@misc{FuegenschuhVierhaus2013, author = {F{\"u}genschuh, Armin and Vierhaus, Ingmar}, title = {A Global Approach to the Optimal Control of System Dynamics Models}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-18600}, year = {2013}, abstract = {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 ordinary differential equations and nonlinear algebraic constraints. Therefore seemingly simple systems can show a nonintuitive, unpredictable behavior over time. Controlling a dynamical system means to specify potential interventions from outside that should keep the system on the desired track, and to define an evaluation schema to compare different controls among each other, so that a "best" control can be defined in a meaningful way. The central question is how to compute such globally optimal control for a given SD model, that allows the transition of the system into a desired state with minimum effort. We propose a mixed-integer nonlinear programming (MINLP) reformulation of the System Dynamics Optimization (SDO) problem. MINLP problems can be solved by linear programming based branch-and-bound approach. We demonstrate that standard MINLP solvers are not able to solve SDO problem. To overcome this obstacle, we introduce a special-tailored bound propagation method. We apply our new method to a predator-prey model with additional hunting activity as control, and to a mini-world model with the consumption level as control. Numerical results for these test cases are presented.}, language = {en} } @misc{ScheumannVierhausChangetal.2013, author = {Scheumann, Ren{\´e} and Vierhaus, Ingmar and Chang, Ya-Ju and F{\"u}genschuh, Armin and Finkbeiner, Matthias}, title = {Identification of trade-offs for sustainable manufacturing of a Bamboo Bike by System Dynamics}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-18895}, year = {2013}, abstract = {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.}, language = {en} } @misc{HumpolaFuegenschuh2013, author = {Humpola, Jesco and F{\"u}genschuh, Armin}, title = {A New Class of Valid Inequalities for Nonlinear Network Design Problems}, issn = {1438-0064}, doi = {10.1007/s00291-015-0390-2}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-17771}, year = {2013}, abstract = {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.}, language = {en} } @inproceedings{FuegenschuhHomfeldMartin2007, author = {F{\"u}genschuh, Armin and Homfeld, Henning and Martin, Alexander}, title = {Leitwegeplanung}, booktitle = {Mathematik f{\"u}r Innovationen in Industrie und Dienstleistungen}, year = {2007}, language = {en} } @book{Fuegenschuh2005, author = {F{\"u}genschuh, Armin}, title = {The Integrated Optimization of School Starting Times and Public Bus Services}, publisher = {Logos Verlag Berlin}, year = {2005}, language = {en} } @misc{Fuegenschuh2000, type = {Master Thesis}, author = {F{\"u}genschuh, Armin}, title = {Zur Bergman-Vollst{\"a}ndigkeit hyperkonvexer Gebiete}, year = {2000}, language = {en} } @misc{FuegenschuhGeisslerGollmeretal.2013, author = {F{\"u}genschuh, Armin and Geißler, Bj{\"o}rn and Gollmer, Ralf and Hayn, Christine and Henrion, Rene and Hiller, Benjamin and Humpola, Jesco and Koch, Thorsten and Lehmann, Thomas and Martin, Alexander and Mirkov, Radoslava and Morsi, Antonio and R{\"o}misch, Werner and R{\"o}vekamp, Jessica and Schewe, Lars and Schmidt, Martin and Schultz, R{\"u}diger and Schwarz, Robert and Schweiger, Jonas and Stangl, Claudia and Steinbach, Marc and Willert, Bernhard}, title = {Mathematical Optimization for Challenging Network Planning Problems in Unbundled Liberalized Gas Markets}, issn = {1438-0064}, doi = {10.1007/s12667-013-0099-8}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-17821}, year = {2013}, abstract = {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.}, language = {en} } @misc{FuegenschuhVierhaus2013, author = {F{\"u}genschuh, Armin and Vierhaus, Ingmar}, title = {System Dynamic Optimization in the Sustainability Assessment of a World-Model}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-18148}, year = {2013}, abstract = {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.}, language = {en} } @misc{FuegenschuhvanVeldhuizenVierhaus2013, author = {F{\"u}genschuh, Armin and van Veldhuizen, Roel and Vierhaus, Ingmar}, title = {Production Planning for Non-Cooperating Companies with Nonlinear Optimization}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-18163}, year = {2013}, abstract = {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.}, language = {en} } @misc{PfetschFuegenschuhGeissleretal.2012, author = {Pfetsch, Marc and F{\"u}genschuh, Armin and Geißler, Bj{\"o}rn and Geißler, Nina and Gollmer, Ralf and Hiller, Benjamin and Humpola, Jesco and Koch, Thorsten and Lehmann, Thomas and Martin, Alexander and Morsi, Antonio and R{\"o}vekamp, Jessica and Schewe, Lars and Schmidt, Martin and Schultz, R{\"u}diger and Schwarz, Robert and Schweiger, Jonas and Stangl, Claudia and Steinbach, Marc and Vigerske, Stefan and Willert, Bernhard}, title = {Validation of Nominations in Gas Network Optimization: Models, Methods, and Solutions}, issn = {1438-0064}, doi = {10.1080/10556788.2014.888426}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-16531}, year = {2012}, abstract = {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.}, language = {en} } @misc{FuegenschuhHaynMichaels2012, author = {F{\"u}genschuh, Armin and Hayn, Christine and Michaels, Dennis}, title = {Mixed-Integer Linear Methods for Layout-Optimization of Screening Systems in Recovered Paper Production}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-16862}, year = {2012}, abstract = {The industrial treatment of waste paper in order to regain valuable fibers from which recovered paper can be produced, involves several steps of preparation. One important step is the separation of stickies that are normally attached to the paper. If not properly separated, remaining stickies reduce the quality of the recovered paper or even disrupt the production process. For the mechanical separation process of fibers from stickies a separator screen is used. This machine has one input feed and two output streams, called the accept and the reject. In the accept the fibers are concentrated, whereas the reject has a higher concentration of stickies. The machine can be controlled by setting its reject rate. But even when the reject rate is set properly, after just a single screening step, the accept still has too many stickies, or the reject too many fibers. To get a proper separation, several separators have to be assembled into a network. From a mathematical point of view this problem can be seen as a multi-commodity network flow design problem with a nonlinear, controllable distribution function at each node. We present a nonlinear mixed-integer programming model for the simultaneous selection of a subset of separators, the network's topology, and the optimal setting of each separator. Numerical results are obtained via different types of linearization of the nonlinearities and the use of mixed-integer linear solvers, and compared with state-of-the-art global optimization software.}, language = {en} } @misc{ScheumannFuegenschuhSchenkeretal.2012, author = {Scheumann, Rene and F{\"u}genschuh, Armin and Schenker, Sebastian and Vierhaus, Ingmar and Bornd{\"o}rfer, Ralf and Finkbeiner, Matthias}, title = {Global Manufacturing: How to Use Mathematical Optimisation Methods to Transform to Sustainable Value Creation}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-15703}, year = {2012}, abstract = {It is clear that a transformation to sustainable value creation is needed, because business as usual is not an option for preserving competitive advantages of leading industries. What does that mean? This contribution proposes possible approaches for a shift in existing manufacturing paradigms. In a first step, sustainability aspects from the German Sustainability Strategy and from the tools of life cycle sustainability assessment are chosen to match areas of a value creation process. Within these aspects are indicators, which can be measured within a manufacturing process. Once these data are obtained they can be used to set up a mathematical linear pulse model of manufacturing in order to analyse the evolution of the system over time, that is the transition process, by using a system dynamics approach. An increase of technology development by a factor of 2 leads to an increase of manufacturing but also to an increase of climate change. Compensation measures need to be taken. This can be done by e.g. taking money from the GDP (as an indicator of the aspect ``macroeconomic performance''). The value of the arc from that building block towards climate change must then be increased by a factor of 10. The choice of independent and representative indicators or aspects shall be validated and double-checked for their significance with the help of multi-criteria mixed-integer programming optimisation methods.}, language = {en} } @misc{FrankFuegenschuhHertyetal.2009, author = {Frank, Martin and F{\"u}genschuh, Armin and Herty, Michael and Schewe, Lars}, title = {The Coolest Path Problem}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-11571}, number = {09-37}, year = {2009}, abstract = {We introduce the coolest path problem, which is a mixture of two well-known problems from distinct mathematical fields. One of them is the shortest path problem from combinatorial optimization. The other is the heat conduction problem from the field of partial differential equations. Together, they make up a control problem, where some geometrical object traverses a digraph in an optimal way, with constraints on intermediate or the final state. We discuss some properties of the problem and present numerical solution techniques. We demonstrate that the problem can be formulated as a linear mixed-integer program. Numerical solutions can thus be achieved within one hour for instances with up to 70 nodes in the graph.}, language = {en} } @inproceedings{KlugJunoszaSzaniawskiKwasiborskietal.2015, author = {Klug, Torsten and Junosza-Szaniawski, Konstanty and Kwasiborski, Slawomir and F{\"u}genschuh, Armin and Schlechte, Thomas}, title = {Fastest, Average and Quantile Schedule}, booktitle = {SOFSEM 2015: Theory and Practice of Computer Science}, publisher = {Springer Berlin Heidelberg}, doi = {10.1007/978-3-662-46078-8_17}, pages = {201 -- 216}, year = {2015}, abstract = {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.}, language = {en} } @article{HumpolaLehmannFuegenschuh2015, author = {Humpola, Jesco and Lehmann, Thomas and F{\"u}genschuh, Armin}, title = {A primal heuristic for optimizing the topology of gas networks based on dual information}, volume = {3}, journal = {EURO Journal on Computational Optimization}, number = {1}, doi = {10.1007/s13675-014-0029-0}, pages = {53 -- 78}, year = {2015}, abstract = {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.}, language = {en} } @inproceedings{VierhausFuegenschuh2015, author = {Vierhaus, Ingmar and F{\"u}genschuh, Armin}, title = {Global and Local Optimal Control of a Resource Utilization Problem}, booktitle = {Proceedings of the 33rd International Conference of the System Dynamics Society}, year = {2015}, abstract = {System Dynamic models describe physical, technical, economical, or social systems using differential and algebraic equations. In their purest form, these models are intended to describe the evolution of a system from a given initial state. In many applications, it is possible to intervene with the system in order to obtain a desired dynamic or a certain outcome in the end. On the mathematical side, this leads to control problems, where aside from the simulation one has to find optimal intervention functions over time that maximize a specific objective function. Using a dynamical model for the utilization of a natural nonrenewable resource of Behrens as a demonstrator example, we present two main mathematical solution strategies. They are distinguished by the quality certificate on their respective solution: one leads to proven local optimal solution, and the other technique yields proven global optimal solutions. We present implementational and numerical issues, and a comparison of both methods.}, language = {en} } @phdthesis{Fuegenschuh2011, author = {F{\"u}genschuh, Armin}, title = {Computational aspects of time in scheduling and dynamic flow problems}, year = {2011}, language = {en} } @incollection{SchenkerVierhausBorndoerferetal.2017, author = {Schenker, Sebastian and Vierhaus, Ingmar and Bornd{\"o}rfer, Ralf and F{\"u}genschuh, Armin and Skutella, Martin}, title = {Optimisation Methods in Sustainable Manufacturing}, booktitle = {Sustainable Manufacturing}, editor = {Stark, Rainer and Seliger, G{\"u}nther and Bonvoisin, J{\´e}r{\´e}my}, publisher = {Springer International Publishing}, isbn = {978-3-319-48514-0}, doi = {10.1007/978-3-319-48514-0_15}, pages = {239 -- 253}, year = {2017}, abstract = {Sustainable manufacturing is driven by the insight that the focus on the economic dimension in current businesses and lifestyles has to be broadened to cover all three pillars of sustainability: economic development, social development, and environmental protection.}, language = {en} } @inproceedings{VierhausFuegenschuh2013, author = {Vierhaus, Ingmar and F{\"u}genschuh, Armin}, title = {A Global Approach to the Optimal Control of System Dynamics Models}, booktitle = {Proceedings of the 31st International Conference of the System Dynamics Society}, year = {2013}, abstract = {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 ordinary differential equations and nonlinear algebraic constraints. Seemingly simple systems can show a nonintuitive, unpredictable behavior over time. Controlling a dynamical system means to specify potential interventions from outside that should keep the system on the desired track, and to define an evaluation schema to compare different controls among each other, so that a ``best'' control can be defined in a meaningful way. The central question is how to compute such globally optimal control for a given SD model, that allows the transition of the system into a desired state with minimum effort. We propose a mixed-integer nonlinear programming (MINLP) reformulation of the System Dynamics Optimization (SDO) problem. MINLP problems can be solved by linear programming based branch-and-bound approach. We demonstrate that standard MINLP solvers are not able to solve SDO problem. To overcome this obstacle, we introduce a special-tailored bound propagation method. Numerical results for these test cases are presented.}, language = {en} } @inproceedings{VierhausFuegenschuhGottwaldetal.2014, author = {Vierhaus, Ingmar and F{\"u}genschuh, Armin and Gottwald, Robert Lion and Gr{\"o}sser, Stefan}, title = {Modern Nonlinear Optimization Techniques for an Optimal Control of System Dynamics Models}, booktitle = {Proceedings of the 32nd International Conference of the System Dynamics Society}, year = {2014}, abstract = {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 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.}, language = {en} }