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 OPUS4-1777 misc Humpola, Jesco; Fügenschuh, Armin A New Class of Valid Inequalities for Nonlinear Network Design Problems 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. 2013 urn:nbn:de:0297-zib-17771 10.1007/s00291-015-0390-2 Mathematical Optimization OPUS4-4718 Wissenschaftlicher Artikel Pfetsch, Marc; 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; Vigerske, Stefan; Willert, Bernhard 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 2014 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; Willert, Bernhard 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 2013 24 Energy Systems 5 3 449 473 10.1007/s12667-013-0099-8 Mathematical Optimization OPUS4-5812 Wissenschaftlicher Artikel Borndörfer, Ralf; Fügenschuh, Armin; Klug, Torsten; Schang, Thilo; Schlechte, Thomas; Schülldorf, Hanno The Freight Train Routing Problem for Congested Railway Networks with Mixed Traffic We consider the following freight train routing problem (FTRP). Given is a transportation network with fixed routes for passenger trains and a set of freight trains (requests), each defined by an origin and destination station pair. The objective is to calculate a feasible route for each freight train such that the sum of all expected delays and all running times is minimal. Previous research concentrated on microscopic train routings for junctions or inside major stations. Only recently approaches were developed to tackle larger corridors or even networks. We investigate the routing problem from a strategic perspective, calculating the routes in a macroscopic transportation network of Deutsche Bahn AG. In this context, macroscopic refers to an aggregation of complex and large real-world structures into fewer network elements. Moreover, the departure and arrival times of freight trains are approximated. The problem has a strategic character since it asks only for a coarse routing through the network without the precise timings. We provide a mixed-integer nonlinear programming (MINLP) formulation for the FTRP, which is a multicommodity flow model on a time-expanded graph with additional routing constraints. The model's nonlinearities originate from an algebraic approximation of the delays of the trains on the arcs of the network by capacity restraint functions. The MINLP is reduced to a mixed-integer linear model (MILP) by piecewise linear approximation. The latter is solved by a state-of-the art MILP solver for various real-world test instances. 2016 15 Transportation Science 50 2 408 423 10.1287/trsc.2015.0656 Mathematical Optimization OPUS4-4815 misc Vierhaus, Ingmar; Fügenschuh, Armin; Gottwald, Robert Lion; Grösser, Stefan N. Modern Nonlinear Optimization Techniques for an Optimal Control of System Dynamics Models We study System Dynamics models with several free parameters that can be altered by the user. We assume that the user's goal is to achieve a certain dynamic behavior of the model by varying these parameters. In order to the find best possible combination of parameter settings, several automatic parameter tuning methods are described in the literature and readily available within existing System Dynamic software packages. We give a survey on the available techniques in the market and describe their theoretical background. Some of these methods are already six decades old, and meanwhile newer and more powerful optimization methods have emerged in the mathematical literature. One major obstacle for their direct use are tabled data in System Dynamics models, which are usually interpreted as piecewise linear functions. However, modern optimization methods usually require smooth functions which are twice continuously differentiable. We overcome this problem by a smooth spline interpolation of the tabled data. We use a test set of three complex System Dynamic models from the literature, describe their individual transition into optimization problems, and demonstrate the applicability of modern optimization algorithms to these System Dynamics Optimization problems. 2014 urn:nbn:de:0297-zib-48159 Mathematical Optimization OPUS4-4816 Konferenzveröffentlichung Brose, Achim; Fügenschuh, Armin; Gausemeier, Pia; Vierhaus, Ingmar; Seliger, Günther A System Dynamic Enhancement for the Scenario Technique The Scenario Technique is a strategic planning method that aims to describe and analyze potential developments of a considered system in the future. Its application consists of several steps, from an initial problem analysis over an influence analysis to projections of key factors and a definition of the scenarios to a final interpretation of the results. The technique itself combines qualitative and quantitative methods and is an enhancement of the standard Scenario Technique. We use the numerical values gathered during the influence analysis, and embed them in a System Dynamics framework. This yields a mathematically rigorous way to achieve predictions of the system's future behavior from an initial impulse and the feedback structure of the factors. The outcome of our new method is a further way of projecting the present into the future, which enables the user of the Scenario Technique to obtain a validation of the results achieved by the standard method. Berlin Universitätsverlag der TU Berlin 2013 5 Proc. 11th Global Conference on Sustainable Manufacturing 561 566 Mathematical Optimization OPUS4-4817 Konferenzveröffentlichung Scheumann, René; Vierhaus, Ingmar; Chang, Ya-Ju; Fügenschuh, Armin; Finkbeiner, Matthias Identification of trade-offs for sustainable manufacturing of a Bamboo Bike by System Dynamics We develop a generic System Dynamic model to simulate the production, machines, employees, waste, and capital flows of a manufacturing company. In a second step, this model is specialised by defining suit-able input data to represent a bicycle manufacturing company in a developing country. We monitor a set of sustainability indicators to understand the social, environmental and economic impact of the company, and to estimate managerial decisions to be taken in order to improve on these criteria. We show that the social and environmental situation can be improved over time without sacrificing the economic success of the company's business. 2013 8 Proceedings of the 27. Conference on Environmental Informatics - Informatics for Environmental Protection, Sustainable Development and Risk Management 523 531 Mathematical Optimization OPUS4-4822 Konferenzveröffentlichung Fügenschuh, Armin; van Veldhuizen, Roel; Vierhaus, Ingmar Production Planning for Non-Cooperating Companies with Nonlinear Optimization We consider a production planning problem where two competing companies are selling their items on a common market. Moreover, the raw material used in the production is a limited non-renewable resource. The revenue per item sold depends on the total amount of items produced by both players. If they collaborate they could apply a production strategy that leads to the highest combined revenue. Usually the formation of such syndicates is prohibited by law; hence we assume that one company does not know how much the other company will produce. We formulate the problem for company A to find an optimal production plan without information on the strategy of company B as a nonlinear mathematical optimization problem. In its naive formulation the model is too large, making its solution practically impossible. After a reformulation we find a much smaller model, which we solve by spatial branch-and-cut methods and linear programming. We discuss the practical implications of our solutions. Berlin Universitätsverlag der TU Berlin 2013 5 11th Global Conference on Sustainable Manufacturing : Proceedings 536 541 Mathematical Optimization OPUS4-4823 Konferenzveröffentlichung Fügenschuh, Armin; Vierhaus, Ingmar System Dynamic Optimization in the Sustainability Assessment of a World-Model The System Dynamics (SD) methodology is a framework for modeling and simulating the dynamic behavior of socioeconomic systems. Characteristic for the description of such systems is the occurrence of feedback loops together with stocks and flows. The mathematical equations that describe the system are usually nonlinear. Therefore seemingly simple systems can show a nonintuitive, nonpredictable behavior over time. Controlling a dynamical system means to define a desired final state in which the system should be, and to specify potential interventions from outside that should keep the system on the right track. The central question is how to compute such globally optimal control for a given SD model. We propose a branch-and-bound approach that is based on a bound propagation method, primal heuristics, and spatial branching. We apply our new SD-control method to a small System Dynamics model, that describes the evolution of a social-economic system over time. We examine the problem of steering this system on a sustainable consumption path. Berlin Universitätsverlag der TU Berlin 2013 5 11th Global Conference on Sustainable Manufacturing : Proceedings 530 535 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. 2011 5 International Conference on the European Energy Market (EEM) 346 351 10.1109/EEM.2011.5953035 Mathematical Optimization