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  <doc>
    <id>7882</id>
    <completedYear/>
    <publishedYear>2024</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>345</pageFirst>
    <pageLast>351</pageLast>
    <pageNumber>7</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>ECMS</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Multi-Site Aggregate Production Planning With Resilience Consideration</title>
    <abstract language="eng">The recent years have shown a high frequency of disruptions like natural disasters or manmade disruptions, leading, for example, to transport routes or production facilities being unavailable for extended periods. Many manufacturing companies, which nowadays operate in a global production network, are heavily exposed to these disruptions. This results in both significant costs and substantial exceeding of promised deadlines. If it concerns the first company in a supply chain, it causes correspondingly significant delays in promised deadlines for subsequent companies in the supply chain, including a correspondingly significant increase in costs. Both are exemplified in this paper through a case study. This case study demonstrates that through resilience, both implications can be significantly reduced.</abstract>
    <parentTitle language="eng">Proceedings of the 38th ECMS International Conference on Modeling and Simulation (ECMS 2024): June 4th - June 7th, 2024, Cracow, Poland</parentTitle>
    <identifier type="isbn">978-3-937436-84-5</identifier>
    <identifier type="issn">2522-2422</identifier>
    <identifier type="doi">10.7148/2024-0345</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Chenghao Dai</author>
    <author>Maximilian Schön</author>
    <author>Thorsten Claus</author>
    <author>Frank Herrmann</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Production Planning and Control</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Aggregate Production Planning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Linear Programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Multi-Site Production Planning and Control</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Supply Chain Resilience</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16316">Produktion und Systeme</collection>
  </doc>
</export-example>
