<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <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>7363</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>2019-06-17</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Optimal Operation of Transient Gas Transport Networks</title>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-73639</identifier>
    <author>Kai Hoppmann</author>
    <submitter>Kai Hoppmann</submitter>
    <author>Felix Hennings</author>
    <author>Ralf Lenz</author>
    <author>Uwe Gotzes</author>
    <author>Nina Heinecke</author>
    <author>Klaus Spreckelsen</author>
    <author>Thorsten Koch</author>
    <series>
      <title>ZIB-Report</title>
      <number>19-23</number>
    </series>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="hennig">Hoppmann, Kai</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="lenz">Lenz, Ralf</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/7363/Netmodel_Paper.pdf</file>
    <file>https://opus4.kobv.de/opus4-zib/files/7363/Netmodel_Paper_v2.pdf</file>
    <file>https://opus4.kobv.de/opus4-zib/files/7363/Netmodel_Paper_v3.pdf</file>
  </doc>
  <doc>
    <id>8152</id>
    <completedYear/>
    <publishedYear>2021</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue>Special Issue on Energy Networks</issue>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">An Optimization Approach for the Transient Control of Hydrogen Transport Networks</title>
    <parentTitle language="eng">Mathematical Methods of Operations Research</parentTitle>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="SubmissionStatus">under review</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <author>Kai Hoppmann-Baum</author>
    <submitter>Kai Hoppmann-Baum</submitter>
    <author>Felix Hennings</author>
    <author>Janina Zittel</author>
    <author>Uwe Gotzes</author>
    <author>Eva-Maria Spreckelsen</author>
    <author>Klaus Spreckelsen</author>
    <author>Thorsten Koch</author>
    <collection role="institutes" number="mip">Mathematical Optimization Methods</collection>
    <collection role="persons" number="hennig">Hoppmann, Kai</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="zittel">Zittel, Janina</collection>
    <collection role="projects" number="MODAL-GasLab">MODAL-GasLab</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="Mathematical Algorithmic Intelligence">Mathematical Algorithmic Intelligence</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>8104</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>1866-1505</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Bounding the final rank during a round robin tournament with integer programming</title>
    <abstract language="eng">This article is mainly motivated by the urge to answer two kinds of questions regarding the Bundesliga, which is Germany’s primary football (soccer) division having the highest average stadium attendance worldwide: “At any point in the season, what is the lowest final rank a certain team can achieve?” and “At any point in the season, what is the highest final rank a certain team can achieve?”. Although we focus on the Bundesliga in particular, the integer programming formulations we introduce to answer these questions can easily be adapted to a variety of other league systems and tournaments.</abstract>
    <parentTitle language="eng">Operational Research</parentTitle>
    <identifier type="doi">https://doi.org/10.1007/s12351-020-00546-w</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="AcceptedDate">07.01.2020</enrichment>
    <enrichment key="PreprintUrn">urn:nbn:de:0297-zib-74638</enrichment>
    <author>Uwe Gotzes</author>
    <submitter>Kai Hoppmann-Baum</submitter>
    <author>Kai Hoppmann-Baum</author>
    <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="Mathematical Algorithmic Intelligence">Mathematical Algorithmic Intelligence</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>7990</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2020-11-04</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">From Natural Gas towards Hydrogen - A Feasibility Study on Current Transport Network Infrastructure and its Technical Control</title>
    <abstract language="eng">This study examines the usability of a real-world, large-scale natural gas transport infrastructure for hydrogen transport. We investigate whether a converted network can transport the amounts of hydrogen necessary to satisfy current energy demands. After introducing an optimization model for the robust transient control of hydrogen networks, we conduct computational experiments based on real-world demand scenarios. Using a representative network, we demonstrate that replacing each turbo compressor unit by four parallel hydrogen compressors, each of them comprising multiple serial compression stages, and imposing stricter rules regarding the balancing of in- and outflow suffices to realize transport in a majority of scenarios. However, due to the reduced linepack there is an increased need for technical and non-technical measures leading to a more dynamic network control. Furthermore, the amount of energy needed for compression increases by 364% on average.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-79901</identifier>
    <submitter>Kai Hoppmann-Baum</submitter>
    <author>Kai Hoppmann-Baum</author>
    <author>Felix Hennings</author>
    <author>Janina Zittel</author>
    <author>Uwe Gotzes</author>
    <author>Eva-Maria Spreckelsen</author>
    <author>Klaus Spreckelsen</author>
    <author>Thorsten Koch</author>
    <series>
      <title>ZIB-Report</title>
      <number>20-27</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Hydrogen Transport</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Hydrogen Infrastructure</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Network Flows</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mixed Integer Programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Energiewende</value>
    </subject>
    <collection role="persons" number="hennig">Hoppmann, Kai</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="zittel">Zittel, Janina</collection>
    <collection role="projects" number="MODAL-GasLab">MODAL-GasLab</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="Mathematical Algorithmic Intelligence">Mathematical Algorithmic Intelligence</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>
    <file>https://opus4.kobv.de/opus4-zib/files/7990/zib_report_20_27.pdf</file>
  </doc>
  <doc>
    <id>8008</id>
    <completedYear>2020</completedYear>
    <publishedYear>2021</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>735</pageFirst>
    <pageLast>781</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>22</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>0021-02-16</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Optimal Operation of Transient Gas Transport Networks</title>
    <abstract language="eng">In this paper, we describe an algorithmic framework for the optimal operation of transient gas transport networks consisting of a hierarchical MILP formulation together with a sequential linear programming inspired post-processing routine. Its implementation is part of the KOMPASS decision support system, which is currently used in an industrial setting.&#13;
&#13;
Real-world gas transport networks are controlled by operating complex pipeline intersection areas, which comprise multiple compressor units, regulators, and valves. In the following, we introduce the concept of network stations to model them. Thereby, we represent the technical capabilities of a station by hand-tailored artificial arcs and add them to network. Furthermore, we choose from a predefined set of flow directions for each network station and time step, which determines where the gas enters and leaves the station. Additionally, we have to select a supported simple state, which consists of two subsets of artificial arcs: Arcs that must and arcs that cannot be used. The goal is to determine a stable control of the network satisfying all supplies and demands.&#13;
&#13;
The pipeline intersections, that are represented by the network stations, were initially built centuries ago. Subsequently, due to updates, changes, and extensions, they evolved into highly complex and involved topologies. To extract their basic properties and to model them using computer-readable and optimizable descriptions took several years of effort.&#13;
&#13;
To support the dispatchers in controlling the network, we need to compute a continuously  updated list of recommended measures. Our motivation for the model presented here is to make fast decisions on important transient global control parameters, i.e., how to route the flow and where to compress the gas. Detailed continuous and discrete technical control measures realizing them, which take all hardware details into account, are determined in a subsequent step. &#13;
&#13;
In this paper, we present computational results from the KOMPASS project using detailed real-world data.</abstract>
    <parentTitle language="eng">Optimization and Engineering</parentTitle>
    <identifier type="doi">10.1007/s11081-020-09584-x</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="PreprintUrn">urn:nbn:de:0297-zib-73639</enrichment>
    <author>Kai Hoppmann-Baum</author>
    <submitter>Kai Hoppmann-Baum</submitter>
    <author>Felix Hennings</author>
    <author>Ralf Lenz</author>
    <author>Uwe Gotzes</author>
    <author>Nina Heinecke</author>
    <author>Klaus Spreckelsen</author>
    <author>Thorsten Koch</author>
    <collection role="persons" number="hennig">Hoppmann, Kai</collection>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="persons" number="lenz">Lenz, Ralf</collection>
    <collection role="projects" number="MODAL-GasLab">MODAL-GasLab</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="Mathematical Algorithmic Intelligence">Mathematical Algorithmic Intelligence</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>
</export-example>
