@article{ShinanoAchterbergBertholdetal.2013, author = {Shinano, Yuji and Achterberg, Tobias and Berthold, Timo and Heinz, Stefan and Koch, Thorsten and Vigerske, Stefan and Winkler, Michael}, title = {制約整数計画ソルバ SCIP の並列化}, volume = {61}, journal = {統計数理}, number = {1}, pages = {47 -- 78}, year = {2013}, abstract = {制約整数計画(CIP: Constraint Integer Programs)は,制約プログラミング(CP: Constraint Programming),混合整数計画(MIP: Mixed Integer Programming),充足可能性問題(SAT: Satisfability Problem)の研究分野におけるモデリング技術と解法を統合している.その結果,制約整数計画は,広いクラスの最適化問題を扱うことができる.SCIP(Solving Constraint Integer Programs)は,CIP を解くソルバとして実装され,Zuse Institute Berlin(ZIB)の研究者を中心として継続的に拡張が続けられている.本論文では,著者らによって開発された SCIP に対する2 種類の並列化拡張を紹介する.一つは,複数計算ノード間で大規模に並列動作する ParaSCIPである.もう一つは,複数コアと共有メモリを持つ 1 台の計算機上で(スレッド)並列で動作する FiberSCIP である.ParaSCIP は,HLRN II スーパーコンピュータ上で,一つのインスタンスを解くために最大 7,168 コアを利用した動作実績がある.また,統計数理研究所の Fujitsu PRIMERGY RX200S5 上でも,最大 512 コアを利用した動作実績がある.統計数理研究所のFujitsu PRIMERGY RX200S5 上では,これまでに最適解が得られていなかった MIPLIB2010のインスタンスである dg012142 に最適解を与えた.}, language = {ja} } @misc{ShinanoAchterbergBertholdetal.2013, author = {Shinano, Yuji and Achterberg, Tobias and Berthold, Timo and Heinz, Stefan and Koch, Thorsten and Vigerske, Stefan and Winkler, Michael}, title = {制約整数計画ソルバ SCIP の並列化}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-18130}, year = {2013}, abstract = {制約整数計画(CIP: Constraint Integer Programming)は,制約プログラミング(CP: Constraint Programming),混合整数計画(MIP: Mixed Integer Programming), 充足可能性問題(SAT: Satisfiability Problems)の研究分野におけるモデリング技術と解法を統合している.その結果,制約整数計画は,広いクラスの最適化問題を扱うことができる.SCIP (Solving Constraint Integer Programs)は,CIPを解くソルバとして実装され,Zuse Institute Berlin (ZIB)の研究者を中心として継続的に拡張が続けられている.本論文では,著者らによって開発されたSCIP に対する2種類の並列化拡張を紹介する. 一つは,複数計算ノード間で大規模に並列動作するParaSCIP である. もう一つは,複数コアと共有メモリを持つ1台の計算機上で(スレッド)並列で動作するFiberSCIP である. ParaSCIP は,HLRN IIスーパーコンピュータ上で, 一つのインスタンスを解くために最大7,168 コアを利用した動作実績がある.また,統計数理研究所のFujitsu PRIMERGY RX200S5上でも,最大512コアを利用した動作実績がある.統計数理研究所のFujitsu PRIMERGY RX200S5上 では,これまでに最適解が得られていなかったMIPLIB2010のインスタンスであるdg012142に最適解を与えた.}, language = {ja} } @misc{ArnoldBertholdHeinzetal.2014, author = {Arnold, Thomas and Berthold, Timo and Heinz, Stefan and Vigerske, Stefan and Henrion, Ren{\´e} and Gr{\"o}tschel, Martin and Koch, Thorsten and Tischendorf, Caren and R{\"o}misch, Werner}, title = {A Jack of all Trades? Solving stochastic mixed-integer nonlinear constraint programs}, issn = {1438-0064}, doi = {10.4171/137}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-49947}, year = {2014}, abstract = {Natural gas is one of the most important energy sources in Germany and Europe. In recent years, political regulations have led to a strict separation of gas trading and gas transport, thereby assigning a central role in energy politics to the transportation and distribution of gas. These newly imposed political requirements influenced the technical processes of gas transport in such a way that the complex task of planning and operating gas networks has become even more intricate. Mathematically, the combination of discrete decisions on the configuration of a gas transport network, the nonlinear equations describing the physics of gas, and the uncertainty in demand and supply yield large-scale and highly complex stochastic mixed-integer nonlinear optimization problems. The Matheon project "Optimization of Gas Transport" takes the key role of making available the necessary core technology to solve the mathematical optimization problems which model the topology planning and the operation of gas networks. An important aspect of the academic impact is the free availability of our framework. As a result of several years of research and development, it is now possible to download a complete state-of-the-art framework for mixed-integer linear and nonlinear programming in source code at http://scip.zib.de}, language = {en} } @misc{ArnoldBertholdHeinzetal.2014, author = {Arnold, Thomas and Berthold, Timo and Heinz, Stefan and Vigerske, Stefan and Henrion, Ren{\´e} and Gr{\"o}tschel, Martin and Koch, Thorsten and Tischendorf, Caren and R{\"o}misch, Werner}, title = {A Jack of all Trades? Solving stochastic mixed-integer nonlinear constraint programs}, volume = {1}, journal = {MATHEON - Mathematics for Key Technologies}, editor = {Deuflhard, Peter and Gr{\"o}tschel, Martin and H{\"o}mberg, Dietmar and Horst, Ulrich and Kramer, J{\"u}rg and Mehrmann, Volker and Polthier, Konrad and Schmidt, Frank and Sch{\"u}tte, Christof and Skutella, Martin and Sprekels, J{\"u}rgen}, publisher = {European Mathematical Society}, doi = {10.4171/137}, pages = {135 -- 146}, year = {2014}, abstract = {Natural gas is one of the most important energy sources in Germany and Europe. In recent years, political regulations have led to a strict separation of gas trading and gas transport, thereby assigning a central role in energy politics to the transportation and distribution of gas. These newly imposed political requirements influenced the technical processes of gas transport in such a way that the complex task of planning and operating gas networks has become even more intricate. Mathematically, the combination of discrete decisions on the configuration of a gas transport network, the nonlinear equations describing the physics of gas, and the uncertainty in demand and supply yield large-scale and highly complex stochastic mixed-integer nonlinear optimization problems. The Matheon project "Optimization of Gas Transport" takes the key role of making available the necessary core technology to solve the mathematical optimization problems which model the topology planning and the operation of gas networks. An important aspect of the academic impact is the free availability of our framework. As a result of several years of research and development, it is now possible to download a complete state-of-the-art framework for mixed-integer linear and nonlinear programming in source code at http://scip.zib.de}, language = {en} } @inproceedings{AchterbergHeinzKoch2008, author = {Achterberg, Tobias and Heinz, Stefan and Koch, Thorsten}, title = {Counting Solutions of Integer Programs Using Unrestricted Subtree Detection}, volume = {5015}, booktitle = {Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, 5th International Conference, CPAIOR 2008}, editor = {Perron, Laurent and Trick, Michael}, publisher = {Springer}, pages = {278 -- 282}, year = {2008}, language = {en} } @incollection{KochMartinVoss2001, author = {Koch, Thorsten and Martin, Alexander and Voß, Stefan}, title = {SteinLib: An Updated Library on Steiner Tree Problems in Graphs}, booktitle = {Steiner Trees in Industry}, editor = {Du, D.-Z. and Cheng, X.}, publisher = {Kluwer}, doi = {10.1007/978-1-4613-0255-1_9}, pages = {285 -- 325}, year = {2001}, language = {en} } @misc{AustConradRempelDegkwitzetal.2015, author = {Aust, Sonja and Conrad-Rempel, Steffi and Degkwitz, Andreas and Golz, Bettina and Hasler, Tim and Heiss, Alexandra and Keidel, Petra and Koch, Thorsten and Kuberek, Monika and Lill, Monika and Lohrum, Stefan and M{\"u}ller, Anja and Peters-Kottig, Wolfgang and Quitzsch, Nicole and Rusch, Beate and Schwidder, Jens and Sischke, Gabriele and Stanek, Ursula and Taylor, Viola and Weihe, Signe and Wyrwol, Christiane and Happel, Hans-Gerd}, title = {KOBV Jahresbericht 2013-2014}, volume = {2013-2014}, number = {2013-2014}, organization = {Kooperativer Bibliotheksverbund Berlin-Brandenburg (KOBV)}, issn = {0934-5892}, pages = {1 -- 56}, year = {2015}, abstract = {Der KOBV-Jahresbericht informiert r{\"u}ckblickend im 2-Jahres-Rhythmus {\"u}ber die bibliothekarisch-fachlichen Entwicklungen im Verbund und die Projekte des Kooperativen Bibliotheksverbunds Berlin-Brandenburg (KOBV).}, language = {de} } @misc{ChristofConradRempelDegkwitzetal.2017, author = {Christof, J{\"u}rgen and Conrad-Rempel, Steffi and Degkwitz, Andreas and Goltz-Fellgiebel, Julia Alexandra and Happel, Hans-Gerd and Hasler, Tim and Heiss, Alexandra and Kaminsky, Uta and Kant, Oliver and Kende, Jiř{\´i} and Koch, Thorsten and Kuberek, Monika and Lohrum, Stefan and M{\"u}ller, Anja and Mutter, Moritz and Peters-Kottig, Wolfgang and Quitzsch, Nicole and Rusch, Beate and Schwidder, Jens and Stanek, Ursula and Weihe, Signe and Zeyns, Andrea}, title = {KOBV Jahresbericht 2015-2016}, volume = {2015-2016}, number = {2015-2016}, organization = {Kooperativer Bibliotheksverbund Berlin-Brandenburg (KOBV)}, issn = {0934-5892}, pages = {1 -- 64}, year = {2017}, abstract = {Der KOBV-Jahresbericht informiert r{\"u}ckblickend im 2-Jahres-Rhythmus {\"u}ber die bibliothekarisch-fachlichen Entwicklungen im Verbund und die Projekte des Kooperativen Bibliotheksverbunds Berlin-Brandenburg (KOBV).}, language = {de} } @article{KochBernalNeiraChenetal.2025, author = {Koch, Thorsten and Bernal Neira, David E. and Chen, Ying and Cortiana, Giorgio and Egger, Daniel J. and Heese, Raoul and Hegade, Narendra N. and Gomez Cadavid, Alejandro and Huang, Rhea and Itoko, Toshinari and Kleinert, Thomas and Maciel Xavier, Pedro and Mohseni, Naeimeh and Montanez-Barrera, Jhon A. and Nakano, Koji and Nannicini, Giacomo and O'Meara, Corey and Pauckert, Justin and Proissl, Manuel and Ramesh, Anurag and Schicker, Maximilian and Shimada, Noriaki and Takeori, Mitsuharu and Valls, Victor and Van Bulck, David and Woerner, Stefan and Zoufal, Christa}, title = {Quantum Optimization Benchmark Library -- The Intractable Decathlon}, arxiv = {http://arxiv.org/abs/2504.03832}, year = {2025}, abstract = {Through recent progress in hardware development, quantum computers have advanced to the point where benchmarking of (heuristic) quantum algorithms at scale is within reach. Particularly in combinatorial optimization -- where most algorithms are heuristics -- it is key to empirically analyze their performance on hardware and track progress towards quantum advantage. To this extent, we present ten optimization problem classes that are difficult for existing classical algorithms and can (mostly) be linked to practically-relevant applications, with the goal to enable systematic, fair, and comparable benchmarks for quantum optimization methods. Further, we introduce the Quantum Optimization Benchmark Library (QOBLIB) where the problem instances and solution track records can be found. The individual properties of the problem classes vary in terms of objective and variable type, coefficient ranges, and density. Crucially, they all become challenging for established classical methods already at system sizes ranging from less than 100 to, at most, an order of 100,000 decision variables, allowing to approach them with today's quantum computers. We reference the results from state-of-the-art solvers for instances from all problem classes and demonstrate exemplary baseline results obtained with quantum solvers for selected problems. The baseline results illustrate a standardized form to present benchmarking solutions, which has been designed to ensure comparability of the used methods, reproducibility of the respective results, and trackability of algorithmic and hardware improvements over time. We encourage the optimization community to explore the performance of available classical or quantum algorithms and hardware platforms with the benchmarking problem instances presented in this work toward demonstrating quantum advantage in optimization.}, language = {en} } @misc{GamrathAndersonBestuzhevaetal.2020, author = {Gamrath, Gerald and Anderson, Daniel and Bestuzheva, Ksenia and Chen, Wei-Kun and Eifler, Leon and Gasse, Maxime and Gemander, Patrick and Gleixner, Ambros and Gottwald, Leona and Halbig, Katrin and Hendel, Gregor and Hojny, Christopher and Koch, Thorsten and Le Bodic, Pierre and Maher, Stephen J. and Matter, Frederic and Miltenberger, Matthias and M{\"u}hmer, Erik and M{\"u}ller, Benjamin and Pfetsch, Marc and Schl{\"o}sser, Franziska and Serrano, Felipe and Shinano, Yuji and Tawfik, Christine and Vigerske, Stefan and Wegscheider, Fabian and Weninger, Dieter and Witzig, Jakob}, title = {The SCIP Optimization Suite 7.0}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-78023}, year = {2020}, abstract = {The SCIP Optimization Suite provides a collection of software packages for mathematical optimization centered around the constraint integer programming frame- work SCIP. This paper discusses enhancements and extensions contained in version 7.0 of the SCIP Optimization Suite. The new version features the parallel presolving library PaPILO as a new addition to the suite. PaPILO 1.0 simplifies mixed-integer linear op- timization problems and can be used stand-alone or integrated into SCIP via a presolver plugin. SCIP 7.0 provides additional support for decomposition algorithms. Besides im- provements in the Benders' decomposition solver of SCIP, user-defined decomposition structures can be read, which are used by the automated Benders' decomposition solver and two primal heuristics. Additionally, SCIP 7.0 comes with a tree size estimation that is used to predict the completion of the overall solving process and potentially trigger restarts. Moreover, substantial performance improvements of the MIP core were achieved by new developments in presolving, primal heuristics, branching rules, conflict analysis, and symmetry handling. Last, not least, the report presents updates to other components and extensions of the SCIP Optimization Suite, in particular, the LP solver SoPlex and the mixed-integer semidefinite programming solver SCIP-SDP.}, language = {en} }