@article{EisenblaetterGeerdesKochetal.2005, author = {Eisenbl{\"a}tter, Andreas and Geerdes, Hans-Florian and Koch, Thorsten and Martin, Alexander and Wess{\"a}ly, Roland}, title = {UMTS Radio Network Evaluation and Optimization beyond Snapshots}, volume = {63}, journal = {Mathematical Methods of Operations Research}, number = {1}, doi = {10.1007/s00186-005-0002-z}, pages = {1 -- 29}, year = {2005}, language = {en} } @article{BleyKoch2000, author = {Bley, Andreas and Koch, Thorsten}, title = {Optimierung des G-WiN}, journal = {DFN-Mitteilungen}, number = {54}, pages = {13 -- 15}, year = {2000}, language = {en} } @article{AbboudGroetschelKoch2008, author = {Abboud, Nadine and Gr{\"o}tschel, Martin and Koch, Thorsten}, title = {Mathematical methods for physical layout of printed circuit boards: an overview}, volume = {30}, journal = {OR Spectrum}, number = {3}, doi = {10.1007/s00291-007-0080-9}, pages = {453 -- 468}, year = {2008}, language = {en} } @article{AchterbergGroetschelKoch2006, author = {Achterberg, Tobias and Gr{\"o}tschel, Martin and Koch, Thorsten}, title = {Teaching MIP Modeling and Solving}, volume = {33}, journal = {OR/MS Today}, number = {6}, pages = {14 -- 15}, year = {2006}, language = {en} } @misc{FuegenschuhHillerHumpolaetal.2011, author = {F{\"u}genschuh, Armin and Hiller, Benjamin and Humpola, Jesco and Koch, Thorsten and Lehmann, Thomas and Schwarz, Robert and Schweiger, Jonas and Szab{\´o}, J{\´a}cint}, title = {Gas Network Topology Optimization for Upcoming Market Requirements}, doi = {10.1109/EEM.2011.5953035}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-12348}, number = {11-09}, year = {2011}, abstract = {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.}, language = {en} } @misc{BleyKochNiu2008, author = {Bley, Andreas and Koch, Thorsten and Niu, Lingfeng}, title = {Experiments with nonlinear extensions to SCIP}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-8300}, number = {08-28}, year = {2008}, abstract = {This paper describes several experiments to explore the options for solving a class of mixed integer nonlinear programming problems that stem from a real-world mine production planning project. The only type of nonlinear constraints in these problems are bilinear equalities involving continuous variables, which enforce the ratios between elements in mixed material streams. A branch-and-bound algorithm to handle the integer variables has been tried in another project. However, this branch-and-bound algorithm is not effective for handling the nonlinear constraints. Therefore state-of-the-art nonlinear solvers are utilized to solve the resulting nonlinear subproblems in this work. The experiments were carried out using the NEOS server for optimization. After finding that current nonlinear programming solvers seem to lack suitable preprocessing capabilities, we preprocess the instances beforehand and use an heuristic approach to solve the nonlinear subproblems. In the appendix, we explain how to add a polynomial constraint handler that uses IPOPT as embedded nonlinear programming solver for the constraint programming framework SCIP. This is one of the crucial steps for implementing our algorithm in SCIP. We briefly described our approach and give an idea of the work involved.}, language = {en} } @incollection{EisenblaetterFuegenschuhKochetal.2002, author = {Eisenbl{\"a}tter, Andreas and F{\"u}genschuh, Armin and Koch, Thorsten and Koster, Arie M.C.A. and Martin, Alexander and Pfender, Tobias and Wegel, Oliver and Wess{\"a}ly, Roland}, title = {Mathematical Model of Feasible Network Configurations for UMTS}, booktitle = {Telecommunications network design and management}, editor = {G. Anandalingam, S.}, publisher = {Kluwer}, pages = {1 -- 24}, year = {2002}, language = {en} } @misc{EisenblaetterFuegenschuhGeerdesetal.2003, author = {Eisenbl{\"a}tter, Andreas and F{\"u}genschuh, Armin and Geerdes, Hans-Florian and Koch, Thorsten and T{\"u}rke, Ulrich and Meijerink, Ellen}, title = {XML Data Specification and Documentation}, publisher = {IST-2000-28088 MOMENTUM Technical Report}, year = {2003}, language = {en} } @inproceedings{EisenblaetterFuegenschuhGeerdesetal.2004, author = {Eisenbl{\"a}tter, Andreas and F{\"u}genschuh, Armin and Geerdes, Hans-Florian and Junglas, Daniel and Koch, Thorsten and Martin, Alexander}, title = {Integer Programming Methods for UMTS Radio Network Planning}, booktitle = {Proceedings of the WiOpt'04, Cambridge, UK}, year = {2004}, language = {en} } @misc{ShinanoAchterbergBertholdetal.2010, author = {Shinano, Yuji and Achterberg, Tobias and Berthold, Timo and Heinz, Stefan and Koch, Thorsten}, title = {ParaSCIP - a parallel extension of SCIP}, doi = {10.1007/978-3-642-24025-6_12}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-11921}, number = {10-27}, year = {2010}, abstract = {Mixed integer programming (MIP) has become one of the most important techniques in Operations Research and Discrete Optimization. SCIP (Solving Constraint Integer Programs) is currently one of the fastest non-commercial MIP solvers. It is based on the branch-and-bound procedure in which the problem is recursively split into smaller subproblems, thereby creating a so-called branching tree. We present ParaSCIP, an extension of SCIP, which realizes a parallelization on a distributed memory computing environment. ParaSCIP uses SCIP solvers as independently running processes to solve subproblems (nodes of the branching tree) locally. This makes the parallelization development independent of the SCIP development. Thus, ParaSCIP directly profits from any algorithmic progress in future versions of SCIP. Using a first implementation of ParaSCIP, we were able to solve two previously unsolved instances from MIPLIB2003, a standard test set library for MIP solvers. For these computations, we used up to 2048 cores of the HLRN~II supercomputer.}, language = {en} } @article{PfetschFuegenschuhGeissleretal.2014, 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}, journal = {Optimization Methods and Software}, publisher = {Taylor \& Francis}, doi = {10.1080/10556788.2014.888426}, year = {2014}, 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 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.}, language = {en} } @inproceedings{FuegenschuhHillerHumpolaetal.2011, author = {F{\"u}genschuh, Armin and Hiller, Benjamin and Humpola, Jesco and Koch, Thorsten and Lehmann, Thomas and Schwarz, Robert and Schweiger, Jonas and Szabo, Jacint}, title = {Gas Network Topology Optimization for Upcoming Market Requirements}, booktitle = {International Conference on the European Energy Market (EEM)}, doi = {10.1109/EEM.2011.5953035}, pages = {346 -- 351}, year = {2011}, abstract = {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.}, language = {en} } @inproceedings{BertholdGleixnerHeinzetal.2012, author = {Berthold, Timo and Gleixner, Ambros and Heinz, Stefan and Koch, Thorsten and Shinano, Yuji}, title = {SCIP Optimization Suite を利用した 混合整数(線形/非線形) 計画問題の解法}, booktitle = {Proceedings of the 24th RAMP symposium. The Operations Society of Japan, RAMP: Research Association of Mathematical Programming}, pages = {165 -- 192}, year = {2012}, abstract = {この論文ではソフトウェア・パッケージSCIP Optimization Suite を紹介し,その3つの構成要素:モデリン グ言語Zimpl, 線形計画(LP: linear programming) ソルバSoPlex, そして,制約整数計画(CIP: constraint integer programming) に対するソフトウェア・フレームワークSCIP, について述べる.本論文では,この3つの 構成要素を利用して,どのようにして挑戦的な混合整数線形計画問題(MIP: mixed integer linear optimization problems) や混合整数非線形計画問題(MINLP: mixed integer nonlinear optimization problems) をモデル化 し解くのかを説明する.SCIP は,現在,最も高速なMIP,MINLP ソルバの1つである.いくつかの例により, Zimpl, SCIP, SoPlex の利用方法を示すとともに,利用可能なインタフェースの概要を示す.最後に,将来の開 発計画の概要について述べる.}, language = {ja} } @article{FuegenschuhGeisslerGollmeretal.2013, author = {F{\"u}genschuh, Armin and Geißler, Bj{\"o}rn and Gollmer, Ralf and Hayn, Christine and Henrion, Ren{\´e} 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}, volume = {5}, journal = {Energy Systems}, number = {3}, publisher = {Springer Berlin Heidelberg}, address = {Berlin}, doi = {10.1007/s12667-013-0099-8}, pages = {449 -- 473}, 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 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.}, language = {en} } @article{HoangKoch2012, author = {Hoang, Nam-Dung and Koch, Thorsten}, title = {Steiner tree packing revisited}, volume = {76}, journal = {Mathematical Methods of Operations Research}, number = {1}, doi = {10.1007/s00186-012-0391-8}, pages = {95 -- 123}, year = {2012}, abstract = {The Steiner tree packing problem (STPP) in graphs is a long studied problem in combinatorial optimization. In contrast to many other problems, where there have been tremendous advances in practical problem solving, STPP remains very difficult. Most heuristics schemes are ineffective and even finding feasible solutions is already NP-hard. What makes this problem special is that in order to reach the overall optimal solution non-optimal solutions to the underlying NP-hard Steiner tree problems must be used. Any non-global approach to the STPP is likely to fail. Integer programming is currently the best approach for computing optimal solutions. In this paper we review some "classical" STPP instances which model the underlying real world application only in a reduced form. Through improved modelling, including some new cutting planes, and by emplyoing recent advances in solver technology we are for the first time able to solve those instances in the original 3D grid graphs to optimimality.}, language = {en} } @incollection{BorndoerferHoangKarbsteinetal.2013, author = {Bornd{\"o}rfer, Ralf and Hoang, Nam-Dung and Karbstein, Marika and Koch, Thorsten and Martin, Alexander}, title = {How many Steiner terminals can you connect in 20 years?}, booktitle = {Facets of Combinatorial Optimization; Festschrift for Martin Gr{\"o}tschel}, editor = {J{\"u}nger, Michael and Reinelt, Gerhard}, publisher = {Springer}, doi = {10.1007/978-3-642-38189-8_10}, pages = {215 -- 244}, year = {2013}, language = {en} } @misc{ShinanoAchterbergBertholdetal.2013, author = {Shinano, Yuji and Achterberg, Tobias and Berthold, Timo and Heinz, Stefan and Koch, Thorsten and Winkler, Michael}, title = {Solving hard MIPLIB2003 problems with ParaSCIP on Supercomputers: An update}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-42888}, year = {2013}, abstract = {Contemporary supercomputers can easily provide years of CPU time per wall-clock hour. One challenge of today's software development is how to harness this wast computing power in order to solve really hard mixed integer programming instances. In 2010, two out of six open MIPLIB2003 instances could be solved by ParaSCIP in more than ten consecutive runs, restarting from checkpointing files. The contribution of this paper is threefold: For the first time, we present computational results of single runs for those two instances. Secondly, we provide new improved upper and lower bounds for all of the remaining four open MIPLIB2003 instances. Finally, we explain which new developments led to these results and discuss the current progress of ParaSCIP. Experiments were conducted on HLRNII, on HLRN III, and on the Titan supercomputer, using up to 35,200 cores.}, language = {en} } @misc{BorndoerferHoangKarbsteinetal.2013, author = {Bornd{\"o}rfer, Ralf and Hoang, Nam-Dung and Karbstein, Marika and Koch, Thorsten and Martin, Alexander}, title = {How Many Steiner Terminals Can You Connect in 20 Years?}, issn = {1438-0064}, doi = {10.1007/978-3-642-38189-8_10}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-42524}, year = {2013}, abstract = {Steiner trees are constructed to connect a set of terminal nodes in a graph. This basic version of the Steiner tree problem is idealized, but it can effectively guide the search for successful approaches to many relevant variants, from both a theoretical and a computational point of view. This article illustrates the theoretical and algorithmic progress on Steiner tree type problems on two examples, the Steiner connectivity and the Steiner tree packing problem.}, language = {en} } @article{HumpolaFuegenschuhKoch2016, author = {Humpola, Jesco and F{\"u}genschuh, Armin and Koch, Thorsten}, title = {Valid inequalities for the topology optimization problem in gas network design}, volume = {38}, journal = {OR Spectrum}, number = {3}, publisher = {Springer}, address = {Berlin Heidelberg}, doi = {https://doi.org/10.1007/s00291-015-0390-2}, pages = {597 -- 631}, year = {2016}, abstract = {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 Euro per km extending the European pipeline network is already a multi-billion Euro business. Therefore, automatic planning tools that support the decision process are desired. Unfortunately, current mathematical methods are not capable of solving the arising network design problems due to their size and complexity. In this article, we will show how to apply optimization methods that can converge to a proven global optimal solution. By introducing a new class of valid inequalities that improve the relaxation of our mixed-integer nonlinear programming model, we are able to speed up the necessary computations substantially.}, language = {en} } @misc{MaherFischerGallyetal.2017, author = {Maher, Stephen J. and Fischer, Tobias and Gally, Tristan and Gamrath, Gerald and Gleixner, Ambros and Gottwald, Robert Lion and Hendel, Gregor and Koch, Thorsten and L{\"u}bbecke, Marco and Miltenberger, Matthias and M{\"u}ller, Benjamin and Pfetsch, Marc and Puchert, Christian and Rehfeldt, Daniel and Schenker, Sebastian and Schwarz, Robert and Serrano, Felipe and Shinano, Yuji and Weninger, Dieter and Witt, Jonas T. and Witzig, Jakob}, title = {The SCIP Optimization Suite 4.0}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-62170}, year = {2017}, abstract = {The SCIP Optimization Suite is a powerful collection of optimization software that consists of the branch-cut-and-price framework and mixed-integer programming solver SCIP, the linear programming solver SoPlex, the modeling language Zimpl, the parallelization framework UG, and the generic branch-cut-and-price solver GCG. Additionally, it features the extensions SCIP-Jack for solving Steiner tree problems, PolySCIP for solving multi-objective problems, and SCIP-SDP for solving mixed-integer semidefinite programs. The SCIP Optimization Suite has been continuously developed and has now reached version 4.0. The goal of this report is to present the recent changes to the collection. We not only describe the theoretical basis, but focus on implementation aspects and their computational consequences.}, language = {en} }