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  <doc>
    <id>261</id>
    <completedYear/>
    <publishedYear>2013</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>631</pageFirst>
    <pageLast>640</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2020-02-04</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Simulation-based determination of capacity load factors for master production scheduling</title>
    <abstract language="eng">This paper deals with the problem of varying capacity load factors in master production scheduling. A simulation system of a production planning and control system and of a production system is described and an approach to compute the capacity loads from the simulation results is developed. This approach is used to measure period-specific capacity load factors for master production scheduling. The measured  capacity load factors vary over time and show that the common assumption of the load factors being period-independent is inappropriate. A stochastic programming model to cope with this variation is described. This model is compared to a common linear programming model for master production scheduling in a simulation experiment. The results show that the use of the measured capacity load factor scenarios improves the quality of the estimation of the capacity load factors significantly.</abstract>
    <parentTitle language="eng">Proceedings of the 15th International Conference on Simulation in Production and Logistics, October 9 - 11, 2013, Paderborn, Germany</parentTitle>
    <identifier type="urn">urn:nbn:de:bvb:898-opus4-2610</identifier>
    <author>Julian Englberger</author>
    <author>Frank Herrmann</author>
    <author>Thorsten Claus</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>PPS</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Kapazitätsplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Stochastisches Modell</value>
    </subject>
    <collection role="ddc" number="67">Industrielle Fertigung</collection>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16316">Produktion und Systeme</collection>
    <thesisPublisher>Ostbayerische Technische Hochschule Regensburg</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-oth-regensburg/files/261/Proof_117_Englberger.pdf</file>
  </doc>
</export-example>
