<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>7896</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>2020-07-15</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Conflict Analysis for MINLP</title>
    <abstract language="eng">The generalization of MIP techniques to deal with nonlinear, potentially non-convex, constraints have been a fruitful direction of research for computational MINLP in the last decade. In this paper, we follow that path in order to extend another essential subroutine of modern MIP solvers towards the case of nonlinear optimization: the analysis of infeasible subproblems for learning additional valid constraints. To this end, we derive two different strategies, geared towards two different solution approaches. These are using local dual proofs of infeasibility for LP-based branch-and-bound and the creation of nonlinear dual proofs for NLP-based branch-and-bound, respectively. We discuss implementation details of both approaches and present an extensive computational study, showing that both techniques can significantly enhance performance when solving MINLPs to global optimality.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-78964</identifier>
    <author>Timo Berthold</author>
    <submitter>Jakob Witzig</submitter>
    <author>Jakob Witzig</author>
    <series>
      <title>ZIB-Report</title>
      <number>20-20</number>
    </series>
    <collection role="msc" number="90C10">Integer 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="institutes" number="mip">Mathematical Optimization Methods</collection>
    <collection role="persons" number="berthold">Berthold, Timo</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="BEAM-ME">BEAM-ME</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="projects" number="HPO-NAVI">HPO-NAVI</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/7896/Berthold_Witzig__Conflict_Analysis_for_MINLP_ZR_20-20_v1.pdf</file>
  </doc>
  <doc>
    <id>7533</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>2019-12-02</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Conflict-Free Learning for Mixed Integer Programming</title>
    <abstract language="eng">Conflict learning plays an important role in solving mixed integer programs (MIPs) and is implemented in most major MIP solvers. A major step for MIP conflict learning is to aggregate the LP relaxation of an infeasible subproblem to a single globally valid constraint, the dual proof, that proves infeasibility within the local bounds. Among others, one way of learning is to add these constraints to the problem formulation for the remainder of the search.&#13;
&#13;
We suggest to not restrict this procedure to infeasible subproblems, but to also use global proof constraints from subproblems that are not (yet) infeasible, but can be expected to be pruned soon. As a special case, we also consider learning from integer feasible LP solutions. First experiments of this conflict-free learning strategy show promising results on the MIPLIB2017 benchmark set.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-75338</identifier>
    <identifier type="doi">10.1007/978-3-030-58942-4_34</identifier>
    <enrichment key="SourceTitle">Integration of AI and OR Techniques in Constraint Programming. CPAIOR 2020</enrichment>
    <author>Jakob Witzig</author>
    <submitter>Jakob Witzig</submitter>
    <author>Timo Berthold</author>
    <series>
      <title>ZIB-Report</title>
      <number>19-59</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>mixed integer programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>conflict analysis</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>dual proof analysis</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>no-good learning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>solution learning</value>
    </subject>
    <collection role="msc" number="90C10">Integer programming</collection>
    <collection role="msc" number="90C11">Mixed integer programming</collection>
    <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="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="BEAM-ME">BEAM-ME</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="projects" number="HPO-NAVI">HPO-NAVI</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/7533/ZR-19-59__witzig_berthold__conflict_free_learning_for_mip.pdf</file>
  </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>7817</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>2020-04-11</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">On the exact solution of prize-collecting Steiner tree problems</title>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-78174</identifier>
    <author>Daniel Rehfeldt</author>
    <submitter>Daniel Rehfeldt</submitter>
    <author>Thorsten Koch</author>
    <series>
      <title>ZIB-Report</title>
      <number>20-11</number>
    </series>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="rehfeldt">Rehfeldt, Daniel</collection>
    <collection role="projects" number="MODAL-SynLab">MODAL-SynLab</collection>
    <collection role="projects" number="BEAM-ME">BEAM-ME</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/7817/pcstpZIBv2.pdf</file>
  </doc>
  <doc>
    <id>7814</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>2020-04-03</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Estimating the Size of Branch-And-Bound Trees</title>
    <abstract language="eng">This paper investigates the estimation of the size of Branch-and-Bound (B&amp;B) trees for solving mixed-integer programs. We first prove that the size of the B&amp;B tree cannot be approximated within a factor of~2 for general binary programs, unless P equals NP. Second, we review measures of the progress of the B&amp;B search, such as the gap, and propose a new measure, which we call leaf frequency.&#13;
&#13;
We study two simple ways to transform these progress measures into B&amp;B tree size estimates, either as a direct projection, or via double-exponential smoothing, a standard time-series forecasting technique. We then combine different progress measures and their trends into nontrivial estimates using Machine Learning techniques, which yields more precise estimates than any individual measure. The best method we have identified uses all individual measures as features of a random forest model.&#13;
In a large computational study, we train and validate all methods on the publicly available MIPLIB and Coral general purpose benchmark sets. On average, the best method estimates B&amp;B tree sizes within a factor of 3 on the set of unseen test instances even during the early stage of the search, and improves in accuracy as the search progresses. It also achieves a factor 2 over the entire search on each out of six additional sets of homogeneous instances we have tested. All techniques are available in version 7 of the branch-and-cut framework SCIP.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-78144</identifier>
    <author>Gregor Hendel</author>
    <submitter>Gregor Hendel</submitter>
    <author>Daniel Anderson</author>
    <author>Pierre Le Bodic</author>
    <author>Marc Pfetsch</author>
    <series>
      <title>ZIB-Report</title>
      <number>20-02</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>mixed integer programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>machine learning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>branch and bound</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>forecasting</value>
    </subject>
    <collection role="msc" number="90-XX">OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="hendel">Hendel, Gregor</collection>
    <collection role="projects" number="ASTfSCM">ASTfSCM</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="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/7814/zibreportestimatingSearchTreeSize.pdf</file>
  </doc>
  <doc>
    <id>5713</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>--</completedDate>
    <publishedDate>2015-12-31</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">An (MI)LP-based Primal Heuristic for 3-Architecture Connected Facility Location in Urban Access Network Design</title>
    <abstract language="eng">We investigate the 3-architecture Connected Facility Location Problem arising in the design of urban telecommunication access networks integrating wired and wireless technologies. We propose an original optimization model for the problem that includes additional variables and constraints to take into account wireless signal coverage represented through signal-to-interference ratios. Since the problem can prove very challenging even for modern state-of-the art optimization solvers, we propose to solve it by an original primal heuristic that combines a probabilistic fixing procedure, guided by peculiar Linear Programming relaxations, with an exact MIP heuristic, based on a very large neighborhood search. Computational experiments on a set of realistic instances show that our heuristic can find solutions associated with much lower optimality gaps than a state-of-the-art solver.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-57139</identifier>
    <identifier type="doi">10.1007/978-3-319-31204-0_19</identifier>
    <enrichment key="SourceTitle">Applications of Evolutionary Computation, LNCS 9597, pp. 283-298</enrichment>
    <author>Fabio D'Andreagiovanni</author>
    <submitter>Fabio D'Andreagiovanni</submitter>
    <author>Fabian Mett</author>
    <author>Jonad Pulaj</author>
    <series>
      <title>ZIB-Report</title>
      <number>15-62</number>
    </series>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="institutes" number="tele">Mathematics of Telecommunication</collection>
    <collection role="persons" number="pulaj">Pulaj, Jonad</collection>
    <collection role="projects" number="ECMath-MI4">ECMath-MI4</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/5713/ZR-15-62_DAndreagiovanni_3architectureConnectedFacilityAccessNetworks.pdf</file>
  </doc>
  <doc>
    <id>6143</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>2016-12-17</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Optimization of Handouts for Rolling Stock Rotations Visualization</title>
    <abstract language="eng">A railway operator creates (rolling stock) rotations in order to have a precise master plan for the&#13;
operation of a timetable by railway vehicles. A rotation is considered as a cycle that multiply&#13;
traverses a set of operational days while covering trips of the timetable. As it is well known,&#13;
the proper creation of rolling stock rotations by, e.g., optimization algorithms is challenging&#13;
and still a topical research subject. Nevertheless, we study a completely different but strongly&#13;
related question in this paper, i.e.: How to visualize a rotation? For this purpose, we introduce&#13;
a basic handout concept, which directly leads to the visualization, i.e., handout of a rotation. In&#13;
our industrial application at DB Fernverkehr AG, the handout is exactly as important as the&#13;
rotation itself. Moreover, it turns out that also other European railway operators use exactly the&#13;
same methodology (but not terminology). Since a rotation can have many handouts of different&#13;
quality, we show how to compute optimal ones through an integer program (IP) by standard&#13;
software. In addition, a construction as well as an improvement heuristic are presented. Our&#13;
computational results show that the heuristics are a very reliable standalone approach to quickly&#13;
find near-optimal and even optimal handouts. The efficiency of the heuristics is shown via a&#13;
computational comparison to the IP approach.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-61430</identifier>
    <author>Ralf Borndörfer</author>
    <submitter>Thomas Schlechte</submitter>
    <author>Boris Grimm</author>
    <author>Markus Reuther</author>
    <author>Thomas Schlechte</author>
    <series>
      <title>ZIB-Report</title>
      <number>ZR-16-73</number>
    </series>
    <collection role="msc" number="90-XX">OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="institutes" number="traffic">Mathematics of Transportation and Logistics</collection>
    <collection role="persons" number="borndoerfer">Borndörfer, Ralf</collection>
    <collection role="persons" number="grimm">Grimm, Boris</collection>
    <collection role="persons" number="schlechte">Schlechte, Thomas</collection>
    <collection role="projects" number="MODAL-RailLab">MODAL-RailLab</collection>
    <collection role="projects" number="ROTOR">ROTOR</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="persons" number="reuther">Reuther, Markus</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/6143/ZR-16-73.pdf</file>
  </doc>
  <doc>
    <id>7024</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>2018-08-28</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Chvátal’s Conjecture Holds for Ground Sets of Seven Elements</title>
    <abstract language="eng">We establish a general computational framework for Chvátal’s conjecture based on exact rational integer programming. As a result we prove Chvátal’s conjecture holds for all downsets whose union of sets contains seven elements or less. The computational proof relies on an exact branch-and-bound certificate that allows for elementary verification and is independent of the integer programming solver used.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-70240</identifier>
    <author>Leon Eifler</author>
    <submitter>Leon Eifler</submitter>
    <author>Ambros Gleixner</author>
    <author>Jonad Pulaj</author>
    <series>
      <title>ZIB-Report</title>
      <number>18-49</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>extremal combinatorics</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>exact rational integer programming</value>
    </subject>
    <collection role="msc" number="05-XX">COMBINATORICS (For finite fields, see 11Txx)</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="pulaj">Pulaj, Jonad</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/7024/chvatal.pdf</file>
  </doc>
  <doc>
    <id>962</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2008-06-10</completedDate>
    <publishedDate>2008-06-10</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Tiefensuche: Bemerkungen zur Algorithmengeschichte</title>
    <title language="eng">Depth-first search: Remarks on the history of algorithms</title>
    <abstract language="deu">Dieser kurze Aufsatz zur Algorithmengeschichte ist Eberhard Knobloch, meinem Lieblings-Mathematikhistoriker, zum 65. Geburtstag gewidmet. Eberhard Knobloch hat immer, wenn ich ihm eine historische Frage zur Mathematik stellte, eine Antwort gewusst – fast immer auch sofort. Erst als ich mich selbst ein wenig und dazu amateurhaft mit Mathematikgeschichte beschäftigte, wurde mir bewusst, wie schwierig dieses „Geschäft“ ist. Man muss nicht nur mehrere (alte) Sprachen beherrschen, sondern auch die wissenschaftliche Bedeutung von Begriffen und Symbolen in früheren Zeiten kennen. Man muss zusätzlich herausfinden, was zur Zeit der Entstehung der Texte „allgemeines Wissen“ war, insbesondere, was seinerzeit gültige Beweisideen und -schritte waren, und daher damals keiner präzisen Definition oder Einführung bedurfte. Es gibt aber noch eine Steigerung des historischen Schwierigkeitsgrades: Algorithmengeschichte. Dies möchte ich in diesem Artikel kurz darlegen in der Hoffnung, dass sich Wissenschaftshistoriker dieses Themas noch intensiver annehmen, als sie das bisher tun. Der Grund ist, dass heute Algorithmen viele Bereiche unserer Alltagswelt steuern und unser tägliches Leben oft von funktionierenden Algorithmen abhängt. Daher wäre eine bessere Kenntnis der Algorithmengeschichte von großem Interesse.</abstract>
    <identifier type="serial">08-23</identifier>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="opus3-id">1106</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-9628</identifier>
    <enrichment key="SourceTitle">Ersch. in: Kosmos und Zahl: Beiträge zur Mathematik- und Astronomiegeschichte, zu Alexander von Humboldt und Leibniz. Hartmut Hecht ... (Hrsg.) Steiner, 2008, ISBN 978-3-515-09176-3. Boethius, 58, S. 331-346</enrichment>
    <author>Martin Grötschel</author>
    <submitter>unknown unknown</submitter>
    <submitter>unknown unknown</submitter>
    <series>
      <title>ZIB-Report</title>
      <number>08-23</number>
    </series>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Algorithmengeschichte</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Algorithmus</value>
    </subject>
    <collection role="ddc" number="510">Mathematik</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="groetschel">Grötschel, Martin</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/962/ZR_08_23.pdf</file>
  </doc>
  <doc>
    <id>1075</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2008-05-14</completedDate>
    <publishedDate>2008-05-14</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Diskrete Mathematik und ihre Anwendungen: Auf dem Weg zu authentischem Mathematikunterricht</title>
    <abstract language="deu">Das heutige Leben ist durchdrungen von komplexen Technologien. Ohne Kommunikationsnetze, Internet, Mobilfunk, Logistik, Verkehrstechnik, medizinische Apparate, etc. könnte die moderne Gesellschaft nicht funktionieren. Fast alle dieser Technologien haben einen hohen Mathematikanteil. Der "normale Bürger"' weiss davon nichts, der Schulunterricht könnte dem ein wenig abhelfen. Einige mathematische Aspekte dieser Technologien sind einfach und sogar spielerisch intuitiv zugänglich. Solche Anwendungen, die zusätzlich noch der Lebensumwelt der Schüler zugehören, können dazu genutzt werden, die mathematische Modellierung, also die mathematische Herangehensweise an die Lösung praktischer Fragen, anschaulich zu erläutern. Gerade in der diskreten Mathematik können hier, quasi "nebenbei" mathematische Theorien erarbeitet und Teilaspekte (Definitionen, Fragestellungen, einfache Sachverhalte) durch eigenständiges Entdecken der Schüler entwickelt werden. Wir beginnen mit einigen Beispielen.</abstract>
    <identifier type="serial">08-21</identifier>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="opus3-id">1104</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-10758</identifier>
    <enrichment key="SourceTitle">Ersch. in: Jahresbericht der Deutschen Mathematiker-Vereinigung 111 (2009) S. 3-22</enrichment>
    <author>Martin Grötschel</author>
    <submitter>unknown unknown</submitter>
    <author>Brigitte Lutz-Westphal</author>
    <submitter>unknown unknown</submitter>
    <series>
      <title>ZIB-Report</title>
      <number>08-21</number>
    </series>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Diskrete Mathematik</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Mathematikunterricht in Schulen</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>authentischer Mathematikunterricht</value>
    </subject>
    <collection role="ddc" number="510">Mathematik</collection>
    <collection role="msc" number="97D40">Teaching methods and classroom techniques</collection>
    <collection role="msc" number="97D50">Teaching problem solving and heuristic strategies (For research aspects, see 97Cxx)</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="groetschel">Grötschel, Martin</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/1075/ZR_08_21.pdf</file>
  </doc>
  <doc>
    <id>1862</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2013-05-30</completedDate>
    <publishedDate>2013-05-30</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Towards optimizing the deployment of optical access networks</title>
    <abstract language="eng">In this paper we study the cost-optimal deployment of optical access networks considering variants of the problem such as fiber to the home (FTTH), fiber to the building (FTTB), fiber to the curb (FTTC), or fiber to the neighborhood (FTTN). We identify the combinatorial structures of the most important sub-problems arising in this area and model these, e.g., as capacitated facility location, concentrator location, or Steiner tree problems. We discuss modeling alternatives as well. We finally construct a “unified” integer programming model that combines all sub-models and provides a global view of all these FTTx problems. We also summarize computational studies of various special cases.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-18627</identifier>
    <identifier type="doi">10.1007/s13675-013-0016-x</identifier>
    <author>Martin Grötschel</author>
    <submitter>Axel Werner</submitter>
    <author>Christian Raack</author>
    <author>Axel Werner</author>
    <series>
      <title>ZIB-Report</title>
      <number>13-11</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>FTTx, FTTH, FTTB, FTTC, FTTN, telecommunications, access networks, passive optical networks, network design, routing, energy efficiency</value>
    </subject>
    <collection role="msc" number="90-XX">OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="groetschel">Grötschel, Martin</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/1862/fttx-zib-report.pdf</file>
    <file>https://opus4.kobv.de/opus4-zib/files/1862/ZR-13-11revisedversion.pdf</file>
  </doc>
  <doc>
    <id>1439</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2012-01-04</completedDate>
    <publishedDate>2012-01-04</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Einblicke in die Diskrete Mathematik</title>
    <abstract language="deu">„Diskrete Mathematik, was ist das?“, ist eine typische Frage von Lehrern mit traditioneller Mathematikausbildung, denn dort kam und kommt diskrete Mathematik kaum vor. Die etwas Aufgeschlosseneren fragen: „Wenn (schon wieder) etwas Neues unterrichtet werden soll, was soll denn dann im Lehrplan gestrichen werden?“ Auf die zweite Frage wird hier nicht eingegangen. Das Ziel dieses Aufsatzes ist es, in diskrete Mathematik einzuführen, Interesse an diesem Fachgebiet zu wecken und dazu anzuregen, dieses auch im Schulunterricht (ein wenig) zu berücksichtigen. Die Schüler und Schülerinnen werden dafür dankbar sein – eine Erfahrung, die in  vielen Unterrichtsreihen gemacht wurde.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="serial">12-01</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-14399</identifier>
    <enrichment key="SourceTitle">Ersch. in: Der Mathematikunterricht - angewandte Diskrete Mathematik mit Schülerinnen und Schülern erkunden Jg. 58, H. 2, S. 4-17, 2012</enrichment>
    <author>Martin Grötschel</author>
    <submitter>Bettina Kasse</submitter>
    <series>
      <title>ZIB-Report</title>
      <number>12-01</number>
    </series>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>diskrete Mathematik</value>
    </subject>
    <collection role="ccs" number="A.">General Literature</collection>
    <collection role="ccs" number="G.">Mathematics of Computing</collection>
    <collection role="msc" number="00A35">Methodology of mathematics, didactics [See also 97Cxx, 97Dxx]</collection>
    <collection role="msc" number="05-01">Instructional exposition (textbooks, tutorial papers, etc.)</collection>
    <collection role="msc" number="97-XX">MATHEMATICS EDUCATION</collection>
    <collection role="msc" number="97-01">Instructional exposition (textbooks, tutorial papers, etc.)</collection>
    <collection role="msc" number="97B50">Teacher education (For research aspects, see 97C70)</collection>
    <collection role="msc" number="97Kxx">Combinatorics. Graph theory. Probability. Statistics</collection>
    <collection role="msc" number="97N70">Discrete mathematics</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="groetschel">Grötschel, Martin</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/1439/ZR12-01.pdf</file>
  </doc>
  <doc>
    <id>1036</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2007-11-19</completedDate>
    <publishedDate>2007-11-19</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Combinatorial Online Optimization: Elevators &amp; Yellow Angels</title>
    <abstract language="eng">In \emph{classical optimization} it is assumed that full information about the problem to be solved is given. This, in particular, includes that all data are at hand. The real world may not be so nice'' to optimizers. Some problem constraints may not be known, the data may be corrupted, or some data may not be available at the moments when decisions have to be made. The last issue is the subject of \emph{online optimization} which will be addressed here. We explain some theory that has been developed to cope with such situations and provide examples from practice where unavailable information is not the result of bad data handling but an inevitable phenomenon.</abstract>
    <identifier type="serial">07-36</identifier>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="opus3-id">1064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-10360</identifier>
    <enrichment key="SourceTitle">Appeared under the title "Structuring a Dynamic Environment: Combinatorial Online Optimization of Logistics Processes" in: Emergence, Analysis and Evolution of Structures : Concepts and Strategies Across Disciplines. Klaus Lucas, Peter Roosen eds. Springer 2010, pp. 199-214</enrichment>
    <author>Martin Grötschel</author>
    <submitter>unknown unknown</submitter>
    <author>Benjamin Hiller</author>
    <author>Andreas Tuchscherer</author>
    <series>
      <title>ZIB-Report</title>
      <number>07-36</number>
    </series>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Online-Optimierung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Aufzugssteuerung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Dispatching von Fahrzeugen</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>online optimization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>elevator control</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>vehicle dispatching</value>
    </subject>
    <collection role="ddc" number="000">Informatik, Informationswissenschaft, allgemeine Werke</collection>
    <collection role="msc" number="68W01">General</collection>
    <collection role="msc" number="90C10">Integer programming</collection>
    <collection role="msc" number="90C27">Combinatorial optimization</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="groetschel">Grötschel, Martin</collection>
    <collection role="projects" number="MATHEON-B14:Comb-Log">MATHEON-B14:Comb-Log</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/1036/ZR_07_36.pdf</file>
  </doc>
  <doc>
    <id>1479</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2012-03-05</completedDate>
    <publishedDate>2012-03-05</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">10 Jahre TELOTA</title>
    <abstract language="deu">Das TELOTA-Projekt - zunächst nur für zwei Jahre gestartet - feierte am 15. Juni 2011 sein&#13;
10-jähriges Bestehen im Rahmen eines Workshops mit einem abschließenden Festvortrag von&#13;
Richard Stallmann zum Thema „Copyright versus community in the age of computer&#13;
networks“. Diese Veranstaltung zeigte, wie aktuell die TELOTA-Themen weiterhin sind und&#13;
dass diese eine große Resonanz in der allgemeinen Öffentlichkeit finden. Die TELOTA-Aktivitäten&#13;
haben sich als wichtiger Bestandteil der IT-Infrastruktur der BBAW erwiesen,&#13;
gehen aber weit über reinen Service hinaus. Sie beeinflussen die Forschung selbst und führen&#13;
zu neuen interessanten wissenschaftlichen Fragestellungen. Der Rückblick auf die ersten zehn&#13;
Jahre der TELOTA-Initiative in diesem Artikel soll einen kleinen Eindruck von dem geben,&#13;
was bisher geleistet wurde.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="serial">12-13</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-14799</identifier>
    <enrichment key="SourceTitle">Ersch. in: Jahrbuch 2011 / Berlin-Brandenburgische Akademie der Wissenschaften. Berlin 2012. S. 202-215</enrichment>
    <author>Martin Grötschel</author>
    <submitter>Susanne Mittenzwey</submitter>
    <author>Gerald Neumann</author>
    <series>
      <title>ZIB-Report</title>
      <number>12-13</number>
    </series>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>BBAW</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Telota</value>
    </subject>
    <collection role="ccs" number="A.">General Literature</collection>
    <collection role="ccs" number="H.">Information Systems</collection>
    <collection role="msc" number="00-XX">GENERAL</collection>
    <collection role="msc" number="94-XX">INFORMATION AND COMMUNICATION, CIRCUITS</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="groetschel">Grötschel, Martin</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/1479/ZR_12_13.pdf</file>
  </doc>
  <doc>
    <id>1039</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2007-11-26</completedDate>
    <publishedDate>2007-11-26</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">George Dantzig's contributions to integer programming</title>
    <abstract language="eng">This paper reviews George Dantzig's contribution to integer programming, especially his seminal work with Fulkerson and Johnson on the traveling salesman problem</abstract>
    <identifier type="serial">07-39</identifier>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="opus3-id">1067</identifier>
    <identifier type="doi">10.1016/j.disopt.2007.08.003</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-10393</identifier>
    <enrichment key="SourceTitle">Appeared in: Discrete Optimization  5 (2008) pp. 168–173</enrichment>
    <author>Martin Grötschel</author>
    <submitter>unknown unknown</submitter>
    <author>George Nemhauser</author>
    <series>
      <title>ZIB-Report</title>
      <number>07-39</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>George Dantzig</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>integer programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>traveling salesman problem</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>TSP</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>mixed-integer programs</value>
    </subject>
    <collection role="ddc" number="510">Mathematik</collection>
    <collection role="msc" number="01A60">20th century</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="groetschel">Grötschel, Martin</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/1039/ZR_07_39.pdf</file>
  </doc>
  <doc>
    <id>7470</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Assessing the Effectiveness of (Parallel) Branch-and-bound Algorithms</title>
    <abstract language="eng">Empirical studies are fundamental in assessing the effectiveness of implementations of branch-and-bound algorithms. The complexity of such implementations makes empirical study difficult for a wide variety of reasons. Various attempts have been made to develop and codify a set of standard techniques for the assessment of optimization algorithms and their software implementations; however, most previous work has been focused on classical sequential algorithms. Since parallel computation has become increasingly mainstream, it is necessary to re-examine and modernize these practices. In this paper, we propose a framework for assessment based on the notion that resource consumption is at the heart of what we generally refer to as the “effectiveness” of an implementation. The proposed framework carefully distinguishes between an implementation’s baseline efficiency, the efficacy with which it utilizes a fixed allocation of resources, and its scalability, a measure of how the efficiency changes as resources (typically additional computing cores) are added or removed. Efficiency is typically applied to sequential implementations, whereas scalability is applied to parallel implementations. Efficiency and scalability are both important contributors in determining the overall effectiveness of a given parallel implementation, but the goal of improved efficiency is often at odds with the goal of improved scalability. Within the proposed framework, we review the challenges to effective evaluation and discuss the strengths and weaknesses of existing methods of assessment.</abstract>
    <identifier type="urn">urn:nbn:de:0297-zib-74702</identifier>
    <author>Stephen J. Maher</author>
    <submitter>Stephen J. Maher</submitter>
    <author>Ted Ralphs</author>
    <author>Yuji Shinano</author>
    <series>
      <title>ZIB-Report</title>
      <number>19-03</number>
    </series>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="shinano">Shinano, Yuji</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/7470/Assessing_effectiveness_branch-and-bound_algorithms_ZIB-Report.pdf</file>
  </doc>
  <doc>
    <id>7488</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>2019-10-25</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Regularized partially functional autoregressive model with application to high-resolution natural gas forecasting in Germany</title>
    <abstract language="eng">We propose a partially functional autoregressive model with exogenous variables&#13;
(pFAR) to describe the dynamic evolution of the serially correlated functional data.&#13;
It provides a unit� ed framework to model both the temporal dependence on multiple lagged functional covariates and the causal relation with ultrahigh-dimensional exogenous scalar covariates. Estimation is conducted under a two-layer sparsity assumption, where only a few groups and elements are supposed to be active, yet without knowing their number and location in advance. We establish asymptotic properties of the estimator and investigate its unite sample performance along with simulation studies. We demonstrate the application of pFAR with the high-resolution natural gas flows in Germany, where the pFAR model provides insightful interpretation as well as good out-of-sample forecast accuracy.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-74880</identifier>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <author>Ying Chen</author>
    <submitter>Janina Zittel</submitter>
    <author>Thorsten Koch</author>
    <author>Xiaofei Xu</author>
    <series>
      <title>ZIB-Report</title>
      <number>19-34</number>
    </series>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="projects" number="MODAL-GasLab">MODAL-GasLab</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/7488/pfar_20190709.pdf</file>
  </doc>
  <doc>
    <id>1462</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2012-01-27</completedDate>
    <publishedDate>2012-01-27</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Steiner Tree Packing Revisited</title>
    <abstract language="eng">The Steiner tree packing problem (STPP) in graphs is a long studied&#13;
problem in combinatorial optimization. In contrast to many other problems,&#13;
where there have been tremendous advances in practical problem&#13;
solving, STPP remains very difficult. Most heuristics schemes are ineffective&#13;
and even finding feasible solutions is already NP-hard. What makes&#13;
this problem special is that in order to reach the overall optimal solution&#13;
non-optimal solutions to the underlying NP-hard Steiner tree problems&#13;
must be used. Any non-global approach to the STPP is likely to fail.&#13;
Integer programming is currently the best approach for computing optimal&#13;
solutions. In this paper we review some “classical” STPP instances&#13;
which model the underlying real world application only in a reduced form.&#13;
Through improved modelling, including some new cutting planes, and by&#13;
emplyoing recent advances in solver technology we are for the first time&#13;
able to solve those instances in the original 3D grid graphs to optimimality.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="serial">12-02</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-14625</identifier>
    <identifier type="doi">10.1007/s00186-012-0391-8</identifier>
    <enrichment key="SourceTitle">Appeared in:  Mathematical Methods of Operations Research August 2012, Volume 76, Issue 1, pp 95-123</enrichment>
    <author>Nam-Dung Hoang</author>
    <submitter>Thorsten Koch</submitter>
    <author>Thorsten Koch</author>
    <series>
      <title>ZIB-Report</title>
      <number>12-02</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Steiner tree packing</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Integer Programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>grid graphs</value>
    </subject>
    <collection role="msc" number="90C11">Mixed integer programming</collection>
    <collection role="msc" number="90C35">Programming involving graphs or networks [See also 90C27]</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="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/1462/ZR-12-02.pdf</file>
  </doc>
  <doc>
    <id>7429</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>2019-08-07</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A Three-Phase Heuristic for Cyclic Crew Rostering with Fairness Requirements</title>
    <abstract language="eng">In this paper, we consider the Cyclic Crew Rostering Problem with Fairness Requirements (CCRP-FR). In this problem, attractive cyclic rosters have to be constructed for groups of employees, considering multiple, a priori determined, fairness levels. The attractiveness follows from the structure of the rosters (e.g., sufficient rest times and variation in work), whereas fairness is based on the work allocation  among the different roster groups. We propose a three-phase heuristic for the CCRP-FR, which  combines the strength of column generation techniques with a large-scale neighborhood search algorithm.  The design of the heuristic assures that good solutions for all fairness levels are obtained quickly, and can still be further improved if additional running time is available. We evaluate the performance of the algorithm using real-world data from Netherlands Railways, and show that the heuristic finds close to optimal solutions for many of the considered instances. In particular, we show that the heuristic is able to quickly find major improvements upon the current sequential practice: For most instances, the heuristic is  able to increase the attractiveness  by at least 20% in just a few minutes.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-74297</identifier>
    <author>Thomas Breugem</author>
    <submitter>Thomas Schlechte</submitter>
    <author>Ralf Borndörfer</author>
    <author>Thomas Schlechte</author>
    <author>Christof Schulz</author>
    <series>
      <title>ZIB-Report</title>
      <number>19-43</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Crew Planning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Column Generation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Variable-Depth Neighborhood Search</value>
    </subject>
    <collection role="msc" number="90-XX">OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="borndoerfer">Borndörfer, Ralf</collection>
    <collection role="persons" number="schlechte">Schlechte, Thomas</collection>
    <collection role="persons" number="schulz">Schulz, Christof</collection>
    <collection role="projects" number="MODAL-RailLab">MODAL-RailLab</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/7429/ZR-19-43.pdf</file>
  </doc>
  <doc>
    <id>7466</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>2019-09-11</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Multi-Period Line Planning with Resource Transfers</title>
    <abstract language="eng">Urban transportation systems are subject to a high level of variation and fluctuation in demand over the day. When this variation and fluctuation are observed in both time and space, it is crucial to develop line plans that are responsive to demand. A multi-period line planning approach that considers a changing demand during the planning horizon is proposed. If such systems are also subject to limitations of resources, a dynamic transfer of resources from one line to another throughout the planning horizon should also be considered. A mathematical modelling framework is developed to solve the line planning problem with transfer of resources during a finite length planning horizon of multiple periods. We analyze whether or not multi-period solutions outperform single period solutions in terms of feasibility and relevant costs. The importance of demand variation on multi-period solutions is investigated. We evaluate the impact of resource transfer constraints on the effectiveness of solutions. We also study the effect of line type designs and question the choice of period lengths along with the problem parameters that are significant for and sensitive to the optimality of solutions.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-74662</identifier>
    <author>Guvenc Sahin</author>
    <submitter>Thomas Schlechte</submitter>
    <author>Amin Ahmadi</author>
    <author>Ralf Borndörfer</author>
    <author>Thomas Schlechte</author>
    <series>
      <title>ZIB-Report</title>
      <number>19-51</number>
    </series>
    <collection role="msc" number="90-XX">OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="borndoerfer">Borndörfer, Ralf</collection>
    <collection role="persons" number="schlechte">Schlechte, Thomas</collection>
    <collection role="projects" number="MODAL-RailLab">MODAL-RailLab</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="projects" number="ECMath-MI7">ECMath-MI7</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/7466/ZR-19-51.pdf</file>
  </doc>
  <doc>
    <id>7463</id>
    <completedYear>2019</completedYear>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2019-09-09</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Bounds for the final ranks during a round robin tournament</title>
    <abstract language="eng">This article answers two kinds of questions regarding the Bundesliga which is Germany's primary football (soccer) competition having the highest average stadium attendance worldwide. First "At any point of the season, what final rank will a certain team definitely reach?" and second "At any point of the season, what final rank can a certain team at most reach?". Although we focus especially on the Bundesliga, the models that we use to answer the two questions can easily be adopted to league systems that are similar to that of the Bundesliga.</abstract>
    <parentTitle language="deu">Operational Research - An International Journal (ORIJ)</parentTitle>
    <identifier type="urn">urn:nbn:de:0297-zib-74638</identifier>
    <identifier type="doi">https://doi.org/10.1007/s12351-020-00546-w</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="SubmissionStatus">accepted for publication</enrichment>
    <enrichment key="AcceptedDate">2020-01-07</enrichment>
    <enrichment key="PreprintUrn">urn:nbn:de:0297-zib-74638</enrichment>
    <author>Uwe Gotzes</author>
    <submitter>Kai Hoppmann</submitter>
    <author>Kai Hoppmann</author>
    <series>
      <title>ZIB-Report</title>
      <number>19-50</number>
    </series>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="hennig">Hoppmann, Kai</collection>
    <collection role="projects" number="MODAL-GasLab">MODAL-GasLab</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="enernet">Energy Network Optimization</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/7463/bounding_final_ranks.pdf</file>
  </doc>
  <doc>
    <id>7417</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2019-08-01</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Verification of Neural Networks</title>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-74174</identifier>
    <author>Ansgar Rössig</author>
    <submitter>Milena Petkovic</submitter>
    <series>
      <title>ZIB-Report</title>
      <number>19-40</number>
    </series>
    <collection role="ddc" number="0">Informatik, Informationswissenschaft, allgemeine Werke</collection>
    <collection role="ccs" number="G.">Mathematics of Computing</collection>
    <collection role="bk" number="31">Mathematik</collection>
    <collection role="collections" number="">Studienabschlussarbeiten</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="projects" number="MODAL-GasLab">MODAL-GasLab</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/7417/ZR_19-40.pdf</file>
  </doc>
  <doc>
    <id>7385</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>2019-07-05</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">New Perspectives on PESP: T-Partitions and Separators</title>
    <abstract language="eng">In the planning process of public transportation companies, designing the timetable is among the core planning steps. In particular in the case of periodic (or cyclic) services, the Periodic Event Scheduling Problem (PESP) is well-established to compute high-quality periodic timetables.&#13;
&#13;
We are considering algorithms for computing good solutions for the very basic PESP with no additional extra features as add-ons. The first of these algorithms generalizes several primal heuristics that had been proposed in the past, such as single-node cuts and the modulo network simplex algorithm. We consider partitions of the graph, and identify so-called delay cuts as a structure that allows to generalize several previous heuristics. In particular, when no more improving delay cut can be found, we already know that the other heuristics could not improve either.&#13;
&#13;
The second of these algorithms turns a strategy, that had been discussed in the past, upside-down: Instead of gluing together the network line-by-line in a bottom-up way, we develop a divide-and-conquer-like top-down approach to separate the initial problem into two easier subproblems such that the information loss along their cutset edges is as small as possible.&#13;
&#13;
We are aware that there may be PESP instances that do not fit well the separator setting. Yet, on the RxLy-instances of PESPlib in our experimental computations, we come up with good primal solutions and dual bounds. In particular, on the largest instance (R4L4), this new separator approach, which applies a state-of-the-art solver as subroutine, is able to come up with better dual bounds than purely applying this state-of-the-art solver in the very same time.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-73853</identifier>
    <identifier type="doi">10.4230/OASIcs.ATMOS.2019.2</identifier>
    <author>Niels Lindner</author>
    <submitter>Niels Lindner</submitter>
    <author>Christian Liebchen</author>
    <series>
      <title>ZIB-Report</title>
      <number>19-35</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Periodic Event Scheduling Problem</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Periodic Timetabling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Graph Partitioning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Graph Separators</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Balanced Cuts</value>
    </subject>
    <collection role="ccs" number="G.">Mathematics of Computing</collection>
    <collection role="ccs" number="J.">Computer Applications</collection>
    <collection role="msc" number="90-XX">OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="lindner">Lindner, Niels</collection>
    <collection role="projects" number="ECMath-MI7">ECMath-MI7</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/7385/main.pdf</file>
  </doc>
</export-example>
