<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>9057</id>
    <completedYear/>
    <publishedYear>2013</publishedYear>
    <thesisYearAccepted/>
    <language>jpn</language>
    <pageFirst>47</pageFirst>
    <pageLast>78</pageLast>
    <pageNumber/>
    <edition/>
    <issue>1</issue>
    <volume>61</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="jpn">制約整数計画ソルバ SCIP の並列化</title>
    <abstract language="jpn">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．</abstract>
    <abstract language="eng">The paradigm of constraint integer programming (CIP) combines modeling and solving techniques from the fields of constraint programming (CP), mixed-integer programming (MIP) and　satisfability problem (SAT). This paradigm allows us to address a wide　range of optimization problems. SCIP is an implementation of the idea of CIP and is now being continuously extended by a group of researchers centered at Zuse Institute Berlin (ZIB). This paper introduces two parallel extensions of SCIP. One is ParaSCIP, which is intended to run on a large scale distributed memory computing environment, and the other is FiberSCIP, intended to run on a shared memory computing environment. ParaSCIP has been run successfully on the HLRN II supercomputer utilizing up to 7,168 cores to solve a single difficult MIP. It has also been tested on an ISM supercomputer (Fujitsu PRIMERGY RX200S5 using up to 512 cores). The previously unsolved instance dg012142 from MIPLIB2010 was solved by using the ISM supercomputer.</abstract>
    <parentTitle language="jpn">統計数理</parentTitle>
    <identifier type="url">https://www.ism.ac.jp/editsec/toukei/pdf/61-1-047.pdf</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="SubmissionStatus">in press</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Yuji Shinano</author>
    <submitter>Yuji Shinano</submitter>
    <author>Tobias Achterberg</author>
    <author>Timo Berthold</author>
    <author>Stefan Heinz</author>
    <author>Thorsten Koch</author>
    <author>Stefan Vigerske</author>
    <author>Michael Winkler</author>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="projects" number="MODAL-SynLab">MODAL-SynLab</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>1813</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>jpn</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2013-04-22</completedDate>
    <publishedDate>2013-04-22</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="jpn">制約整数計画ソルバ SCIP の並列化</title>
    <title language="eng">Parallelizing the Constraint Integer Programming Solver SCIP</title>
    <abstract language="jpn">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．</abstract>
    <abstract language="eng">The paradigm of Constraint Integer Programming (CIP) combines modeling and solving techniques from the fields of Constraint Programming (CP), Mixed Integer Programming (MIP) and Satisfiability Problems (SAT). The paradigm allows us to address a wide range of optimization problems. SCIP is an implementation of the idea of CIP and is now continuously extended by a group of researchers centered at Zuse Institute Berlin (ZIB). This paper introduces two parallel extensions of SCIP. One is ParaSCIP, which is intended to run on a large scale distributed memory computing environment, and the other is FiberSCIP, intended to run on shared memory computing environments. ParaSCIP has successfully been run on the HLRN II supercomputer utilizing up to 7,168 cores to solve a single difficult MIP. It has also been tested on an ISM supercomputer (Fujitsu PRIMERGY RX200S5 using up to 512 cores). The previously unsolved instance dg012142 from MIPLIB2010 was solved by using the ISM supercomputer.</abstract>
    <additionalTitle language="eng">Parallelizing the Constraint Integer Programming Solver SCIP</additionalTitle>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-18130</identifier>
    <author>Yuji Shinano</author>
    <submitter>Yuji Shinano</submitter>
    <author>Tobias Achterberg</author>
    <author>Timo Berthold</author>
    <author>Stefan Heinz</author>
    <author>Thorsten Koch</author>
    <author>Stefan Vigerske</author>
    <author>Michael Winkler</author>
    <series>
      <title>ZIB-Report</title>
      <number>13-22</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mixed Integer Programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Constraint Integer Programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Parallel Computing</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Distributed Memory</value>
    </subject>
    <collection role="msc" number="68W10">Parallel algorithms</collection>
    <collection role="msc" number="90C11">Mixed integer programming</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="achterberg">Achterberg, Tobias</collection>
    <collection role="persons" number="berthold">Berthold, Timo</collection>
    <collection role="persons" number="heinz">Heinz, Stefan</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="persons" number="vigerske">Vigerske, Stefan</collection>
    <collection role="persons" number="michael.winkler">Winkler, Michael</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/1813/para-scip.pdf</file>
  </doc>
  <doc>
    <id>4994</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2014-05-13</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A Jack of all Trades? Solving stochastic mixed-integer nonlinear constraint programs</title>
    <abstract language="eng">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.&#13;
&#13;
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.&#13;
&#13;
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</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-49947</identifier>
    <identifier type="doi">10.4171/137</identifier>
    <enrichment key="SourceTitle">Appeared in: Matheon - Mathematics for Key Technologies. EMS 2014, pp. 135-146</enrichment>
    <author>Thomas Arnold</author>
    <submitter>Timo Berthold</submitter>
    <author>Timo Berthold</author>
    <author>Stefan Heinz</author>
    <author>Stefan Vigerske</author>
    <author>René Henrion</author>
    <author>Martin Grötschel</author>
    <author>Thorsten Koch</author>
    <author>Caren Tischendorf</author>
    <author>Werner Römisch</author>
    <series>
      <title>ZIB-Report</title>
      <number>14-14</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>gas transport optimization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>mixed integer nonlinear programming</value>
    </subject>
    <collection role="msc" number="90C11">Mixed integer programming</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/4994/B-koch-thorsten.pdf</file>
  </doc>
  <doc>
    <id>5080</id>
    <completedYear/>
    <publishedYear>2014</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>135</pageFirst>
    <pageLast>146</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>1</volume>
    <type>incollection</type>
    <publisherName>European Mathematical Society</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A Jack of all Trades? Solving stochastic mixed-integer nonlinear constraint programs</title>
    <abstract language="eng">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</abstract>
    <parentTitle language="eng">MATHEON - Mathematics for Key Technologies</parentTitle>
    <identifier type="doi">10.4171/137</identifier>
    <enrichment key="Series">EMS Series in Industrial and Applied Mathematics</enrichment>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="PreprintUrn">urn:nbn:de:0297-zib-49947</enrichment>
    <editor>Peter Deuflhard</editor>
    <author>Thomas Arnold</author>
    <submitter>Bettina Kasse</submitter>
    <editor>Martin Grötschel</editor>
    <author>Timo Berthold</author>
    <editor>Dietmar Hömberg</editor>
    <author>Stefan Heinz</author>
    <editor>Ulrich Horst</editor>
    <author>Stefan Vigerske</author>
    <editor>Jürg Kramer</editor>
    <author>René Henrion</author>
    <author>Martin Grötschel</author>
    <editor>Volker Mehrmann</editor>
    <author>Thorsten Koch</author>
    <editor>Konrad Polthier</editor>
    <author>Caren Tischendorf</author>
    <editor>Frank Schmidt</editor>
    <author>Werner Römisch</author>
    <editor>Christof Schütte</editor>
    <editor>Martin Skutella</editor>
    <editor>Jürgen Sprekels</editor>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="institutes" number="mip">Mathematical Optimization Methods</collection>
    <collection role="persons" number="berthold">Berthold, Timo</collection>
    <collection role="persons" number="groetschel">Grötschel, Martin</collection>
    <collection role="persons" number="heinz">Heinz, Stefan</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="vigerske">Vigerske, Stefan</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>3260</id>
    <completedYear>2008</completedYear>
    <publishedYear>2008</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>278</pageFirst>
    <pageLast>282</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>5015</volume>
    <type>conferenceobject</type>
    <publisherName>Springer</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Counting Solutions of Integer Programs Using Unrestricted Subtree Detection</title>
    <parentTitle language="eng">Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, 5th International Conference, CPAIOR 2008</parentTitle>
    <identifier type="url">http://opus.kobv.de/zib/volltexte/2008/1092/</identifier>
    <enrichment key="Series">Lecture Notes in Computer Science</enrichment>
    <enrichment key="PreprintUrn">urn:nbn:de:0297-zib-10632</enrichment>
    <author>Tobias Achterberg</author>
    <editor>Laurent Perron</editor>
    <author>Stefan Heinz</author>
    <editor>Michael Trick</editor>
    <author>Thorsten Koch</author>
    <collection role="institutes" number="mip">Mathematical Optimization Methods</collection>
    <collection role="persons" number="achterberg">Achterberg, Tobias</collection>
    <collection role="persons" number="heinz">Heinz, Stefan</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="projects" number="VeriCount">VeriCount</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>3242</id>
    <completedYear>2001</completedYear>
    <publishedYear>2001</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>285</pageFirst>
    <pageLast>325</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>bookpart</type>
    <publisherName>Kluwer</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">SteinLib: An Updated Library on Steiner Tree Problems in Graphs</title>
    <parentTitle language="eng">Steiner Trees in Industry</parentTitle>
    <identifier type="doi">10.1007/978-1-4613-0255-1_9</identifier>
    <enrichment key="PreprintUrn">urn:nbn:de:0297-zib-6056</enrichment>
    <author>Thorsten Koch</author>
    <editor>D.-Z. Du</editor>
    <author>Alexander Martin</author>
    <editor>X. Cheng</editor>
    <author>Stefan Voß</author>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
  </doc>
  <doc>
    <id>7485</id>
    <completedYear/>
    <publishedYear>2015</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>1</pageFirst>
    <pageLast>56</pageLast>
    <pageNumber>56</pageNumber>
    <edition/>
    <issue>2013-2014</issue>
    <volume>2013-2014</volume>
    <type>annualzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation>Kooperativer Bibliotheksverbund Berlin-Brandenburg (KOBV)</creatingCorporation>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">KOBV Jahresbericht 2013-2014</title>
    <abstract language="deu">Der KOBV-Jahresbericht informiert rückblickend im 2-Jahres-Rhythmus über die bibliothekarisch-fachlichen Entwicklungen im Verbund und die Projekte des Kooperativen Bibliotheksverbunds Berlin-Brandenburg (KOBV).</abstract>
    <identifier type="issn">0934-5892</identifier>
    <licence>Creative Commons - CC BY-ND - Namensnennung - Keine Bearbeitungen 4.0 International</licence>
    <author>Sonja Aust</author>
    <submitter>Hanna Jansen</submitter>
    <author>Steffi Conrad-Rempel</author>
    <author>Andreas Degkwitz</author>
    <author>Bettina Golz</author>
    <author>Tim Hasler</author>
    <author>Alexandra Heiss</author>
    <author>Petra Keidel</author>
    <author>Thorsten Koch</author>
    <author>Monika Kuberek</author>
    <author>Monika Lill</author>
    <author>Stefan Lohrum</author>
    <author>Anja Müller</author>
    <author>Wolfgang Peters-Kottig</author>
    <author>Nicole Quitzsch</author>
    <author>Beate Rusch</author>
    <author>Jens Schwidder</author>
    <author>Gabriele Sischke</author>
    <author>Ursula Stanek</author>
    <author>Viola Taylor</author>
    <author>Signe Weihe</author>
    <author>Christiane Wyrwol</author>
    <author>Hans-Gerd Happel</author>
    <series>
      <title>KOBV-Jahresbericht</title>
      <number>2013-2014</number>
    </series>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>KOBV</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Jahresbericht</value>
    </subject>
    <collection role="institutes" number="">KOBV</collection>
    <collection role="persons" number="conrad-rempel">Conrad-Rempel, Steffi</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="lohrum">Lohrum, Stefan</collection>
    <collection role="persons" number="anja.mueller">Müller, Anja</collection>
    <collection role="persons" number="heidingsfelder">Heidingsfelder, Nicole</collection>
    <collection role="persons" number="rusch">Rusch, Beate</collection>
    <collection role="persons" number="schwidder">Schwidder, Jens</collection>
    <collection role="persons" number="weihe">Weihe, Signe</collection>
    <collection role="projects" number="KOBV">KOBV</collection>
    <thesisPublisher>Zuse Institute Berlin (ZIB)</thesisPublisher>
  </doc>
  <doc>
    <id>7486</id>
    <completedYear/>
    <publishedYear>2017</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>1</pageFirst>
    <pageLast>64</pageLast>
    <pageNumber>64</pageNumber>
    <edition/>
    <issue>2015-2016</issue>
    <volume>2015-2016</volume>
    <type>annualzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation>Kooperativer Bibliotheksverbund Berlin-Brandenburg (KOBV)</creatingCorporation>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">KOBV Jahresbericht 2015-2016</title>
    <abstract language="deu">Der KOBV-Jahresbericht informiert rückblickend im 2-Jahres-Rhythmus über die bibliothekarisch-fachlichen Entwicklungen im Verbund und die Projekte des Kooperativen Bibliotheksverbunds Berlin-Brandenburg (KOBV).</abstract>
    <identifier type="issn">0934-5892</identifier>
    <licence>Creative Commons - CC BY-ND - Namensnennung - Keine Bearbeitungen 4.0 International</licence>
    <author>Jürgen Christof</author>
    <submitter>Hanna Jansen</submitter>
    <author>Steffi Conrad-Rempel</author>
    <author>Andreas Degkwitz</author>
    <author>Julia Alexandra Goltz-Fellgiebel</author>
    <author>Hans-Gerd Happel</author>
    <author>Tim Hasler</author>
    <author>Alexandra Heiss</author>
    <author>Uta Kaminsky</author>
    <author>Oliver Kant</author>
    <author>Jiří Kende</author>
    <author>Thorsten Koch</author>
    <author>Monika Kuberek</author>
    <author>Stefan Lohrum</author>
    <author>Anja Müller</author>
    <author>Moritz Mutter</author>
    <author>Wolfgang Peters-Kottig</author>
    <author>Nicole Quitzsch</author>
    <author>Beate Rusch</author>
    <author>Jens Schwidder</author>
    <author>Ursula Stanek</author>
    <author>Signe Weihe</author>
    <author>Andrea Zeyns</author>
    <series>
      <title>KOBV-Jahresbericht</title>
      <number>2015-2016</number>
    </series>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>KOBV</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Jahresbericht</value>
    </subject>
    <collection role="institutes" number="">KOBV</collection>
    <collection role="persons" number="conrad-rempel">Conrad-Rempel, Steffi</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="lohrum">Lohrum, Stefan</collection>
    <collection role="persons" number="heidingsfelder">Heidingsfelder, Nicole</collection>
    <collection role="persons" number="rusch">Rusch, Beate</collection>
    <collection role="persons" number="schwidder">Schwidder, Jens</collection>
    <collection role="persons" number="weihe">Weihe, Signe</collection>
    <collection role="projects" number="KOBV">KOBV</collection>
    <thesisPublisher>Zuse Institute Berlin (ZIB)</thesisPublisher>
  </doc>
  <doc>
    <id>9998</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Quantum Optimization Benchmark Library -- The Intractable Decathlon</title>
    <abstract language="eng">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.</abstract>
    <identifier type="arxiv">2504.03832</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="SubmissionStatus">under review</enrichment>
    <author>Thorsten Koch</author>
    <submitter>Janina Zittel</submitter>
    <author>David E. Bernal Neira</author>
    <author>Ying Chen</author>
    <author>Giorgio Cortiana</author>
    <author>Daniel J. Egger</author>
    <author>Raoul Heese</author>
    <author>Narendra N. Hegade</author>
    <author>Alejandro Gomez Cadavid</author>
    <author>Rhea Huang</author>
    <author>Toshinari Itoko</author>
    <author>Thomas Kleinert</author>
    <author>Pedro Maciel Xavier</author>
    <author>Naeimeh Mohseni</author>
    <author>Jhon A. Montanez-Barrera</author>
    <author>Koji Nakano</author>
    <author>Giacomo Nannicini</author>
    <author>Corey O'Meara</author>
    <author>Justin Pauckert</author>
    <author>Manuel Proissl</author>
    <author>Anurag Ramesh</author>
    <author>Maximilian Schicker</author>
    <author>Noriaki Shimada</author>
    <author>Mitsuharu Takeori</author>
    <author>Victor Valls</author>
    <author>David Van Bulck</author>
    <author>Stefan Woerner</author>
    <author>Christa Zoufal</author>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="projects" number="MODAL-EnergyLab">MODAL-EnergyLab</collection>
    <collection role="persons" number="schicker">Schicker, Maximilian</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>7802</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2020-03-30</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">The SCIP Optimization Suite 7.0</title>
    <abstract language="eng">The SCIP Optimization Suite provides a collection of software packages for&#13;
mathematical optimization centered around the constraint integer programming frame-&#13;
work SCIP. This paper discusses enhancements and extensions contained in version 7.0&#13;
of the SCIP Optimization Suite. The new version features the parallel presolving library&#13;
PaPILO as a new addition to the suite. PaPILO 1.0 simplifies mixed-integer linear op-&#13;
timization problems and can be used stand-alone or integrated into SCIP via a presolver&#13;
plugin. SCIP 7.0 provides additional support for decomposition algorithms. Besides im-&#13;
provements in the Benders’ decomposition solver of SCIP, user-defined decomposition&#13;
structures can be read, which are used by the automated Benders’ decomposition solver&#13;
and two primal heuristics. Additionally, SCIP 7.0 comes with a tree size estimation&#13;
that is used to predict the completion of the overall solving process and potentially&#13;
trigger restarts. Moreover, substantial performance improvements of the MIP core were&#13;
achieved by new developments in presolving, primal heuristics, branching rules, conflict&#13;
analysis, and symmetry handling. Last, not least, the report presents updates to other&#13;
components and extensions of the SCIP Optimization Suite, in particular, the LP solver&#13;
SoPlex and the mixed-integer semidefinite programming solver SCIP-SDP.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-78023</identifier>
    <author>Gerald Gamrath</author>
    <submitter>Felipe Serrano</submitter>
    <author>Daniel Anderson</author>
    <author>Ksenia Bestuzheva</author>
    <author>Wei-Kun Chen</author>
    <author>Leon Eifler</author>
    <author>Maxime Gasse</author>
    <author>Patrick Gemander</author>
    <author>Ambros Gleixner</author>
    <author>Leona Gottwald</author>
    <author>Katrin Halbig</author>
    <author>Gregor Hendel</author>
    <author>Christopher Hojny</author>
    <author>Thorsten Koch</author>
    <author>Pierre Le Bodic</author>
    <author>Stephen J. Maher</author>
    <author>Frederic Matter</author>
    <author>Matthias Miltenberger</author>
    <author>Erik Mühmer</author>
    <author>Benjamin Müller</author>
    <author>Marc Pfetsch</author>
    <author>Franziska Schlösser</author>
    <author>Felipe Serrano</author>
    <author>Yuji Shinano</author>
    <author>Christine Tawfik</author>
    <author>Stefan Vigerske</author>
    <author>Fabian Wegscheider</author>
    <author>Dieter Weninger</author>
    <author>Jakob Witzig</author>
    <series>
      <title>ZIB-Report</title>
      <number>20-10</number>
    </series>
    <collection role="msc" number="65-XX">NUMERICAL ANALYSIS</collection>
    <collection role="msc" number="90-XX">OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="institutes" number="mip">Mathematical Optimization Methods</collection>
    <collection role="persons" number="gamrath">Gamrath, Gerald</collection>
    <collection role="persons" number="robert.gottwald">Gottwald, Robert</collection>
    <collection role="persons" number="hendel">Hendel, Gregor</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="miltenberger">Miltenberger, Matthias</collection>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="persons" number="vigerske">Vigerske, Stefan</collection>
    <collection role="projects" number="ASTfSCM">ASTfSCM</collection>
    <collection role="projects" number="MIP-ZIBOPT">MIP-ZIBOPT</collection>
    <collection role="projects" number="MODAL-SynLab">MODAL-SynLab</collection>
    <collection role="projects" number="Siemens">Siemens</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="persons" number="schloesser">Schlösser, Franziska</collection>
    <collection role="persons" number="bestuzheva">Bestuzheva, Ksenia</collection>
    <collection role="projects" number="plan4res">Plan4res</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/7802/scipopt-70.pdf</file>
  </doc>
  <doc>
    <id>9828</id>
    <completedYear/>
    <publishedYear>2024</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>718</pageFirst>
    <pageLast>735</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>6</volume>
    <type>article</type>
    <publisherName>Springer Science and Business Media LLC</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2024-10-28</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Challenges and opportunities in quantum optimization</title>
    <parentTitle language="eng">Nature Reviews Physics</parentTitle>
    <identifier type="doi">10.1038/s42254-024-00770-9</identifier>
    <identifier type="issn">2522-5820</identifier>
    <identifier type="arxiv">2312.02279</identifier>
    <enrichment key="opus_doi_flag">true</enrichment>
    <enrichment key="opus_crossrefDocumentType">journal-article</enrichment>
    <enrichment key="opus_crossrefLicence">https://www.springernature.com/gp/researchers/text-and-data-mining</enrichment>
    <enrichment key="opus_import_origin">crossref</enrichment>
    <enrichment key="opus_doiImportPopulated">PersonAuthorFirstName_1,PersonAuthorLastName_1,PersonAuthorIdentifierOrcid_1,PersonAuthorFirstName_2,PersonAuthorLastName_2,PersonAuthorFirstName_3,PersonAuthorLastName_3,PersonAuthorFirstName_4,PersonAuthorLastName_4,PersonAuthorIdentifierOrcid_4,PersonAuthorFirstName_5,PersonAuthorLastName_5,PersonAuthorFirstName_6,PersonAuthorLastName_6,PersonAuthorIdentifierOrcid_6,PersonAuthorFirstName_7,PersonAuthorLastName_7,PersonAuthorIdentifierOrcid_7,PersonAuthorFirstName_8,PersonAuthorLastName_8,PersonAuthorIdentifierOrcid_8,PersonAuthorFirstName_9,PersonAuthorLastName_9,PersonAuthorIdentifierOrcid_9,PersonAuthorFirstName_10,PersonAuthorLastName_10,PersonAuthorFirstName_11,PersonAuthorLastName_11,PersonAuthorIdentifierOrcid_11,PersonAuthorFirstName_12,PersonAuthorLastName_12,PersonAuthorIdentifierOrcid_12,PersonAuthorFirstName_13,PersonAuthorLastName_13,PersonAuthorIdentifierOrcid_13,PersonAuthorFirstName_14,PersonAuthorLastName_14,PersonAuthorIdentifierOrcid_14,PersonAuthorFirstName_15,PersonAuthorLastName_15,PersonAuthorFirstName_16,PersonAuthorLastName_16,PersonAuthorIdentifierOrcid_16,PersonAuthorFirstName_17,PersonAuthorLastName_17,PersonAuthorFirstName_18,PersonAuthorLastName_18,PersonAuthorIdentifierOrcid_18,PersonAuthorFirstName_19,PersonAuthorLastName_19,PersonAuthorIdentifierOrcid_19,PersonAuthorFirstName_20,PersonAuthorLastName_20,PersonAuthorIdentifierOrcid_20,PersonAuthorFirstName_21,PersonAuthorLastName_21,PersonAuthorIdentifierOrcid_21,PersonAuthorFirstName_22,PersonAuthorLastName_22,PersonAuthorIdentifierOrcid_22,PersonAuthorFirstName_23,PersonAuthorLastName_23,PersonAuthorIdentifierOrcid_23,PersonAuthorFirstName_24,PersonAuthorLastName_24,PersonAuthorIdentifierOrcid_24,PersonAuthorFirstName_25,PersonAuthorLastName_25,PersonAuthorIdentifierOrcid_25,PersonAuthorFirstName_26,PersonAuthorLastName_26,PersonAuthorFirstName_27,PersonAuthorLastName_27,PersonAuthorIdentifierOrcid_27,PersonAuthorFirstName_28,PersonAuthorLastName_28,PersonAuthorIdentifierOrcid_28,PersonAuthorFirstName_29,PersonAuthorLastName_29,PersonAuthorIdentifierOrcid_29,PersonAuthorFirstName_30,PersonAuthorLastName_30,PersonAuthorIdentifierOrcid_30,PersonAuthorFirstName_31,PersonAuthorLastName_31,PersonAuthorIdentifierOrcid_31,PersonAuthorFirstName_32,PersonAuthorLastName_32,PersonAuthorFirstName_33,PersonAuthorLastName_33,PersonAuthorIdentifierOrcid_33,PersonAuthorFirstName_34,PersonAuthorLastName_34,PersonAuthorIdentifierOrcid_34,PersonAuthorFirstName_35,PersonAuthorLastName_35,PersonAuthorFirstName_36,PersonAuthorLastName_36,PersonAuthorIdentifierOrcid_36,PersonAuthorFirstName_37,PersonAuthorLastName_37,PersonAuthorIdentifierOrcid_37,PersonAuthorFirstName_38,PersonAuthorLastName_38,PersonAuthorIdentifierOrcid_38,PersonAuthorFirstName_39,PersonAuthorLastName_39,PersonAuthorFirstName_40,PersonAuthorLastName_40,PersonAuthorFirstName_41,PersonAuthorLastName_41,PersonAuthorFirstName_42,PersonAuthorLastName_42,PersonAuthorFirstName_43,PersonAuthorLastName_43,PersonAuthorIdentifierOrcid_43,PersonAuthorFirstName_44,PersonAuthorLastName_44,PersonAuthorFirstName_45,PersonAuthorLastName_45,PersonAuthorIdentifierOrcid_45,PersonAuthorFirstName_46,PersonAuthorLastName_46,PersonAuthorIdentifierOrcid_46,PublisherName,TitleMain_1,Language,TitleParent_1,PublishedYear,IdentifierIssn,Enrichmentopus_crossrefLicence</enrichment>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="opus.source">doi-import</enrichment>
    <author>Amira Abbas</author>
    <submitter>Janina Zittel</submitter>
    <author>Andris Ambainis</author>
    <author>Brandon Augustino</author>
    <author>Andreas Bärtschi</author>
    <author>Harry Buhrman</author>
    <author>Carleton Coffrin</author>
    <author>Giorgio Cortiana</author>
    <author>Vedran Dunjko</author>
    <author>Daniel J. Egger</author>
    <author>Bruce G. Elmegreen</author>
    <author>Nicola Franco</author>
    <author>Filippo Fratini</author>
    <author>Bryce Fuller</author>
    <author>Julien Gacon</author>
    <author>Constantin Gonciulea</author>
    <author>Sander Gribling</author>
    <author>Swati Gupta</author>
    <author>Stuart Hadfield</author>
    <author>Raoul Heese</author>
    <author>Gerhard Kircher</author>
    <author>Thomas Kleinert</author>
    <author>Thorsten Koch</author>
    <author>Georgios Korpas</author>
    <author>Steve Lenk</author>
    <author>Jakub Marecek</author>
    <author>Vanio Markov</author>
    <author>Guglielmo Mazzola</author>
    <author>Stefano Mensa</author>
    <author>Naeimeh Mohseni</author>
    <author>Giacomo Nannicini</author>
    <author>Corey O’Meara</author>
    <author>Elena Peña Tapia</author>
    <author>Sebastian Pokutta</author>
    <author>Manuel Proissl</author>
    <author>Patrick Rebentrost</author>
    <author>Emre Sahin</author>
    <author>Benjamin C. B. Symons</author>
    <author>Sabine Tornow</author>
    <author>Víctor Valls</author>
    <author>Stefan Woerner</author>
    <author>Mira L. Wolf-Bauwens</author>
    <author>Jon Yard</author>
    <author>Sheir Yarkoni</author>
    <author>Dirk Zechiel</author>
    <author>Sergiy Zhuk</author>
    <author>Christa Zoufal</author>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="pokutta">Pokutta, Sebastian</collection>
    <collection role="institutes" number="ais2t">AI in Society, Science, and Technology</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="projects" number="MODAL-EnergyLab">MODAL-EnergyLab</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>6629</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2017-12-21</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">The SCIP Optimization Suite 5.0</title>
    <abstract language="eng">This article describes new features and enhanced algorithms made available in version 5.0 of the SCIP Optimization Suite. In its central component, the constraint integer programming solver SCIP, remarkable performance improvements have been achieved for solving mixed-integer linear and nonlinear programs. On MIPs, SCIP 5.0 is about 41 % faster than SCIP 4.0 and over twice as fast on instances that take at least 100 seconds to solve. For MINLP, SCIP 5.0 is about 17 % faster overall and 23 % faster on instances that take at least 100 seconds to solve. This boost is due to algorithmic advances in several parts of the solver such as cutting plane generation and management, a new adaptive coordination of large neighborhood search heuristics, symmetry handling, and strengthened McCormick relaxations for bilinear terms in MINLPs. Besides discussing the theoretical background and the implementational aspects of these developments, the report describes recent additions for the other software packages connected to SCIP, in particular for the LP solver SoPlex, the Steiner tree solver SCIP-Jack, the MISDP solver SCIP-SDP, and the parallelization framework UG.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-66297</identifier>
    <author>Ambros Gleixner</author>
    <submitter>Gregor Hendel</submitter>
    <author>Leon Eifler</author>
    <author>Tristan Gally</author>
    <author>Gerald Gamrath</author>
    <author>Patrick Gemander</author>
    <author>Robert Lion Gottwald</author>
    <author>Gregor Hendel</author>
    <author>Christopher Hojny</author>
    <author>Thorsten Koch</author>
    <author>Matthias Miltenberger</author>
    <author>Benjamin Müller</author>
    <author>Marc Pfetsch</author>
    <author>Christian Puchert</author>
    <author>Daniel Rehfeldt</author>
    <author>Franziska Schlösser</author>
    <author>Felipe Serrano</author>
    <author>Yuji Shinano</author>
    <author>Jan Merlin Viernickel</author>
    <author>Stefan Vigerske</author>
    <author>Dieter Weninger</author>
    <author>Jonas T. Witt</author>
    <author>Jakob Witzig</author>
    <series>
      <title>ZIB-Report</title>
      <number>17-61</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>constraint integer programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>linear programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>mixed-integer linear programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>mixed-integer nonlinear programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>optimization solver</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>branch-and-cut</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>branch-and-price</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>column generation framework</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>parallelization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>mixed-integer semidefinite programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Steiner tree optimization</value>
    </subject>
    <collection role="msc" number="65-XX">NUMERICAL ANALYSIS</collection>
    <collection role="msc" number="90-XX">OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="institutes" number="mip">Mathematical Optimization Methods</collection>
    <collection role="persons" number="gamrath">Gamrath, Gerald</collection>
    <collection role="persons" number="robert.gottwald">Gottwald, Robert</collection>
    <collection role="persons" number="hendel">Hendel, Gregor</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="miltenberger">Miltenberger, Matthias</collection>
    <collection role="persons" number="rehfeldt">Rehfeldt, Daniel</collection>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="persons" number="vigerske">Vigerske, Stefan</collection>
    <collection role="projects" number="ASTfSCM">ASTfSCM</collection>
    <collection role="projects" number="MIP-ZIBOPT">MIP-ZIBOPT</collection>
    <collection role="projects" number="MODAL-SynLab">MODAL-SynLab</collection>
    <collection role="projects" number="Siemens">Siemens</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="persons" number="schloesser">Schlösser, Franziska</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/6629/scipopt-50.pdf</file>
  </doc>
  <doc>
    <id>5640</id>
    <completedYear/>
    <publishedYear>2015</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2015-10-27</completedDate>
    <publishedDate>2015-10-27</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Solving Open MIP Instances with ParaSCIP on Supercomputers using up to 80,000 Cores</title>
    <abstract language="eng">This paper describes how we solved 12 previously unsolved mixed-integer program-&#13;
ming (MIP) instances from the MIPLIB benchmark sets. To achieve these results we&#13;
used an enhanced version of ParaSCIP, setting a new record for the largest scale MIP&#13;
computation: up to 80,000 cores in parallel on the Titan supercomputer. In this paper&#13;
we describe the basic parallelization mechanism of ParaSCIP, improvements of the&#13;
dynamic load balancing and novel techniques to exploit the power of parallelization&#13;
for MIP solving. We give a detailed overview of computing times and statistics for&#13;
solving open MIPLIB instances.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-56404</identifier>
    <identifier type="doi">10.1109/IPDPS.2016.56</identifier>
    <enrichment key="SourceTitle">Appeared in: Proc. of 30th IEEE International Parallel &amp; Distributed Processing Symposium</enrichment>
    <submitter>Yuji Shinano</submitter>
    <author>Yuji Shinano</author>
    <author>Tobias Achterberg</author>
    <author>Timo Berthold</author>
    <author>Stefan Heinz</author>
    <author>Thorsten Koch</author>
    <author>Michael Winkler</author>
    <series>
      <title>ZIB-Report</title>
      <number>15-53</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mixed Integer Programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Parallel processing</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Node merging</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Racing ParaSCIP</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Ubiquity Generator Framework</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>MIPLIB</value>
    </subject>
    <collection role="ccs" number="D.">Software</collection>
    <collection role="ccs" number="I.">Computing Methodologies</collection>
    <collection role="msc" number="68-XX">COMPUTER SCIENCE (For papers involving machine computations and programs in a specific mathematical area, see Section -04 in that area)</collection>
    <collection role="msc" number="90-XX">OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="institutes" number="mip">Mathematical Optimization Methods</collection>
    <collection role="persons" number="achterberg">Achterberg, Tobias</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="projects" number="MIP-ZIBOPT">MIP-ZIBOPT</collection>
    <collection role="projects" number="MODAL-SynLab">MODAL-SynLab</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/5640/ZR-15-53.pdf</file>
    <file>https://opus4.kobv.de/opus4-zib/files/5640/ZR-15-53-rev.pdf</file>
  </doc>
  <doc>
    <id>4760</id>
    <completedYear>2012</completedYear>
    <publishedYear>2012</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>25</pageFirst>
    <pageLast>39</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Comparing MIQCP Solvers to a Specialised Algorithm for Mine Production Scheduling</title>
    <abstract language="eng">In this paper we investigate the performance of several out-of-the box solvers for mixed-integer quadratically constrained programmes (MIQCPs) on an open pit mine production scheduling problem with mixing constraints. We compare the solvers BARON, Couenne, SBB, and SCIP to a problem-specific algorithm on two different MIQCP formulations. The computational results presented show that general-purpose solvers with no particular knowledge of problem structure are able to nearly match the performance of a hand-crafted algorithm.</abstract>
    <parentTitle language="eng">Modeling, Simulation and Optimization of Complex Processes. Proceedings of the Fourth International Conference on High Performance Scientific Computing, March 2-6, 2009, Hanoi, Vietnam</parentTitle>
    <identifier type="doi">10.1007/978-3-642-25707-0_3</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="PreprintUrn">urn:nbn:de:0297-zib-11507</enrichment>
    <author>Andreas Bley</author>
    <submitter> Engel</submitter>
    <author>Ambros Gleixner</author>
    <author>Thorsten Koch</author>
    <author>Stefan Vigerske</author>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="vigerske">Vigerske, Stefan</collection>
    <collection role="projects" number="MATHEON-B20">MATHEON-B20</collection>
    <collection role="projects" number="MIP-ZIBOPT">MIP-ZIBOPT</collection>
    <collection role="projects" number="Siemens">Siemens</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>1150</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation>ZIB</creatingCorporation>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2009-10-15</completedDate>
    <publishedDate>2009-10-15</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Comparing MIQCP solvers to a specialised algorithm for mine production scheduling</title>
    <abstract language="eng">In this paper we investigate the performance of several out-of-the box solvers for mixed-integer quadratically constrained programmes (MIQCPs) on an open pit mine production scheduling problem with mixing constraints. We compare the solvers BARON, Couenne, SBB, and SCIP to a problem-specific algorithm on two different MIQCP formulations. The computational results presented show that general-purpose solvers with no particular knowledge of problem structure are able to nearly match the performance of a hand-crafted algorithm.</abstract>
    <identifier type="serial">09-32</identifier>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="opus3-id">1206</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-11507</identifier>
    <identifier type="doi">10.1007/978-3-642-25707-0</identifier>
    <enrichment key="SourceTitle">Appeared in: Modeling, Simulation and Optimization of Complex Processes, Proc. of the 4th Int. Conf. on High Performance Scientific Computing, 2009, Hanoi, Vietnam. H. G. Bock et al. (eds.) 2012, pp. 25-39</enrichment>
    <author>Andreas Bley</author>
    <submitter>unknown unknown</submitter>
    <author>Ambros Gleixner</author>
    <author>Thorsten Koch</author>
    <author>Stefan Vigerske</author>
    <series>
      <title>ZIB-Report</title>
      <number>09-32</number>
    </series>
    <collection role="ddc" number="000">Informatik, Informationswissenschaft, allgemeine Werke</collection>
    <collection role="msc" number="90B30">Production models</collection>
    <collection role="msc" number="90B35">Scheduling theory, deterministic [See also 68M20]</collection>
    <collection role="msc" number="90C11">Mixed integer programming</collection>
    <collection role="msc" number="90C26">Nonconvex programming, global optimization</collection>
    <collection role="msc" number="90C90">Applications of mathematical programming</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="vigerske">Vigerske, Stefan</collection>
    <collection role="projects" number="MATHEON-B19:MINLP">MATHEON-B19:MINLP</collection>
    <collection role="projects" number="MIP-ZIBOPT">MIP-ZIBOPT</collection>
    <collection role="projects" number="Siemens">Siemens</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/1150/ZR_09_32.pdf</file>
    <file>https://opus4.kobv.de/opus4-zib/files/1150/ZR_09_32.ps</file>
  </doc>
  <doc>
    <id>7839</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2020-05-28</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Solving Previously Unsolved MIP Instances with ParaSCIP on Supercomputers by using up to 80,000 Cores</title>
    <abstract language="deu">Mixed-integer programming (MIP) problem is arguably among the hardest classes of optimization problems. This paper describes how we solved 21 previously unsolved MIP instances from the MIPLIB benchmark sets. To achieve these results we used an enhanced version of ParaSCIP, setting a new record for the largest scale MIP computation: up to 80,000 cores in parallel on the Titan supercomputer. In this paper, we describe the basic parallelization mechanism of ParaSCIP, improvements of the dynamic load balancing and novel techniques to exploit the power of parallelization for MIP solving. We give a detailed overview of computing times and statistics for solving open MIPLIB instances.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-78393</identifier>
    <author>Yuji Shinano</author>
    <submitter>Yuji Shinano</submitter>
    <author>Tobias Achterberg</author>
    <author>Timo Berthold</author>
    <author>Stefan Heinz</author>
    <author>Thorsten Koch</author>
    <author>Michael Winkler</author>
    <series>
      <title>ZIB-Report</title>
      <number>20-16</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mixed Integer Programming, Parallel processing, Node merging, Racing, ParaSCIP,  Ubiquity Generator Framework, MIPLIB</value>
    </subject>
    <collection role="ccs" number="D.">Software</collection>
    <collection role="msc" number="68-XX">COMPUTER SCIENCE (For papers involving machine computations and programs in a specific mathematical area, see Section -04 in that area)</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="achterberg">Achterberg, Tobias</collection>
    <collection role="persons" number="berthold">Berthold, Timo</collection>
    <collection role="persons" number="heinz">Heinz, Stefan</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="persons" number="michael.winkler">Winkler, Michael</collection>
    <collection role="projects" number="MODAL-SynLab">MODAL-SynLab</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/7839/ZIB-Report_20-16.pdf</file>
  </doc>
  <doc>
    <id>8570</id>
    <completedYear/>
    <publishedYear>2021</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>113</pageFirst>
    <pageLast>116</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>9</volume>
    <type>other</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2021-04-09</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Synergistic approach of multi-energy models for a European optimal energy system management tool</title>
    <parentTitle language="eng">The Project Repository Journal</parentTitle>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="FulltextUrl">https://www.europeandissemination.eu/project-repository-journal-volume-9-april-2021/13570</enrichment>
    <author>Sandrine Charousset-Brignol</author>
    <submitter>Inci Yüksel-Ergün</submitter>
    <author>Wim van Ackooij</author>
    <author>Nadia Oudjane</author>
    <author>Dominique Daniel</author>
    <author>Slimane Noceir</author>
    <author>Utz-Uwe Haus</author>
    <author>Alfio Lazzaro</author>
    <author>Antonio Frangioni</author>
    <author>Rafael Lobato</author>
    <author>Ali Ghezelsoflu</author>
    <author>Niccolò Iardella</author>
    <author>Laura Galli</author>
    <author>Enrico Gorgone</author>
    <author>Mauro dell’Amico</author>
    <author>Spyros Giannelos</author>
    <author>Alex Moreira</author>
    <author>Goran Strbac</author>
    <author>Stefan Borozan</author>
    <author>Paula Falugi</author>
    <author>Danny Pudjianto</author>
    <author>Lothar Wyrwoll</author>
    <author>Carlo Schmitt</author>
    <author>Marco Franken</author>
    <author>Daniel Beulertz</author>
    <author>Henrik Schwaeppe</author>
    <author>Dieter Most</author>
    <author>Inci Yüksel-Ergün</author>
    <author>Janina Zittel</author>
    <author>Thorsten Koch</author>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="zittel">Zittel, Janina</collection>
    <collection role="persons" number="yueksel-erguen">Yüksel-Ergün, Inci</collection>
    <collection role="projects" number="plan4res">Plan4res</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>605</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2000-11-27</completedDate>
    <publishedDate>2000-11-27</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">SteinLib: An Updated Library on Steiner Tree Problems in Graphs</title>
    <abstract language="eng">In this paper we present the {\em SteinLib}, a library of data sets for the Steiner tree problem in graphs. This library extends former libraries on Steiner tree problems by many new interesting and difficult instances, most of them arising from real-world applications. We give a survey on the difficulty of these problem instances by giving references to state-of-the-art software packages that were the first or are currently among the best to solve these instances.</abstract>
    <identifier type="serial">00-37</identifier>
    <identifier type="opus3-id">606</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-6056</identifier>
    <enrichment key="SourceTitle">Appeared in: Steiner Trees in Industry. D.-Z. Du, X. Cheng (eds.) Kluwer 2001, pp. 285-325</enrichment>
    <author>Thorsten Koch</author>
    <author>Alexander Martin</author>
    <author>Stefan Voß</author>
    <series>
      <title>ZIB-Report</title>
      <number>00-37</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Steiner Trees</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mathematical Programming Testdata Library</value>
    </subject>
    <collection role="ddc" number="000">Informatik, Informationswissenschaft, allgemeine Werke</collection>
    <collection role="msc" number="90C10">Integer programming</collection>
    <collection role="msc" number="90C27">Combinatorial optimization</collection>
    <collection role="msc" number="90C35">Programming involving graphs or networks [See also 90C27]</collection>
    <collection role="institutes" number="">ZIB Allgemein</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/605/ZR-00-37.ps</file>
    <file>https://opus4.kobv.de/opus4-zib/files/605/ZR-00-37.pdf</file>
  </doc>
  <doc>
    <id>3606</id>
    <completedYear>2013</completedYear>
    <publishedYear>2013</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>249</pageFirst>
    <pageLast>256</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace>Sydney, Australia</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Visualizing Linear Neighborhoods in Non-Linear Vector Fields</title>
    <parentTitle language="eng">Proceedings of the IEEE Pacific Visualization Symposium</parentTitle>
    <enrichment key="PeerReviewed">yes</enrichment>
    <author>Stefan Koch</author>
    <author>Alexander Wiebel</author>
    <author>Jens Kasten</author>
    <author>Mario Hlawitschka</author>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="institutes" number="visalgo">Visual Data Analysis in Science and Engineering</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
  <doc>
    <id>3563</id>
    <completedYear>2004</completedYear>
    <publishedYear>2004</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>3277</pageFirst>
    <pageLast>3279</pageLast>
    <pageNumber/>
    <edition/>
    <issue>17</issue>
    <volume>20</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">PTGL - a web-based database application for protein topologies</title>
    <parentTitle language="eng">Bioinformatics</parentTitle>
    <identifier type="doi">10.1093/bioinformatics/bth367</identifier>
    <author>Patrick May</author>
    <author>Stefan Barthel</author>
    <author>Ina Koch</author>
    <collection role="institutes" number="vas">Distributed Algorithms and Supercomputing</collection>
  </doc>
  <doc>
    <id>3659</id>
    <completedYear>2011</completedYear>
    <publishedYear>2011</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>177</pageFirst>
    <pageLast>190</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>incollection</type>
    <publisherName>Springer</publisherName>
    <publisherPlace>Berlin</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Glyphs for Non-Linear Vector Field Singularities</title>
    <parentTitle language="eng">Topological Methods in Data Analysis and Visualization II</parentTitle>
    <enrichment key="Series">Mathematics and Visualization</enrichment>
    <enrichment key="PeerReviewed">yes</enrichment>
    <author>Alexander Wiebel</author>
    <editor>Ronald Peikert</editor>
    <author>Stefan Koch</author>
    <editor>Helwig Hauser</editor>
    <author>Gerik Scheuermann</author>
    <editor>Hamish Carr</editor>
    <editor>Raphael Fuchs</editor>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="institutes" number="visalgo">Visual Data Analysis in Science and Engineering</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
  <doc>
    <id>5172</id>
    <completedYear/>
    <publishedYear>2014</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>102</pageFirst>
    <pageLast>111</pageLast>
    <pageNumber/>
    <edition/>
    <issue>3</issue>
    <volume>2</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Investigation of the Ergopeptide Epimerization Process</title>
    <abstract language="eng">Ergopeptides, like ergocornine and a-ergocryptine, exist in an S- and in an R-configuration. Kinetic experiments imply that certain configurations are preferred depending on the solvent. The experimental methods are explained in this article. Furthermore, computational methods are used to understand this configurational preference. Standard quantum chemical methods can predict the favored configurations by using minimum energy calculations on the potential energy landscape. However, the explicit role of the solvent is not revealed by this type of methods. In order to better understand its influence, classical mechanical molecular simulations are applied. It appears from our research that “folding” the ergopeptide molecules into an intermediate state (between the S- and the R-configuration) is mechanically hindered for the preferred configurations.</abstract>
    <parentTitle language="eng">Computation</parentTitle>
    <identifier type="doi">10.3390/computation2030102</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <author>Karsten Andrae</author>
    <submitter>Adam Nielsen</submitter>
    <author>Stefan Merkel</author>
    <author>Vedat Durmaz</author>
    <author>Konstantin Fackeldey</author>
    <author>Robert Köppen</author>
    <author>Marcus Weber</author>
    <author>Matthias Koch</author>
    <collection role="institutes" number="num">Numerical Mathematics</collection>
    <collection role="institutes" number="compmol">Computational Molecular Design</collection>
    <collection role="persons" number="durmaz">Durmaz, Vedat</collection>
    <collection role="persons" number="fackeldey">Fackeldey, Konstantin</collection>
    <collection role="persons" number="weber">Weber, Marcus</collection>
    <collection role="projects" number="BAM-Ergoline">BAM-Ergoline</collection>
  </doc>
  <doc>
    <id>8247</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>84</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>annualzib</type>
    <publisherName/>
    <publisherPlace>Berlin</publisherPlace>
    <creatingCorporation>Kooperativer Bibliotheksverbund Berlin-Brandenburg</creatingCorporation>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2021-06-24</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">KOBV Jahresbericht 2019-2020</title>
    <abstract language="deu">Der aktuelle KOBV-Jahresbericht informiert darüber, was in den Mitgliedsbibliotheken und Partnerprojekten in den letzten beiden Jahren passiert ist und was sich in der Verbundzentrale und in der Bibliothekslandschaft ändert. Die Ausgabe 2019/2020 enthält den Schwerpunktteil »Digitalisierung« mit verschiedenen Perspektiven auf die digitale Arbeitswelt.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-82474</identifier>
    <identifier type="doi">10.12752/8247</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Beate Rusch</author>
    <submitter>Tim Hasler</submitter>
    <author>Wolfgang Peters-Kottig</author>
    <author>Julia Boltze</author>
    <author>Andreas Brandtner</author>
    <author>Andreas Degkwitz</author>
    <author>Simona Kirsch</author>
    <author>Thorsten Koch</author>
    <author>Stefan Lohrum</author>
    <author>Anja Müller</author>
    <author>Moritz Mutter</author>
    <author>Frank Seeliger</author>
    <author>Ursula Stanek</author>
    <series>
      <title>KOBV-Jahresbericht</title>
      <number>2019-2020</number>
    </series>
    <collection role="institutes" number="sis">Digital Data and Information for Society, Science, and Culture</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="lohrum">Lohrum, Stefan</collection>
    <collection role="persons" number="anja.mueller">Müller, Anja</collection>
    <collection role="persons" number="rusch">Rusch, Beate</collection>
    <collection role="persons" number="Peters-Kottig">Peters-Kottig, Wolfgang</collection>
    <collection role="projects" number="KOBV">KOBV</collection>
    <collection role="persons" number="boltze">Boltze, Julia</collection>
    <thesisPublisher>Zuse Institute Berlin (ZIB)</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-zib/files/8247/KOBV-Jahresbericht-2019-2020-web.pdf</file>
  </doc>
  <doc>
    <id>8542</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2022-01-12</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">DeepGreen: Etablierung und Weiterentwicklung rechtssicherer Workflows zur effizienten Umsetzung von Open-Access-Komponenten in Lizenzvereinbarungen für wissenschaftliche Publikationen – Abschlussbericht</title>
    <abstract language="deu">DeepGreen wurde vom 01.08.2018 bis zum 30.06.2021 in einer zweiten Projektphase von der Deutschen Forschungsgemeinschaft (DFG) gefördert. DeepGreen unterstützt Bibliotheken als Dienstleister für Hochschulen, außeruniversitäre Forschungseinrichtungen und die dort tätigen Wissenschaftler:innen dabei, Publikationen auf Open-Access-Repositorien frei zugänglich zu machen und fördert das Zusammenspiel von wissenschaftlichen Einrichtungen und Verlagen. An der zweiten Projektphase waren der Kooperative Bibliotheksverbund Berlin-Brandenburg, die Bayerische Staatsbibliothek, der Bibliotheksverbund Bayern, die Universitätsbibliotheken der Friedrich-Alexander-Universität Erlangen-Nürnberg und der Technischen Universität Berlin und das Helmholtz Open Science Office beteiligt. In dem Projekt wurde erfolgreich eine technische und organisatorische Lösung zur automatisierten Verteilung von Artikeldaten wissenschaftlicher Verlage an institutionelle und fachliche Repositorien entwickelt.  In der zweiten Projektphase lag der Fokus auf der Erprobung der Datendrehscheibe in der Praxis und der Ausweitung auf weitere Datenabnehmer und weitere Verlage. Im Anschluss an die DFG-geförderte Projektlaufzeit ist DeepGreen in einen zweijährigen Pilotbetrieb übergegangen. Ziel des Pilotbetriebs ist es, den Übergang in einen bundesweiten Real-Betrieb vorzubereiten.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-85420</identifier>
    <identifier type="doi">10.12752/8542</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <author>Roland Bertelmann</author>
    <submitter>Julia Boltze</submitter>
    <author>Thorsten Koch</author>
    <author>Klaus Ceynowa</author>
    <author>Konstanze Söllner</author>
    <author>Jürgen Christof</author>
    <author>Beate Rusch</author>
    <author>Hildegard Schäffler</author>
    <author>Markus Putnings</author>
    <author>Heinz Pampel</author>
    <author>Monika Kuberek</author>
    <author>Julia Boltze</author>
    <author>Stefan Lohrum</author>
    <author>Regina Retter</author>
    <author>Annika Höllerl</author>
    <author>Katja Faensen</author>
    <author>Ronald Steffen</author>
    <author>Matthias Gross</author>
    <author>Cornelia Hoffmann</author>
    <author>Marsa Haoua</author>
    <series>
      <title>ZIB-Report</title>
      <number>21-37</number>
    </series>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Open Access</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Repositorien</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>DeepGreen</value>
    </subject>
    <collection role="institutes" number="sis">Digital Data and Information for Society, Science, and Culture</collection>
    <collection role="institutes" number="">KOBV</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="lohrum">Lohrum, Stefan</collection>
    <collection role="persons" number="rusch">Rusch, Beate</collection>
    <collection role="persons" number="boltze">Boltze, Julia</collection>
    <collection role="projects" number="DeepGreen">DeepGreen</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/8542/DeepGreen_Abschlussbericht.pdf</file>
  </doc>
  <doc>
    <id>8150</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2021-02-11</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">DeepGreen: Open-Access-Transformation in der Informationsinfrastruktur – Anforderungen und Empfehlungen, Version 1.0</title>
    <abstract language="deu">DeepGreen ist ein Service, der es teilnehmenden institutionellen Open-Access-Repositorien,Open-Access-Fachrepositorien und Forschungsinformationssystemen erleichtert, für sie relevante Verlagspublikationen in zyklischer Abfolge mithilfe von Schnittstellen Open Access zur Verfügung zu stellen. Die entsprechende Bandbreite an Relationen zwischen den Akteuren, diverse lizenzrechtliche Rahmenbedingungen sowie technische Anforderungen gestalten das Thema komplex. Ziel dieser Handreichung ist es, neben all diesen Themen, die begleitend beleuchtet werden, im Besonderen Empfehlungen für die reibungslose Nutzung der Datenübertragung zu liefern. Außerdem werden mithilfe einer vorangestellten Workflow- Evaluierung Unterschiede und Besonderheiten in den Arbeitsschritten bei institutionellen Open-Access-Repositorien und Open-Access-Fachrepositorien aufgezeigt und ebenfalls mit Empfehlungen angereichert.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-81503</identifier>
    <identifier type="doi">10.12752/8150</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Roland Bertelmann</author>
    <submitter>Julia Boltze</submitter>
    <author>Julia Boltze</author>
    <author>Klaus Ceynowa</author>
    <author>Jürgen Christof</author>
    <author>Katja Faensen</author>
    <author>Matthias Groß</author>
    <author>Cornelia Hoffmann</author>
    <author>Thorsten Koch</author>
    <author>Monika Kuberek</author>
    <author>Stefan Lohrum</author>
    <author>Heinz Pampel</author>
    <author>Markus Putnings</author>
    <author>Regina Retter</author>
    <author>Beate Rusch</author>
    <author>Hildegard Schäffler</author>
    <author>Konstanze Söllner</author>
    <author>Ronald Steffen</author>
    <author>Eike Wannick</author>
    <series>
      <title>ZIB-Report</title>
      <number>21-03</number>
    </series>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Open Access</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Zweitveröffentlichung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Bibliotheken</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Verlage</value>
    </subject>
    <collection role="institutes" number="sis">Digital Data and Information for Society, Science, and Culture</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="lohrum">Lohrum, Stefan</collection>
    <collection role="persons" number="rusch">Rusch, Beate</collection>
    <collection role="persons" number="boltze">Boltze, Julia</collection>
    <collection role="projects" number="DeepGreen">DeepGreen</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/8150/Final_DeepGreen-Handreichung.pdf</file>
  </doc>
  <doc>
    <id>3264</id>
    <completedYear>2011</completedYear>
    <publishedYear>2011</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>103</pageFirst>
    <pageLast>163</pageLast>
    <pageNumber/>
    <edition/>
    <issue>2</issue>
    <volume>3</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">MIPLIB 2010</title>
    <parentTitle language="eng">Mathematical Programming Computation</parentTitle>
    <identifier type="doi">10.1007/s12532-011-0025-9</identifier>
    <identifier type="url">http://mpc.zib.de/index.php/MPC/article/view/56</identifier>
    <enrichment key="PreprintUrn">urn:nbn:de:0297-zib-12953</enrichment>
    <enrichment key="PeerReviewed">yes</enrichment>
    <author>Thorsten Koch</author>
    <author>Tobias Achterberg</author>
    <author>Erling Andersen</author>
    <author>Oliver Bastert</author>
    <author>Timo Berthold</author>
    <author>Robert E. Bixby</author>
    <author>Emilie Danna</author>
    <author>Gerald Gamrath</author>
    <author>Ambros Gleixner</author>
    <author>Stefan Heinz</author>
    <author>Andrea Lodi</author>
    <author>Hans Mittelmann</author>
    <author>Ted Ralphs</author>
    <author>Domenico Salvagnin</author>
    <author>Daniel Steffy</author>
    <author>Kati Wolter</author>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="institutes" number="mip">Mathematical Optimization Methods</collection>
    <collection role="persons" number="achterberg">Achterberg, Tobias</collection>
    <collection role="persons" number="berthold">Berthold, Timo</collection>
    <collection role="persons" number="gamrath">Gamrath, Gerald</collection>
    <collection role="persons" number="heinz">Heinz, Stefan</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="projects" number="MATHEON-B20">MATHEON-B20</collection>
    <collection role="projects" number="MIP-ZIBOPT">MIP-ZIBOPT</collection>
    <collection role="projects" number="Siemens">Siemens</collection>
    <collection role="projects" number="SPP1307-ExactIP">SPP1307-ExactIP</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>1192</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2010-12-21</completedDate>
    <publishedDate>2010-12-21</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">ParaSCIP - a parallel extension of SCIP</title>
    <abstract language="eng">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.</abstract>
    <identifier type="serial">10-27</identifier>
    <identifier type="doi">10.1007/978-3-642-24025-6_12</identifier>
    <identifier type="url">http://www.springerlink.com/content/t2160206253v7661/</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-11921</identifier>
    <enrichment key="SourceTitle">Bischof, Christian et al. (eds.): Competence in High Performance Computing 2010. Proceedings of an International Conference on Competence in High Performance Computing, June 2010, Schloss Schwetzingen, Germany. Berlin: Springer, 2012, S. 135-148.</enrichment>
    <author>Yuji Shinano</author>
    <submitter>-empty- (Opus4 user: admin)</submitter>
    <author>Tobias Achterberg</author>
    <submitter>Stefan Heinz</submitter>
    <author>Timo Berthold</author>
    <author>Stefan Heinz</author>
    <author>Thorsten Koch</author>
    <series>
      <title>ZIB-Report</title>
      <number>10-27</number>
    </series>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>massive parallization</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>mixed integer programming</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>ParaSCIP</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>branch-and-cut</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>branch-and-bound</value>
    </subject>
    <collection role="msc" number="65K05">Mathematical programming methods [See also 90Cxx]</collection>
    <collection role="msc" number="68W10">Parallel algorithms</collection>
    <collection role="msc" number="90C11">Mixed integer programming</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="achterberg">Achterberg, Tobias</collection>
    <collection role="persons" number="berthold">Berthold, Timo</collection>
    <collection role="persons" number="heinz">Heinz, Stefan</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/1192/ZR-10-27.pdf</file>
  </doc>
  <doc>
    <id>4718</id>
    <completedYear/>
    <publishedYear>2014</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName>Taylor &amp; Francis</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Validation of Nominations in Gas Network Optimization: Models, Methods, and Solutions</title>
    <abstract language="eng">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.&#13;
&#13;
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.</abstract>
    <parentTitle language="eng">Optimization Methods and Software</parentTitle>
    <identifier type="doi">10.1080/10556788.2014.888426</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="PreprintUrn">urn:nbn:de:0297-zib-16531</enrichment>
    <submitter>Robert Schwarz</submitter>
    <author>Marc Pfetsch</author>
    <author>Armin Fügenschuh</author>
    <author>Björn Geißler</author>
    <author>Nina Geißler</author>
    <author>Ralf Gollmer</author>
    <author>Benjamin Hiller</author>
    <author>Jesco Humpola</author>
    <author>Thorsten Koch</author>
    <author>Thomas Lehmann</author>
    <author>Alexander Martin</author>
    <author>Antonio Morsi</author>
    <author>Jessica Rövekamp</author>
    <author>Lars Schewe</author>
    <author>Martin Schmidt</author>
    <author>Rüdiger Schultz</author>
    <author>Robert Schwarz</author>
    <author>Jonas Schweiger</author>
    <author>Claudia Stangl</author>
    <author>Marc Steinbach</author>
    <author>Stefan Vigerske</author>
    <author>Bernhard Willert</author>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="fuegenschuh">Fügenschuh, Armin</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="vigerske">Vigerske, Stefan</collection>
    <collection role="persons" number="schweiger">Schweiger, Jonas</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>4821</id>
    <completedYear>2012</completedYear>
    <publishedYear>2012</publishedYear>
    <thesisYearAccepted/>
    <language>jpn</language>
    <pageFirst>165</pageFirst>
    <pageLast>192</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="jpn">SCIP Optimization Suite を利用した 混合整数(線形/非線形) 計画問題の解法</title>
    <abstract language="jpn">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．</abstract>
    <abstract language="eng">This paper introduces the SCIP Optimization Suite and discusses the capabilities of its three components: the modeling language Zimpl, the linear programming solver SoPlex, and the constraint integer programming framework SCIP. We explain how in concert these can be used to model and solve challenging mixed integer linear and nonlinear optimization problems. SCIP is currently one of the fastest non-commercial MIP and MINLP solvers. We demonstrate the usage of Zimpl, SCIP, and SoPlex by selected examples, we give an overview over available interfaces, and outline plans for future development.</abstract>
    <parentTitle language="jpn">Proceedings of the 24th RAMP symposium. The Operations Society of Japan, RAMP: Research Association of Mathematical Programming</parentTitle>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="PreprintUrn">urn:nbn:de:0297-zib-15598</enrichment>
    <author>Timo Berthold</author>
    <submitter>Ambros Gleixner</submitter>
    <author>Ambros Gleixner</author>
    <author>Stefan Heinz</author>
    <author>Thorsten Koch</author>
    <author>Yuji Shinano</author>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="institutes" number="mip">Mathematical Optimization Methods</collection>
    <collection role="persons" number="berthold">Berthold, Timo</collection>
    <collection role="persons" number="heinz">Heinz, Stefan</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="projects" number="MATHEON-B20">MATHEON-B20</collection>
    <collection role="projects" number="MIP-ZIBOPT">MIP-ZIBOPT</collection>
    <collection role="projects" number="Siemens">Siemens</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>4288</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2013-10-21</completedDate>
    <publishedDate>2013-10-21</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Solving hard MIPLIB2003 problems with ParaSCIP on Supercomputers: An update</title>
    <abstract language="eng">Contemporary supercomputers can easily provide years of&#13;
 CPU time per wall-clock hour. One challenge of today's software&#13;
 development is how to harness this wast computing power in order to solve&#13;
really hard mixed integer  programming instances. In 2010,  two out of&#13;
six open MIPLIB2003 instances  could be solved by ParaSCIP in more than&#13;
ten consecutive runs, restarting from checkpointing files.&#13;
 The contribution of this paper is threefold:&#13;
For the first time, we present computational results of single runs for&#13;
those two instances. Secondly, we provide new improved upper and lower&#13;
bounds for all of the remaining four open MIPLIB2003 instances.&#13;
 Finally, we explain which new developments led to these results and&#13;
discuss the current progress of ParaSCIP. Experiments were conducted on&#13;
HLRNII, on HLRN III, and on the Titan supercomputer, using up to 35,200 cores.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-42888</identifier>
    <author>Yuji Shinano</author>
    <submitter>Yuji Shinano</submitter>
    <author>Tobias Achterberg</author>
    <author>Timo Berthold</author>
    <author>Stefan Heinz</author>
    <author>Thorsten Koch</author>
    <author>Michael Winkler</author>
    <series>
      <title>ZIB-Report</title>
      <number>13-66</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mixed Integer Programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>MIPLIB2003</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>ParaSCIP</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Ubiquity Generator Framework</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Supercomputer</value>
    </subject>
    <collection role="ccs" number="G.">Mathematics of Computing</collection>
    <collection role="msc" number="90C11">Mixed integer programming</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="achterberg">Achterberg, Tobias</collection>
    <collection role="persons" number="berthold">Berthold, Timo</collection>
    <collection role="persons" number="heinz">Heinz, Stefan</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="persons" number="michael.winkler">Winkler, Michael</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/4288/zib-report-13-66.pdf</file>
    <file>https://opus4.kobv.de/opus4-zib/files/4288/ZR-13-66-revisedversion.pdf</file>
  </doc>
  <doc>
    <id>5767</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2016-02-26</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">The SCIP Optimization Suite 3.2</title>
    <abstract language="eng">The SCIP Optimization Suite is a software toolbox for generating and solving various classes of mathematical optimization problems. Its major components are the modeling language ZIMPL, the linear programming solver SoPlex, the constraint integer programming framework and mixed-integer linear and nonlinear programming solver SCIP, the UG framework for parallelization of branch-and-bound-based solvers, and the generic branch-cut-and-price solver GCG. It has been used in many applications from both academia and industry and is one of the leading non-commercial solvers.&#13;
This paper highlights the new features of version 3.2 of the SCIP Optimization Suite. Version 3.2 was released in July 2015. This release comes with new presolving steps, primal heuristics, and branching rules within SCIP. In addition, version 3.2 includes a reoptimization feature and improved handling of quadratic constraints and special ordered sets. SoPlex can now solve LPs exactly over the rational number and performance improvements have been achieved by exploiting sparsity in more situations. UG has been tested successfully on 80,000 cores. A major new feature of UG is the functionality to parallelize a customized SCIP solver. GCG has been enhanced with a new separator, new primal heuristics, and improved column management. Finally, new and improved extensions of SCIP are presented, namely solvers for multi-criteria optimization, Steiner tree problems, and mixed-integer semidefinite programs.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-57675</identifier>
    <enrichment key="PeerReviewed">no</enrichment>
    <author>Gerald Gamrath</author>
    <submitter>Gerald Gamrath</submitter>
    <author>Tobias Fischer</author>
    <author>Tristan Gally</author>
    <author>Ambros Gleixner</author>
    <author>Gregor Hendel</author>
    <author>Thorsten Koch</author>
    <author>Stephen J. Maher</author>
    <author>Matthias Miltenberger</author>
    <author>Benjamin Müller</author>
    <author>Marc Pfetsch</author>
    <author>Christian Puchert</author>
    <author>Daniel Rehfeldt</author>
    <author>Sebastian Schenker</author>
    <author>Robert Schwarz</author>
    <author>Felipe Serrano</author>
    <author>Yuji Shinano</author>
    <author>Stefan Vigerske</author>
    <author>Dieter Weninger</author>
    <author>Michael Winkler</author>
    <author>Jonas T. Witt</author>
    <author>Jakob Witzig</author>
    <series>
      <title>ZIB-Report</title>
      <number>15-60</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>mixed-integer linear and nonlinear programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>MIP solver</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>MINLP solver</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>linear programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>LP solver</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>simplex method</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>modeling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>parallel branch-and-bound</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>branch-cut-and-price framework</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>generic column generation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Steiner tree solver</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>multi-criteria optimization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>mixed-integer semidefinite programming</value>
    </subject>
    <collection role="msc" number="65Y05">Parallel computation</collection>
    <collection role="msc" number="90C05">Linear programming</collection>
    <collection role="msc" number="90C10">Integer programming</collection>
    <collection role="msc" number="90C11">Mixed integer programming</collection>
    <collection role="msc" number="90C30">Nonlinear programming</collection>
    <collection role="msc" number="90C90">Applications of mathematical programming</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="institutes" number="mip">Mathematical Optimization Methods</collection>
    <collection role="persons" number="gamrath">Gamrath, Gerald</collection>
    <collection role="persons" number="hendel">Hendel, Gregor</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="miltenberger">Miltenberger, Matthias</collection>
    <collection role="persons" number="rehfeldt">Rehfeldt, Daniel</collection>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="persons" number="vigerske">Vigerske, Stefan</collection>
    <collection role="persons" number="michael.winkler">Winkler, Michael</collection>
    <collection role="projects" number="ASTfSCM">ASTfSCM</collection>
    <collection role="projects" number="MIP-ZIBOPT">MIP-ZIBOPT</collection>
    <collection role="projects" number="MODAL-SynLab">MODAL-SynLab</collection>
    <collection role="projects" number="CRC1026">CRC1026</collection>
    <collection role="projects" number="Siemens">Siemens</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/5767/scipopt-32.pdf</file>
  </doc>
  <doc>
    <id>3270</id>
    <completedYear>2012</completedYear>
    <publishedYear>2012</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>135</pageFirst>
    <pageLast>148</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>Springer</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">ParaSCIP: a parallel extension of SCIP</title>
    <parentTitle language="eng">Competence in High Performance Computing 2010</parentTitle>
    <identifier type="doi">10.1007/978-3-642-24025-6_12</identifier>
    <enrichment key="PreprintUrn">urn:nbn:de:0297-zib-11921</enrichment>
    <enrichment key="PeerReviewed">yes</enrichment>
    <author>Yuji Shinano</author>
    <editor>Christian Bischof</editor>
    <author>Tobias Achterberg</author>
    <editor>Heinz-Gerd Hegering</editor>
    <author>Timo Berthold</author>
    <editor>Wolfgang Nagel</editor>
    <author>Stefan Heinz</author>
    <editor>Gabriel Wittum</editor>
    <author>Thorsten Koch</author>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="achterberg">Achterberg, Tobias</collection>
    <collection role="persons" number="berthold">Berthold, Timo</collection>
    <collection role="persons" number="heinz">Heinz, Stefan</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>3268</id>
    <completedYear>2012</completedYear>
    <publishedYear>2012</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>145</pageFirst>
    <pageLast>158</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>bookpart</type>
    <publisherName>Springer</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Using ZIMPL for Modeling Production Planning Problems</title>
    <parentTitle language="eng">Algebraic Modeling Systems</parentTitle>
    <identifier type="doi">10.1007/978-3-642-23592-4</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <author>Ulrich Dorndorf</author>
    <editor>Josef Kallrath</editor>
    <author>Stefan Droste</author>
    <author>Thorsten Koch</author>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>1559</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>jpn</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2012-07-25</completedDate>
    <publishedDate>2012-07-25</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="jpn">SCIP Optimization Suite を利用した 混合整数(線形/非線形) 計画問題の解法</title>
    <title language="eng">Solving mixed integer linear and nonlinear problems using the SCIP Optimization Suite</title>
    <abstract language="jpn">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&#13;
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&#13;
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&#13;
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&#13;
problems) や混合整数非線形計画問題(MINLP: mixed integer nonlinear optimization problems) をモデル化&#13;
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，&#13;
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&#13;
発計画の概要について述べる．</abstract>
    <abstract language="eng">This paper introduces the SCIP Optimization Suite and discusses the capabilities of its three components: the modeling language Zimpl, the linear programming solver SoPlex, and the constraint integer programming framework SCIP. We explain how in concert these can be used to model and solve challenging mixed integer linear and nonlinear optimization problems. SCIP is currently one of the fastest non-commercial MIP and MINLP solvers. We demonstrate the usage of Zimpl, SCIP, and SoPlex by selected examples, we give an overview over available interfaces, and outline plans for future development.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-15598</identifier>
    <enrichment key="SourceTitle">Appeared in: Proceedings of the 24th RAMP symposium. The Operations Society of Japan, RAMP: Research Association of Mathematical Programming. Masakazu Muramatsu (ed. ) 2012, pp. 165-192</enrichment>
    <author>Timo Berthold</author>
    <submitter>Ambros Gleixner</submitter>
    <author>Ambros Gleixner</author>
    <author>Stefan Heinz</author>
    <author>Thorsten Koch</author>
    <author>Yuji Shinano</author>
    <series>
      <title>ZIB-Report</title>
      <number>12-24</number>
    </series>
    <subject>
      <language>mul</language>
      <type>uncontrolled</type>
      <value>SCIP, MIP, MINLP, CIP, LP, modeling, optimization</value>
    </subject>
    <collection role="msc" number="90C05">Linear programming</collection>
    <collection role="msc" number="90C11">Mixed integer programming</collection>
    <collection role="msc" number="90C26">Nonconvex programming, global optimization</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="berthold">Berthold, Timo</collection>
    <collection role="persons" number="heinz">Heinz, Stefan</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="projects" number="MATHEON-B20">MATHEON-B20</collection>
    <collection role="projects" number="MIP-ZIBOPT">MIP-ZIBOPT</collection>
    <collection role="projects" number="Siemens">Siemens</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/1559/ZR-12-24.pdf</file>
  </doc>
  <doc>
    <id>1063</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2008-02-26</completedDate>
    <publishedDate>2008-02-26</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Counting solutions of integer programs using unrestricted subtree detection</title>
    <abstract language="eng">In the recent years there has been tremendous progress in the development of algorithms to find optimal solutions for integer programs. In many applications it is, however, desirable (or even necessary) to generate all feasible solutions. Examples arise in the areas of hardware and software verification and discrete geometry. In this paper, we investigate how to extend branch-and-cut integer programming frameworks to support the generation of all solutions. We propose a method to detect so-called unrestricted subtrees, which allows us to prune the integer program search tree and to collect several solutions simultaneously. We present computational results of this branch-and-count paradigm which show the potential of the unrestricted subtree detection.</abstract>
    <identifier type="serial">08-09</identifier>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="opus3-id">1092</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-10632</identifier>
    <enrichment key="SourceTitle">App. in: Integration of AI and OR techniques in constraint programming for combinatorial optimization problems : 5th International Conference, CPAIOR 2008 Paris, France, 2008; proc.,  Laurent Perron ... (eds.), LNC 5015, Springer 2008, pp. 278-282</enrichment>
    <author>Tobias Achterberg</author>
    <submitter>unknown unknown</submitter>
    <author>Stefan Heinz</author>
    <author>Thorsten Koch</author>
    <series>
      <title>ZIB-Report</title>
      <number>08-09</number>
    </series>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Zählen</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>ganzzahlige Programme</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>IP</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>counting</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>integer programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>IP</value>
    </subject>
    <collection role="ddc" number="510">Mathematik</collection>
    <collection role="msc" number="90C10">Integer programming</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="achterberg">Achterberg, Tobias</collection>
    <collection role="persons" number="heinz">Heinz, Stefan</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="projects" number="VeriCount">VeriCount</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/1063/ZR_08_09.pdf</file>
    <file>https://opus4.kobv.de/opus4-zib/files/1063/ZR_08_09.ps</file>
  </doc>
  <doc>
    <id>5890</id>
    <completedYear/>
    <publishedYear>2016</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Solving Open MIP Instances with ParaSCIP on Supercomputers using up to 80,000 Cores</title>
    <abstract language="eng">This paper describes how we solved 12 previously unsolved mixed-integer program- ming (MIP) instances from the MIPLIB benchmark sets. To achieve these results we used an enhanced version of ParaSCIP, setting a new record for the largest scale MIP computation: up to 80,000 cores in parallel on the Titan supercomputer. In this paper we describe the basic parallelization mechanism of ParaSCIP, improvements of the dynamic load balancing and novel techniques to exploit the power of parallelization for MIP solving. We give a detailed overview of computing times and statistics for solving open MIPLIB instances.</abstract>
    <parentTitle language="eng">Proc. of 30th IEEE International Parallel &amp; Distributed Processing Symposium</parentTitle>
    <identifier type="doi">10.1109/IPDPS.2016.56</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="PreprintUrn">urn:nbn:de:0297-zib-56404</enrichment>
    <author>Yuji Shinano</author>
    <submitter>Ambros Gleixner</submitter>
    <author>Tobias Achterberg</author>
    <author>Timo Berthold</author>
    <author>Stefan Heinz</author>
    <author>Thorsten Koch</author>
    <author>Michael Winkler</author>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="institutes" number="mip">Mathematical Optimization Methods</collection>
    <collection role="persons" number="achterberg">Achterberg, Tobias</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="projects" number="MIP-ZIBOPT">MIP-ZIBOPT</collection>
    <collection role="projects" number="MODAL-SynLab">MODAL-SynLab</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>1295</id>
    <completedYear>2010</completedYear>
    <publishedYear>2010</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">MIPLIB 2010</title>
    <abstract language="eng">This paper reports on the fifth version of the Mixed Integer Programming Library.  &#13;
The MIPLIB 2010 is the first MIPLIB release that has been assembled by a large group from academia and from industry, all of whom work in integer programming. There was mutual consent that the concept of the library had to be expanded in order to fulfill the needs of the community. The new version comprises 361 instances sorted into several groups.&#13;
This includes the main benchmark test set of 87 instances, which&#13;
are all solvable by today's codes, and also the challenge test set with 164 instances, many of which are currently unsolved.&#13;
For the first time, we include scripts to run automated tests in a predefined way. Further, there is a solution checker to&#13;
test the accuracy of provided solutions using exact arithmetic.</abstract>
    <identifier type="serial">10-31</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-12953</identifier>
    <identifier type="doi">10.1007/s12532-011-0025-9</identifier>
    <enrichment key="SourceTitle">Appeared in: Mathematical Programming Computation vol. 3 iss. 2 (2011), pp. 103-163</enrichment>
    <author>Thorsten Koch</author>
    <submitter>Timo Berthold</submitter>
    <author>Tobias Achterberg</author>
    <author>Erling Andersen</author>
    <author>Oliver Bastert</author>
    <author>Timo Berthold</author>
    <author>Robert E. Bixby</author>
    <author>Emilie Danna</author>
    <author>Gerald Gamrath</author>
    <author>Ambros Gleixner</author>
    <author>Stefan Heinz</author>
    <author>Andrea Lodi</author>
    <author>Hans Mittelmann</author>
    <author>Ted Ralphs</author>
    <author>Domenico Salvagnin</author>
    <author>Daniel Steffy</author>
    <author>Kati Wolter</author>
    <series>
      <title>ZIB-Report</title>
      <number>10-31</number>
    </series>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Mixed Integer Programming</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Problem Instances</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>IP</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>MIP</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>MIPLIB</value>
    </subject>
    <collection role="msc" number="90C10">Integer programming</collection>
    <collection role="msc" number="90C11">Mixed integer programming</collection>
    <collection role="msc" number="90C90">Applications of mathematical programming</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="achterberg">Achterberg, Tobias</collection>
    <collection role="persons" number="berthold">Berthold, Timo</collection>
    <collection role="persons" number="gamrath">Gamrath, Gerald</collection>
    <collection role="persons" number="heinz">Heinz, Stefan</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="projects" number="MATHEON-B20">MATHEON-B20</collection>
    <collection role="projects" number="MIP-ZIBOPT">MIP-ZIBOPT</collection>
    <collection role="projects" number="Siemens">Siemens</collection>
    <collection role="projects" number="SPP1307-ExactIP">SPP1307-ExactIP</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/1295/miplib5.pdf</file>
    <file>https://opus4.kobv.de/opus4-zib/files/1295/miplib5.ps</file>
  </doc>
  <doc>
    <id>1653</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2012-11-19</completedDate>
    <publishedDate>2012-11-19</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Validation of Nominations in Gas Network Optimization: Models, Methods, and Solutions</title>
    <abstract language="eng">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.&#13;
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.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-16531</identifier>
    <identifier type="doi">10.1080/10556788.2014.888426</identifier>
    <enrichment key="SourceTitle">Appeared in: Optimization Methods and Software 30 (2015) pp. 15-53</enrichment>
    <author>Marc Pfetsch</author>
    <submitter>Jonas Schweiger</submitter>
    <author>Armin Fügenschuh</author>
    <author>Björn Geißler</author>
    <author>Nina Geißler</author>
    <author>Ralf Gollmer</author>
    <author>Benjamin Hiller</author>
    <author>Jesco Humpola</author>
    <author>Thorsten Koch</author>
    <author>Thomas Lehmann</author>
    <author>Alexander Martin</author>
    <author>Antonio Morsi</author>
    <author>Jessica Rövekamp</author>
    <author>Lars Schewe</author>
    <author>Martin Schmidt</author>
    <author>Rüdiger Schultz</author>
    <author>Robert Schwarz</author>
    <author>Jonas Schweiger</author>
    <author>Claudia Stangl</author>
    <author>Marc Steinbach</author>
    <author>Stefan Vigerske</author>
    <author>Bernhard Willert</author>
    <series>
      <title>ZIB-Report</title>
      <number>12-41</number>
    </series>
    <collection role="ccs" number="D.">Software</collection>
    <collection role="ccs" number="J.">Computer Applications</collection>
    <collection role="msc" number="90-08">Computational methods</collection>
    <collection role="msc" number="90C11">Mixed integer programming</collection>
    <collection role="msc" number="90C30">Nonlinear programming</collection>
    <collection role="msc" number="90C90">Applications of mathematical programming</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="fuegenschuh">Fügenschuh, Armin</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="vigerske">Vigerske, Stefan</collection>
    <collection role="projects" number="MODAL-GasLab">MODAL-GasLab</collection>
    <collection role="projects" number="ForNe">ForNe</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="persons" number="schweiger">Schweiger, Jonas</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/1653/ZR-12-41.pdf</file>
    <file>https://opus4.kobv.de/opus4-zib/files/1653/ZR-12-41_revised.pdf</file>
  </doc>
  <doc>
    <id>1565</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2012-07-31</completedDate>
    <publishedDate>2012-07-31</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Solving mixed integer linear and nonlinear problems using the SCIP Optimization Suite</title>
    <abstract language="eng">This paper introduces the SCIP Optimization Suite and discusses the capabilities of its three components: the modeling language Zimpl, the linear programming solver SoPlex, and the constraint integer programming framework SCIP. We explain how these can be used in concert to model and solve challenging mixed integer linear and nonlinear optimization problems. SCIP is currently one of the fastest non-commercial MIP and MINLP solvers. We demonstrate the usage of Zimpl, SCIP, and SoPlex by selected examples, we give an overview of available interfaces, and outline plans for future development.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-15654</identifier>
    <author>Timo Berthold</author>
    <submitter>Ambros Gleixner</submitter>
    <author>Gerald Gamrath</author>
    <author>Ambros Gleixner</author>
    <author>Stefan Heinz</author>
    <author>Thorsten Koch</author>
    <author>Yuji Shinano</author>
    <series>
      <title>ZIB-Report</title>
      <number>12-27</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>LP, MIP, CIP, MINLP, modeling, optimization, SCIP, SoPlex, Zimpl</value>
    </subject>
    <collection role="msc" number="90C05">Linear programming</collection>
    <collection role="msc" number="90C11">Mixed integer programming</collection>
    <collection role="msc" number="90C26">Nonconvex programming, global optimization</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="berthold">Berthold, Timo</collection>
    <collection role="persons" number="gamrath">Gamrath, Gerald</collection>
    <collection role="persons" number="heinz">Heinz, Stefan</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="projects" number="MATHEON-B20">MATHEON-B20</collection>
    <collection role="projects" number="MIP-ZIBOPT">MIP-ZIBOPT</collection>
    <collection role="projects" number="Siemens">Siemens</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/1565/ZR-12-27.pdf</file>
  </doc>
  <doc>
    <id>1095</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2008-10-31</completedDate>
    <publishedDate>2008-10-31</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Constraint Integer Programming: Techniques and Applications</title>
    <abstract language="eng">This article introduces constraint integer programming (CIP), which is a novel way to combine constraint programming (CP) and mixed integer programming (MIP) methodologies. CIP is a generalization of MIP that supports the notion of general constraints as in CP. This approach is supported by the CIP framework SCIP, which also integrates techniques for solving satisfiability problems. SCIP is available in source code and free for noncommercial use. We demonstrate the usefulness of CIP on three tasks. First, we apply the constraint integer programming approach to pure mixed integer programs. Computational experiments show that SCIP is almost competitive to current state-of-the-art commercial MIP solvers. Second, we demonstrate how to use CIP techniques to compute the number of optimal solutions of integer programs. Third, we employ the CIP framework to solve chip design verification problems, which involve some highly nonlinear constraint types that are very hard to handle by pure MIP solvers. The CIP approach is very effective here: it can apply the full sophisticated MIP machinery to the linear part of the problem, while dealing with the nonlinear constraints by employing constraint programming techniques.</abstract>
    <identifier type="serial">08-43</identifier>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="opus3-id">1132</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-10950</identifier>
    <author>Tobias Achterberg</author>
    <submitter>unknown unknown</submitter>
    <author>Timo Berthold</author>
    <author>Stefan Heinz</author>
    <author>Thorsten Koch</author>
    <author>Kati Wolter</author>
    <series>
      <title>ZIB-Report</title>
      <number>08-43</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>constraint programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>mixed integer programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>branch-and-cut</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>optimization software</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>chip verification</value>
    </subject>
    <collection role="ddc" number="000">Informatik, Informationswissenschaft, allgemeine Werke</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="achterberg">Achterberg, Tobias</collection>
    <collection role="persons" number="berthold">Berthold, Timo</collection>
    <collection role="persons" number="heinz">Heinz, Stefan</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="projects" number="MATHEON-B12:IPSym">MATHEON-B12:IPSym</collection>
    <collection role="projects" number="VeriCount">VeriCount</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/1095/ZR_08_43.pdf</file>
    <file>https://opus4.kobv.de/opus4-zib/files/1095/ZR_08_43.ps</file>
  </doc>
  <doc>
    <id>5708</id>
    <completedYear/>
    <publishedYear>2014</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1552</pageFirst>
    <pageLast>1561</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>IEEE Computer Society</publisherName>
    <publisherPlace>Washington, DC, USA</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Solving Hard MIPLIP2003 Problems with ParaSCIP on Supercomputers: An Update</title>
    <parentTitle language="deu">IPDPSW'14 Proceedings of the 2014 IEEE,  International  Parallel &amp; Distributed Processing Symposium Workshops</parentTitle>
    <identifier type="isbn">978-1-4799-4117-9</identifier>
    <identifier type="doi">10.1109/IPDPSW.2014.174</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <editor> IEEE</editor>
    <submitter>Bettina Kasse</submitter>
    <author>Yuji Shinano</author>
    <submitter>Thorsten Koch</submitter>
    <author>Tobias Achterberg</author>
    <author>Timo Berthold</author>
    <author>Stefan Heinz</author>
    <author>Thorsten Koch</author>
    <author>Michael Winkler</author>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="achterberg">Achterberg, Tobias</collection>
    <collection role="persons" number="berthold">Berthold, Timo</collection>
    <collection role="persons" number="heinz">Heinz, Stefan</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="persons" number="michael.winkler">Winkler, Michael</collection>
    <collection role="projects" number="MIP-ZIBOPT">MIP-ZIBOPT</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>8530</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2021-12-17</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">The SCIP Optimization Suite 8.0</title>
    <abstract language="eng">The SCIP Optimization Suite provides a collection of software packages for mathematical optimization centered around the constraint integer programming framework SCIP. This paper discusses enhancements and extensions contained in version 8.0 of the SCIP Optimization Suite. Major updates in SCIP include improvements in symmetry handling and decomposition algorithms, new cutting planes, a new plugin type for cut selection, and a complete rework of the way nonlinear constraints are handled. Additionally, SCIP 8.0 now supports interfaces for Julia as well as Matlab. Further, UG now includes a unified framework to parallelize all solvers, a utility to analyze computational experiments has been added to GCG, dual solutions can be postsolved by PaPILO, new heuristics and presolving methods were added to SCIP-SDP, and additional problem classes and major performance improvements are available in SCIP-Jack.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-85309</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <author>Ksenia Bestuzheva</author>
    <submitter>Ksenia Bestuzheva</submitter>
    <author>Mathieu Besançon</author>
    <author>Wei-Kun Chen</author>
    <author>Antonia Chmiela</author>
    <author>Tim Donkiewicz</author>
    <author>Jasper van Doornmalen</author>
    <author>Leon Eifler</author>
    <author>Oliver Gaul</author>
    <author>Gerald Gamrath</author>
    <author>Ambros Gleixner</author>
    <author>Leona Gottwald</author>
    <author>Christoph Graczyk</author>
    <author>Katrin Halbig</author>
    <author>Alexander Hoen</author>
    <author>Christopher Hojny</author>
    <author>Rolf van der Hulst</author>
    <author>Thorsten Koch</author>
    <author>Marco Lübbecke</author>
    <author>Stephen J. Maher</author>
    <author>Frederic Matter</author>
    <author>Erik Mühmer</author>
    <author>Benjamin Müller</author>
    <author>Marc E. Pfetsch</author>
    <author>Daniel Rehfeldt</author>
    <author>Steffan Schlein</author>
    <author>Franziska Schlösser</author>
    <author>Felipe Serrano</author>
    <author>Yuji Shinano</author>
    <author>Boro Sofranac</author>
    <author>Mark Turner</author>
    <author>Stefan Vigerske</author>
    <author>Fabian Wegscheider</author>
    <author>Philipp Wellner</author>
    <author>Dieter Weninger</author>
    <author>Jakob Witzig</author>
    <series>
      <title>ZIB-Report</title>
      <number>21-41</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Constraint integer programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Linear programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mixed-integer linear programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mixed-integer nonlinear programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Optimization solver</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Branch-and-cut</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Branch-and-price</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Column generation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Parallelization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mixed-integer semidefinite programming</value>
    </subject>
    <collection role="msc" number="65Y05">Parallel computation</collection>
    <collection role="msc" number="90C05">Linear programming</collection>
    <collection role="msc" number="90C10">Integer programming</collection>
    <collection role="msc" number="90C11">Mixed integer programming</collection>
    <collection role="msc" number="90C30">Nonlinear programming</collection>
    <collection role="msc" number="90C90">Applications of mathematical programming</collection>
    <collection role="persons" number="gamrath">Gamrath, Gerald</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="rehfeldt">Rehfeldt, Daniel</collection>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="persons" number="vigerske">Vigerske, Stefan</collection>
    <collection role="projects" number="MODAL-SynLab">MODAL-SynLab</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="persons" number="schloesser">Schlösser, Franziska</collection>
    <collection role="persons" number="turner">Turner, Mark Ruben</collection>
    <collection role="persons" number="bestuzheva">Bestuzheva, Ksenia</collection>
    <collection role="projects" number="HPO-NAVI">HPO-NAVI</collection>
    <collection role="institutes" number="ais2t">AI in Society, Science, and Technology</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="persons" number="hoen">Hoen, Alexander</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/8530/scipopt-80.pdf</file>
  </doc>
  <doc>
    <id>9552</id>
    <completedYear/>
    <publishedYear>2024</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2024-02-26</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">The SCIP Optimization Suite 9.0</title>
    <abstract language="eng">The SCIP Optimization Suite provides a collection of software packages for mathematical optimization, centered around the constraint integer programming framework SCIP. This report discusses the enhancements and extensions included in the SCIP Optimization Suite 9.0. The updates in SCIP 9.0 include improved symmetry handling, additions and improvements of nonlinear handlers and primal heuristics, a new cut generator and two new cut selection schemes, a new branching rule, a new LP interface, and several bug fixes. The SCIP Optimization Suite 9.0 also features new Rust and C++ interfaces for SCIP, new Python interface for SoPlex, along with enhancements to existing interfaces. The SCIP Optimization Suite 9.0 also includes new and improved features in the LP solver SoPlex, the presolving library PaPILO, the parallel framework UG, the decomposition framework GCG, and the SCIP extension SCIP-SDP. These additions and enhancements have resulted in an overall performance improvement of SCIP in terms of solving time, number of nodes in the branch-and-bound tree, as well as the reliability of the solver.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-95528</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <author>Suresh Bolusani</author>
    <submitter>Christoph Spiegel</submitter>
    <author>Mathieu Besançon</author>
    <submitter>Suresh Bolusani</submitter>
    <author>Ksenia Bestuzheva</author>
    <author>Antonia Chmiela</author>
    <author>João Dionísio</author>
    <author>Tim Donkiewicz</author>
    <author>Jasper van Doornmalen</author>
    <author>Leon Eifler</author>
    <author>Mohammed Ghannam</author>
    <author>Ambros Gleixner</author>
    <author>Christoph Graczyk</author>
    <author>Katrin Halbig</author>
    <author>Ivo Hedtke</author>
    <author>Alexander Hoen</author>
    <author>Christopher Hojny</author>
    <author>Rolf van der Hulst</author>
    <author>Dominik Kamp</author>
    <author>Thorsten Koch</author>
    <author>Kevin Kofler</author>
    <author>Jurgen Lentz</author>
    <author>Julian Manns</author>
    <author>Gioni Mexi</author>
    <author>Erik Mühmer</author>
    <author>Marc E. Pfetsch</author>
    <author>Franziska Schlösser</author>
    <author>Felipe Serrano</author>
    <author>Yuji Shinano</author>
    <author>Mark Turner</author>
    <author>Stefan Vigerske</author>
    <author>Dieter Weninger</author>
    <author>Liding Xu</author>
    <series>
      <title>ZIB-Report</title>
      <number>24-02-29</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Constraint integer programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Linear programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mixed-integer linear programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mixed-integer nonlinear programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Optimization solver</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Branch-and-cut</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Branch-and-price</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Column generation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Parallelization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mixed-integer semidefinite programming</value>
    </subject>
    <collection role="msc" number="65Y05">Parallel computation</collection>
    <collection role="msc" number="90C05">Linear programming</collection>
    <collection role="msc" number="90C10">Integer programming</collection>
    <collection role="msc" number="90C11">Mixed integer programming</collection>
    <collection role="msc" number="90C30">Nonlinear programming</collection>
    <collection role="msc" number="90C90">Applications of mathematical programming</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="persons" number="vigerske">Vigerske, Stefan</collection>
    <collection role="projects" number="MODAL-SynLab">MODAL-SynLab</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="persons" number="schloesser">Schlösser, Franziska</collection>
    <collection role="persons" number="turner">Turner, Mark Ruben</collection>
    <collection role="persons" number="bestuzheva">Bestuzheva, Ksenia</collection>
    <collection role="persons" number="mexi">Mexi, Gioni</collection>
    <collection role="projects" number="HPO-NAVI">HPO-NAVI</collection>
    <collection role="institutes" number="ais2t">AI in Society, Science, and Technology</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="persons" number="hoen">Hoen, Alexander</collection>
    <collection role="persons" number="ghannam">Ghannam, Mohammed</collection>
    <collection role="persons" number="manns">Manns, Julian</collection>
    <collection role="persons" number="joao.goncalves.dionisio">Dionísio, João Pedro</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/9552/scipopt-90.pdf</file>
  </doc>
  <doc>
    <id>9405</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>21</pageLast>
    <pageNumber/>
    <edition/>
    <issue>2</issue>
    <volume>49</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Enabling research through the SCIP optimization suite 8.0</title>
    <abstract language="eng">The SCIP Optimization Suite provides a collection of software packages for mathematical optimization centered around the constraint integer programming framework SCIP. The focus of this article is on the role of the SCIP Optimization Suite in supporting research. SCIP’s main design principles are discussed, followed by a presentation of the latest performance improvements and developments in version 8.0, which serve both as examples of SCIP’s application as a research tool and as a platform for further developments. Furthermore, this article gives an overview of interfaces to other programming and modeling languages, new features that expand the possibilities for user interaction with the framework, and the latest developments in several extensions built upon SCIP.</abstract>
    <parentTitle language="eng">ACM Transactions on Mathematical Software</parentTitle>
    <identifier type="doi">10.1145/3585516</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Ksenia Bestuzheva</author>
    <submitter>Christoph Spiegel</submitter>
    <author>Mathieu Besançon</author>
    <author>Wei-Kun Chen</author>
    <author>Antonia Chmiela</author>
    <author>Tim Donkiewicz</author>
    <author>Jasper Doornmalen</author>
    <author>Leon Eifler</author>
    <author>Oliver Gaul</author>
    <author>Gerald Gamrath</author>
    <author>Ambros Gleixner</author>
    <author>Leona Gottwald</author>
    <author>Christoph Graczyk</author>
    <author>Katrin Halbig</author>
    <author>Alexander Hoen</author>
    <author>Christopher Hojny</author>
    <author>Rolf Hulst</author>
    <author>Thorsten Koch</author>
    <author>Marco Lübbecke</author>
    <author>Stephen J. Maher</author>
    <author>Frederic Matter</author>
    <author>Erik Mühmer</author>
    <author>Benjamin Müller</author>
    <author>Marc Pfetsch</author>
    <author>Daniel Rehfeldt</author>
    <author>Steffan Schlein</author>
    <author>Franziska Schlösser</author>
    <author>Felipe Serrano</author>
    <author>Yuji Shinano</author>
    <author>Boro Sofranac</author>
    <author>Mark Turner</author>
    <author>Stefan Vigerske</author>
    <author>Fabian Wegscheider</author>
    <author>Philipp Wellner</author>
    <author>Dieter Weninger</author>
    <author>Jakob Witzig</author>
    <collection role="persons" number="gamrath">Gamrath, Gerald</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="rehfeldt">Rehfeldt, Daniel</collection>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="persons" number="vigerske">Vigerske, Stefan</collection>
    <collection role="projects" number="MODAL-SynLab">MODAL-SynLab</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="persons" number="schloesser">Schlösser, Franziska</collection>
    <collection role="persons" number="turner">Turner, Mark Ruben</collection>
    <collection role="persons" number="bestuzheva">Bestuzheva, Ksenia</collection>
    <collection role="persons" number="sofranac">Šofranac, Boro</collection>
    <collection role="institutes" number="ais2t">AI in Society, Science, and Technology</collection>
    <collection role="persons" number="hoen">Hoen, Alexander</collection>
  </doc>
  <doc>
    <id>10003</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1168</pageFirst>
    <pageLast>1177</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2025-10-24</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Quantum Approximate Multi-Objective Optimization</title>
    <abstract language="eng">The goal of multi-objective optimization is to understand optimal trade-offs between competing objective functions by finding the Pareto front, i.e., the set of all Pareto optimal solutions, where no objective can be improved without degrading another one. Multi-objective optimization can be challenging classically, even if the corresponding single-objective optimization problems are efficiently solvable. Thus, multi-objective optimization represents a compelling problem class to analyze with quantum computers. In this work, we use low-depth Quantum Approximate Optimization Algorithm to approximate the optimal Pareto front of certain multi-objective weighted maximum cut problems. We demonstrate its performance on an IBM Quantum computer, as well as with Matrix Product State numerical simulation, and show its potential to outperform classical approaches.</abstract>
    <parentTitle language="deu">Nature Computational Science</parentTitle>
    <identifier type="arxiv">2503.22797</identifier>
    <identifier type="doi">10.1038/s43588-025-00873-y</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <author>Ayse Kotil</author>
    <submitter>Stephanie Riedmüller</submitter>
    <author>Elijah Pelofske</author>
    <author>Stephanie Riedmüller</author>
    <author>Daniel J. Egger</author>
    <author>Stephan Eidenbenz</author>
    <author>Thorsten Koch</author>
    <author>Stefan Woerner</author>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="projects" number="MODAL-EnergyLab">MODAL-EnergyLab</collection>
    <collection role="persons" number="riedmueller">Riedmüller, Stephanie</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
</export-example>
