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  <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>
</export-example>
