1 - 2017 U6 - https://doi.org/10.1007/978-3-319-55702-1_34 SP - 251 EP - 257 ER - TY - CHAP A1 - Hiller, Benjamin A1 - Hayn, Christine A1 - Heitsch, Holger A1 - Henrion, René A1 - Leövey, Hernan A1 - Möller, Andris A1 - Römisch, Werner T1 - Methods for verifying booked capacities T2 - Evaluating gas network capacities Y1 - 2015 SP - 291 EP - 315 PB - Society for Industrial and Applied Mathematics ER - TY - GEN A1 - Hiller, Benjamin A1 - Koch, Thorsten A1 - Schewe, Lars A1 - Schwarz, Robert A1 - Schweiger, Jonas T1 - A System to Evaluate Gas Network Capacities: Concepts and Implementation N2 - Since 2005, the gas market in the European Union is liberalized and the trading of natural gas is decoupled from its transport. The transport is done by so-called transmissions system operators or TSOs. The market model established by the European Union views the gas transmission network as a black box, providing shippers (gas traders and consumers) the opportunity to transport gas from any entry to any exit. TSOs are required to offer maximum independent capacities at each entry and exit such that the resulting gas flows can be realized by the network without compromising security of supply. Therefore, evaluating the available transport capacities is extremely important to the TSOs. This paper gives an overview of the toolset for evaluating gas network capacities that has been developed within the ForNe project, a joint research project of seven research partners initiated by Open Grid Europe, Germany's biggest TSO. While most of the relevant mathematics is described in the book "Evaluating Gas Network Capacities", this article sketches the system as a whole, describes some developments that have taken place recently, and gives some details about the current implementation. T3 - ZIB-Report - 17-03 KW - operations research in energy KW - gas network optimization KW - entry-exit model KW - freely allocable capacity KW - large-scale mixed-integer nonlinear programming Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-61931 SN - 1438-0064 N1 - A revised and extended version is available as ZIB-Report 18-11. ER - TY - GEN A1 - Griewank, Andreas A1 - Streubel, Tom A1 - Lehmann, Lutz A1 - Hasenfelder, Richard A1 - Radons, Manuel T1 - Piecewise linear secant approximation via Algorithmic Piecewise Differentiation N2 - It is shown how piecewise differentiable functions \(F: R^n → R^m\) that are defined by evaluation programs can be approximated locally by a piecewise linear model based on a pair of sample points x̌ and x̂. We show that the discrepancy between function and model at any point x is of the bilinear order O(||x − x̌|| ||x − x̂||). This is a little surprising since x ∈ R^n may vary over the whole Euclidean space, and we utilize only two function samples F̌ = F(x̌) and F̂ = F(x̂), as well as the intermediates computed during their evaluation. As an application of the piecewise linearization procedure we devise a generalized Newton’s method based on successive piecewise linearization and prove for it sufficient conditions for convergence and convergence rates equaling those of semismooth Newton. We conclude with the derivation of formulas for the numerically stable implementation of the aforedeveloped piecewise linearization methods. T3 - ZIB-Report - 16-54 KW - Automatic differentiation KW - Computational graph KW - Lipschitz continuity KW - Generalized Hermite interpolation KW - ADOL-C Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-61642 SN - 1438-0064 ER - TY - JOUR A1 - Kickhöfer, Benjamin A1 - Kern, Julia T1 - Pricing local emission exposure of road traffic: An agent-based approach JF - Transportation Research Part D: Transport and Environment N2 - This paper proposes a new approach to iteratively calculate local air pollution exposure tolls in large-scale urban settings by taking the exposure times and locations of individuals into consideration. It explicitly avoids detailed air pollution concentration calculations and is therefore characterized by little data requirements, reasonable computation times for iterative calculations, and open-source compatibility. In a first step, the paper shows how to derive time-dependent vehicle-specific exposure tolls in an agent-based model. It closes the circle from the polluting entity, to the receiving entity, to damage costs, to tolls, and back to the behavioral change of the polluting entity. In a second step, the approach is applied to a large-scale real-world scenario of the Munich metropolitan area in Germany. Changes in emission levels, exposure costs, and user benefits are calculated. These figures are compared to a flat emission toll, and to a regulatory measure (a speed reduction in the inner city), respectively. The results indicate that the flat emission toll reduces overall emissions more significantly than the exposure toll, but its exposure cost reductions are rather small. For the exposure toll, overall emissions increase for freight traffic which implies a potential conflict between pricing schemes to optimize local emission exposure and others to abate climate change. Regarding the mitigation of exposure costs caused by urban travelers, the regulatory measure is found to be an effective strategy, but it implies losses in user benefits. Y1 - 2015 U6 - https://doi.org/10.1016/j.trd.2015.04.019 VL - 37 SP - 14 EP - 28 ER - TY - JOUR A1 - Gamrath, Gerald A1 - Koch, Thorsten A1 - Martin, Alexander A1 - Miltenberger, Matthias A1 - Weninger, Dieter T1 - Progress in presolving for mixed integer programming JF - Mathematical Programming Computation N2 - This paper describes three presolving techniques for solving mixed integer programming problems (MIPs) that were implemented in the academic MIP solver SCIP. The task of presolving is to reduce the problem size and strengthen the formulation, mainly by eliminating redundant information and exploiting problem structures. The first method fixes continuous singleton columns and extends results known from duality fixing. The second analyzes and exploits pairwise dominance relations between variables, whereas the third detects isolated subproblems and solves them independently. The performance of the presented techniques is demonstrated on two MIP test sets. One contains all benchmark instances from the last three MIPLIB versions, while the other consists of real-world supply chain management problems. The computational results show that the combination of all three presolving techniques almost halves the solving time for the considered supply chain management problems. For the MIPLIB instances we obtain a speedup of 20 % on affected instances while not degrading the performance on the remaining problems. Y1 - 2015 U6 - https://doi.org/10.1007/s12532-015-0083-5 VL - 7 IS - 4 SP - 367 EP - 398 ER -