Dokument-ID Dokumenttyp Verfasser/Autoren Herausgeber Haupttitel Abstract Auflage Verlagsort Verlag Erscheinungsjahr Seitenzahl Schriftenreihe Titel Schriftenreihe Bandzahl ISBN Quelle der Hochschulschrift Konferenzname Quelle:Titel Quelle:Jahrgang Quelle:Heftnummer Quelle:Erste Seite Quelle:Letzte Seite URN DOI Abteilungen
OPUS4-1220 Masterarbeit / Diplomarbeit Schweiger, Jonas Application of Multistage Stochastic Programming in Strategic Telecommunication Network Planning Telecommunication is fundamental for the information society. In both, the private and the professional sector, mobile communication is nowadays taken for granted. Starting primarily as a service for speech communication, data service and mobile Internet access are now driving the evolution of network infrastructure. In the year 2009, 19 million users generated over 33 million GB of traffic using mobile data services. The 3rd generation networks (3G or UMTS) in Germany comprises over 39,000 base stations with some 120,000 cells. From 1998 to 2008, the four network operators in Germany invested over 33 billion Euros in their infrastructure. A careful allocation of the resources is thus crucial for the profitability for a network operator: a network should be dimensioned to match customers demand. As this demand evolves over time, the infrastructure has to evolve accordingly. The demand evolution is hard to predict and thus constitutes a strong source of uncertainty. Strategic network planning has to take this uncertainty into account, and the planned network evolution should adapt to changing market conditions. The application of superior planning methods under the consideration of uncertainty can improve the profitability of the network and creates a competitive advantage. Multistage stochastic programming is a suitable framework to model strategic telecommunication network planning. We present mathematical models and effective optimization procedures for strategic cellular network design. The demand evolution is modeled as a continuous stochastic process which is approximated by a discrete scenario tree. A tree-stage approach is used for the construction of non-uniform scenario trees that serve as input of the stochastic program. The model is calibrated by historical traffic observations. A realistic system model of UMTS radio cells is used that determines coverage areas and cell capacities and takes signal propagation and interferences into account. The network design problem is formulated as a multistage stochastic mixed integer linear program, which is solved using state-of-the-art commercial MIP solvers. Problem specific presolving is proposed to reduce the problem size. Computational results on realistic data is presented. Optimization for the expected profit and the conditional value at risk are performed and compared. 149 urn:nbn:de:0297-zib-12206 Mathematical Optimization
OPUS4-1223 misc Eisenblätter, Andreas; Schweiger, Jonas Multistage Stochastic Programming in Strategic Telecommunication Network Planning Mobile communication is nowadays taken for granted. Having started primarily as a service for speech communication, data service and mobile Internet access are now driving the evolution of network infrastructure. Operators are facing the challenge to match the demand by continuously expanding and upgrading the network infrastructure. However, the evolution of the customer's demand is uncertain. We introduce a novel (long-term) network planning approach based on multistage stochastic programming, where demand evolution is considered as a stochastic process and the network is extended as to maximize the expected profit. The approach proves capable of designing large-scale realistic UMTS networks with a time-horizon of several years. Our mathematical optimization model, the solution approach, and computational results are presented in this paper. urn:nbn:de:0297-zib-12232 10.1007/s10287-012-0143-5 Mathematical Optimization
OPUS4-1234 misc Fügenschuh, Armin; Hiller, Benjamin; Humpola, Jesco; Koch, Thorsten; Lehmann, Thomas; Schwarz, Robert; Schweiger, Jonas; Szabó, Jácint Gas Network Topology Optimization for Upcoming Market Requirements Gas distribution networks are complex structures that consist of passive pipes, and active, controllable elements such as valves and compressors. Controlling such network means to find a suitable setting for all active components such that a nominated amount of gas can be transmitted from entries to exits through the network, without violating physical or operational constraints. The control of a large-scale gas network is a challenging task from a practical point of view. In most companies the actual controlling process is supported by means of computer software that is able to simulate the flow of the gas. However, the active settings have to be set manually within such simulation software. The solution quality thus depends on the experience of a human planner. When the gas network is insufficient for the transport then topology extensions come into play. Here a set of new pipes or active elements is determined such that the extended network admits a feasible control again. The question again is how to select these extensions and where to place them such that the total extension costs are minimal. Industrial practice is again to use the same simulation software, determine extensions by experience, add them to the virtual network, and then try to find a feasible control of the active elements. The validity of this approach now depends even more on the human planner. Another weakness of this manual simulation-based approach is that it cannot establish infeasibility of a certain gas nomination, unless all settings of the active elements are tried. Moreover, it is impossible to find a cost-optimal network extension in this way. In order to overcome these shortcomings of the manual planning approach we present a new approach, rigorously based on mathematical optimization. Hereto we describe a model for finding feasible controls and then extend this model such that topology extensions can additionally and simultaneously be covered. Numerical results for real-world instances are presented and discussed. urn:nbn:de:0297-zib-12348 10.1109/EEM.2011.5953035 Mathematical Optimization
OPUS4-1512 misc Martin, Alexander; Geißler, Björn; Hayn, Christine; Hiller, Benjamin; Humpola, Jesco; Koch, Thorsten; Lehmann, Thomas; Morsi, Antonio; Pfetsch, Marc; Schewe, Lars; Schmidt, Martin; Schultz, Rüdiger; Schwarz, Robert; Schweiger, Jonas; Steinbach, Marc; Willert, Bernhard Optimierung Technischer Kapazitäten in Gasnetzen Die mittel- und längerfristige Planung für den Gastransport hat sich durch Änderungen in den regulatorischen Rahmenbedingungen stark verkompliziert. Kernpunkt ist die Trennung von Gashandel und -transport. Dieser Artikel diskutiert die hieraus resultierenden mathematischen Planungsprobleme, welche als Validierung von Nominierungen und Buchungen, Bestimmung der technischen Kapazität und Topologieplanung bezeichnet werden. Diese mathematischen Optimierungsprobleme werden vorgestellt und Lösungsansätze skizziert. urn:nbn:de:0297-zib-15121 Mathematical Optimization
OPUS4-1653 misc Pfetsch, Marc E.; Fügenschuh, Armin; Geißler, Björn; Geißler, Nina; Gollmer, Ralf; Hiller, Benjamin; Humpola, Jesco; Koch, Thorsten; Lehmann, Thomas; Martin, Alexander; Morsi, Antonio; Rövekamp, Jessica; Schewe, Lars; Schmidt, Martin; Schultz, Rüdiger; Schwarz, Robert; Schweiger, Jonas; Stangl, Claudia; Steinbach, Marc C.; Vigerske, Stefan; Willert, Bernhard M. Validation of Nominations in Gas Network Optimization: Models, Methods, and Solutions 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. urn:nbn:de:0297-zib-16531 10.1080/10556788.2014.888426 Mathematical Optimization
OPUS4-1782 misc Fügenschuh, Armin; Geißler, Björn; Gollmer, Ralf; Hayn, Christine; Henrion, Rene; Hiller, Benjamin; Humpola, Jesco; Koch, Thorsten; Lehmann, Thomas; Martin, Alexander; Mirkov, Radoslava; Morsi, Antonio; Römisch, Werner; Rövekamp, Jessica; Schewe, Lars; Schmidt, Martin; Schultz, Rüdiger; Schwarz, Robert; Schweiger, Jonas; Stangl, Claudia; Steinbach, Marc C.; Willert, Bernhard M. Mathematical Optimization for Challenging Network Planning Problems in Unbundled Liberalized Gas Markets 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. urn:nbn:de:0297-zib-17821 10.1007/s12667-013-0099-8 Mathematical Optimization
OPUS4-4832 Konferenzveröffentlichung Fügenschuh, Armin; Hiller, Benjamin; Humpola, Jesco; Koch, Thorsten; Lehmann, Thomas; Schwarz, Robert; Schweiger, Jonas; Szabo, Jacint Gas Network Topology Optimization for Upcoming Market Requirements Gas distribution networks are complex structures that consist of passive pipes, and active, controllable elements such as valves and compressors. Controlling such network means to find a suitable setting for all active components such that a nominated amount of gas can be transmitted from entries to exits through the network, without violating physical or operational constraints. The control of a large-scale gas network is a challenging task from a practical point of view. In most companies the actual controlling process is supported by means of computer software that is able to simulate the flow of the gas. However, the active settings have to be set manually within such simulation software. The solution quality thus depends on the experience of a human planner. When the gas network is insufficient for the transport then topology extensions come into play. Here a set of new pipes or active elements is determined such that the extended network admits a feasible control again. The question again is how to select these extensions and where to place them such that the total extension costs are minimal. Industrial practice is again to use the same simulation software, determine extensions by experience, add them to the virtual network, and then try to find a feasible control of the active elements. The validity of this approach now depends even more on the human planner. Another weakness of this manual simulation-based approach is that it cannot establish infeasibility of a certain gas nomination, unless all settings of the active elements are tried. Moreover, it is impossible to find a cost-optimal network extension in this way. In order to overcome these shortcomings of the manual planning approach we present a new approach, rigorously based on mathematical optimization. Hereto we describe a model for finding feasible controls and then extend this model such that topology extensions can additionally and simultaneously be covered. Numerical results for real-world instances are presented and discussed. 5 International Conference on the European Energy Market (EEM) 346 351 10.1109/EEM.2011.5953035 Mathematical Optimization
OPUS4-4834 Wissenschaftlicher Artikel Eisenblätter, Andreas; Schweiger, Jonas Multistage Stochastic Programming in Strategic Telecommunication Network Planning Mobile communication is nowadays taken for granted. Having started primarily as a service for speech communication, data service and mobile Internet access are now driving the evolution of network infrastructure. Operators are facing the challenge to match the demand by continuously expanding and upgrading the network infrastructure. However, the evolution of the customer's demand is uncertain. We introduce a novel (long-term) network planning approach based on multistage stochastic programming, where demand evolution is considered as a stochastic process and the network is extended as to maximize the expected profit. The approach proves capable of designing large-scale realistic UMTS networks with a time-horizon of several years. Our mathematical optimization model, the solution approach, and computational results are presented in this paper. Springer 18 Computational Management Science 9 3 303 321 10.1007/s10287-012-0143-5 Mathematical Optimization
OPUS4-3323 Konferenzveröffentlichung Eisenblätter, Andreas; Geerdes, Hans-Florian; Gross, James; Puñal, Oscar; Schweiger, Jonas A Two-Stage Approach to WLAN Planning Avignon, France 2010 9 Proc. of the 8th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt’10) 232 241 Mathematical Optimization
OPUS4-3267 Konferenzveröffentlichung Martin, Alexander; Geißler, Björn; Heyn, Christine; Hiller, Benjamin; Humpola, Jesco; Koch, Thorsten; Lehmann, Thomas; Morsi, Antonio; Pfetsch, Marc; Schewe, Lars; Schmidt, Martin; Schultz, Rüdiger; Schwarz, Robert; Schweiger, Jonas; Steinbach, Marc; Willert, Bernhard Optimierung Technischer Kapazitäten in Gasnetzen VDI-Verlag, Düsseldorf 2011 9 Optimierung in der Energiewirtschaft 105 114 Mathematical Optimization
OPUS4-4718 Wissenschaftlicher Artikel Pfetsch, Marc. E; Fügenschuh, Armin; Geißler, Björn; Geißler, Nina; Gollmer, Ralf; Hiller, Benjamin; Humpola, Jesco; Koch, Thorsten; Lehmann, Thomas; Martin, Alexander; Morsi, Antonio; Rövekamp, Jessica; Schewe, Lars; Schmidt, Martin; Schultz, Rüdiger; Schwarz, Robert; Schweiger, Jonas; Stangl, Claudia; Steinbach, Marc C.; Vigerske, Stefan; Willert, Bernhard M. Validation of Nominations in Gas Network Optimization: Models, Methods, and Solutions 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 feasibility problem. The first phase consists of four distinct algorithms applying linear, and methods for complementarity constraints to compute possible settings for the discrete decisions. The second phase employs a precise continuous programming model of the gas network. Using this setup, we are able to compute high quality solutions to real-world industrial instances that are significantly larger than networks that have appeared in the mathematical programming literature before. Taylor & Francis Optimization Methods and Software 10.1080/10556788.2014.888426 Mathematical Optimization
OPUS4-4738 Wissenschaftlicher Artikel Fügenschuh, Armin; Geißler, Björn; Gollmer, Ralf; Hayn, Christine; Henrion, René; Hiller, Benjamin; Humpola, Jesco; Koch, Thorsten; Lehmann, Thomas; Martin, Alexander; Mirkov, Radoslava; Morsi, Antonio; Römisch, Werner; Rövekamp, Jessica; Schewe, Lars; Schmidt, Martin; Schultz, Rüdiger; Schwarz, Robert; Schweiger, Jonas; Stangl, Claudia; Steinbach, Marc C.; Willert, Bernhard M. Mathematical optimization for challenging network planning problems in unbundled liberalized gas markets 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 were 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 discuss how these changing paradigms lead to new and challenging mathematical optimization problems. This includes the validation of nominations, that asks for the decision if the network's capacity is sufficient to transport a specific amount of flow, the verification of booked capacities and the detection of available freely allocable capacities, and the topological extension of the network with new pipelines or compressors in order to increase its capacity. In order to solve each of these problems and to provide meaningful results for the practice, a mixture of different mathematical aspects have to be addressed, such as combinatorics, stochasticity, uncertainty, and nonlinearity. Currently, no numerical solver is available that can deal with such blended problems out-of-the-box. The main goal of our research is to develop such a solver, that moreover is able to solve instances of realistic size. In this article, we describe the main ingredients of our prototypical software implementations. Berlin Springer Berlin Heidelberg 24 Energy Systems 5 3 449 473 10.1007/s12667-013-0099-8 Mathematical Optimization
OPUS4-6193 misc Hiller, Benjamin; Koch, Thorsten; Schewe, Lars; Schwarz, Robert; Schweiger, Jonas A System to Evaluate Gas Network Capacities: Concepts and Implementation 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. urn:nbn:de:0297-zib-61931 Mathematical Optimization
OPUS4-5103 misc Schweiger, Jonas Gas network extension planning for multiple demand scenarios Today's gas markets demand more flexibility from the network operators which in turn have to invest into their network infrastructure. As these investments are very cost-intensive and long-living, network extensions should not only focus on one bottleneck scenario, but should increase the flexibility to fulfill different demand scenarios. We formulate a model for the network extension problem for multiple demand scenarios and propose a scenario decomposition. We solve MINLP single-scenario sub-problems and obtain valid bounds even without solving them to optimality. Heuristics prove capable of improving the initial solutions substantially. Results of computational experiments are presented. urn:nbn:de:0297-zib-51030 Mathematical Optimization
OPUS4-6947 misc Schweiger, Jonas Exploiting structure in non-convex quadratic optimization 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 poses principal difficulties. This paper summarizes the dissertation of Jonas Schweiger for the occasion of the GOR dissertation award 2018. We focus on the work on non-convex quadratic programs and show how problem specific structure can be used to obtain tight relaxations and speed up Branch&Bound methods. Both a classic general QP and the Pooling Problem as an important practical application serve as showcases. urn:nbn:de:0297-zib-69476 Mathematical Optimization
OPUS4-6691 Dissertation Schweiger, Jonas Exploiting structure in non-convex quadratic optimization and gas network planning under uncertainty 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. 411 Mathematical Optimization
OPUS4-6693 Wissenschaftlicher Artikel Schweiger, Jonas; Liers, Frauke A Decomposition Approach for Optimal Gas Network Extension with a Finite Set of Demand Scenarios Today's gas markets demand more flexibility from the network operators which in turn have to invest into their network infrastructure. As these investments are very cost-intensive and long-living, network extensions should not only focus on a single bottleneck scenario, but should increase the flexibility to fulfill different demand scenarios. In this work, we formulate a model for the network extension problem for multiple demand scenarios and propose a scenario decomposition in order to solve the arising challenging optimization tasks. In fact, each subproblem consists of a mixed-integer nonlinear optimization problem (MINLP). Valid bounds on the objective value are derived even without solving the subproblems to optimality. Furthermore, we develop heuristics that prove capable of improving the initial solutions substantially. Results of computational experiments on realistic network topologies are presented. It turns out that our method is able to solve these challenging instances to optimality within a reasonable amount of time. Springer 29 Optimization and Engineering 19 2 297 326 Mathematical Optimization
OPUS4-6780 misc Luedtke, James; D'Ambrosio, Claudia; Linderoth, Jeff; Schweiger, Jonas Strong Convex Nonlinear Relaxations of the Pooling Problem: Extreme Points We investigate new convex relaxations for the pooling problem, a classic nonconvex production planning problem in which products are mixed in intermediate pools in order to meet quality targets at their destinations. In this technical report, we characterize the extreme points of the convex hull of our non-convex set, and show that they are not finite, i.e., the convex hull is not polyhedral. This analysis was used to derive valid nonlinear convex inequalities and show that, for a specific case, they characterize the convex hull of our set. The new valid inequalities and computational results are presented in ZIB Report 18-12. urn:nbn:de:0297-zib-67801 Mathematical Optimization
OPUS4-6782 misc Luedtke, James; D'Ambrosio, Claudia; Linderoth, Jeff; Schweiger, Jonas Strong Convex Nonlinear Relaxations of the Pooling Problem We investigate new convex relaxations for the pooling problem, a classic nonconvex production planning problem in which input materials are mixed in intermediate pools, with the outputs of these pools further mixed to make output products meeting given attribute percentage requirements. Our relaxations are derived by considering a set which arises from the formulation by considering a single product, a single attibute, and a single pool. The convex hull of the resulting nonconvex set is not polyhedral. We derive valid linear and convex nonlinear inequalities for the convex hull, and demonstrate that different subsets of these inequalities define the convex hull of the nonconvex set in three cases determined by the parameters of the set. Computational results on literature instances and newly created larger test instances demonstrate that the inequalities can significantly strengthen the convex relaxation of the pq-formulation of the pooling problem, which is the relaxation known to have the strongest bound. urn:nbn:de:0297-zib-67824 Mathematical Optimization
OPUS4-6743 misc Hiller, Benjamin; Koch, Thorsten; Schewe, Lars; Schwarz, Robert; Schweiger, Jonas A System to Evaluate Gas Network Capacities: Concepts and Implementation In 2005 the European Union liberalized the gas market with a disruptive change and decoupled trading of natural gas from its transport. The gas is now transported by independent 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 the maximum possible capacities at each entry and exit such that any resulting gas flow can be realized by the network. The revenue from selling these capacities more than one billion Euro in Germany alone, but overestimating the capacity might compromise the security of supply. Therefore, evaluating the available transport capacities is extremely important to the TSOs. This is a report on a large project in mathematical optimization, set out to develop a new toolset for evaluating gas network capacities. The goals and the challenges as they occurred in the project are described, as well as the developments and design decisions taken to meet the requirements. urn:nbn:de:0297-zib-67438 Mathematical Optimization
OPUS4-6730 Wissenschaftlicher Artikel Hiller, Benjamin; Koch, Thorsten; Schewe, Lars; Schwarz, Robert; Schweiger, Jonas A System to Evaluate Gas Network Capacities: Concepts and Implementation In 2005 the European Union liberalized the gas market with a disruptive change and decoupled trading of natural gas from its transport. The gas is now trans- ported by independent 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 the maximum possible capacities at each entry and exit such that any resulting gas flow can be realized by the network. The revenue from selling these capacities more than one billion Euro in Germany alone, but overestimating the capacity might compromise the security of supply. Therefore, evaluating the available transport capacities is extremely important to the TSOs. This is a report on a large project in mathematical optimization, set out to develop a new toolset for evaluating gas network capacities. The goals and the challenges as they occurred in the project are described, as well as the developments and design decisions taken to meet the requirements. 11 European Journal of Operational Research 270 3 797 808 Mathematical Optimization
OPUS4-5349 Teil eines Buches Hiller, Benjamin; Humpola, Jesco; Lehmann, Thomas; Lenz, Ralf; Morsi, Antonio; Pfetsch, Marc E.; Schewe, Lars; Schmidt, Martin; Schwarz, Robert; Schweiger, Jonas; Stangl, Claudia; Willert, Bernhard M. Computational results for validation of nominations 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. Evaluating Gas Network Capacities SIAM-MOS series on Optimization 9781611973686 Mathematical Optimization
OPUS4-5345 Teil eines Buches Humpola, Jesco; Fügenschuh, Armin; Hiller, Benjamin; Koch, Thorsten; Lehmann, Thomas; Lenz, Ralf; Schwarz, Robert; Schweiger, Jonas The Specialized MINLP Approach 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. Evaluating Gas Network Capacities SIAM-MOS series on Optimization 9781611973686 Mathematical Optimization
OPUS4-5497 Teil eines Buches Hayn, Christine; Humpola, Jesco; Koch, Thorsten; Schewe, Lars; Schweiger, Jonas; Spreckelsen, Klaus Perspectives After we discussed approaches to validate nominations and to verify bookings, we consider possible future research paths. This includes determining technical capacities and planning of network extensions. Evaluating Gas Network Capacities SIAM-MOS series on Optimization 9781611973686 Mathematical Optimization