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<export-example>
  <doc>
    <id>3900</id>
    <completedYear/>
    <publishedYear>2021</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferencepresentation</type>
    <publisherName>TU Berlin</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Berücksichtigung stochastischer Einflüsse bei der Hauptproduktionsprogrammplanung</title>
    <parentTitle language="deu">Im Mix der Methoden - Neue Perspektiven der Produktionswirtschaft. 1. Doktorandenworkshop der Wissenschaftlichen Kommission für Produktionswirtschaft, 19./20. März 2021, Berlin</parentTitle>
    <author>Julian Englberger</author>
    <author>Frank Herrmann</author>
    <author>Michael Manitz</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16316">Produktion und Systeme</collection>
  </doc>
  <doc>
    <id>232</id>
    <completedYear/>
    <publishedYear>2012</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferencepresentation</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2020-01-29</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A simulation analysis of Independent Requirements Consumption in Master Production Scheduling</title>
    <abstract language="eng">This  poster  presents  purpose  and  function  of  the  Independent  Requirements  Consumption  in Master Production Scheduling and gives recommendations for its application. The approach of hierarchical production planning and its planning problems are explained. The problem of new customer  requirements  information  between  planning  periods  and  solving  options  are  shown. The solving option of Independent Requirements Consumption is focus of this poster. The algorithm of the Independent Requirements Consumption that is implemented in commercial Enterprise Resource Planning (ERP) systems like the SAP system is analyzed. The methods for analyzing the effects of the Independent Requirements Consumption are outlined. The scenarios for simulation studies are stated and compared  to  similar  investigations.  The simulation studies were performed on a simulation  system  at IPF that contains both a production planning and control system and a production. The extent of simulation analyses outreaches similar investigations, especially because of the variety of scenarios. For scenarios in which capacity is available to a sufficient extent, advice for setting the Independent Requirements Consumption parameters is given. It is pointed out that with production constrained scenarios, the necessity to level out production  leads to problems. An algorithm to determine necessary  inventory levels is presented. It is stated that straight advice for  Independent Requirements Consumption parameter settings might not be possible with production constrained scenarios. Further analyses with production constrained scenarios as well as investigations concerning safety stocks in combination with Independent Requirements Consumption are current and future research topics at the Innovation Center for Production Logistics and Factory Planning.</abstract>
    <parentTitle language="eng">ASIM Workshop, Trends in Computational Science and Engineering (ASIM TCSE 2012), February 13-14, 2012, Vienna University of Technology, Austria</parentTitle>
    <author>Julian Englberger</author>
    <author>Frank Herrmann</author>
    <author>Thorsten Claus</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Produktonsplanung</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Simulation analysis</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Independent Requirements Consumption</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Master Production Scheduling</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Enterprise-Resource-Planning</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Kundenorientierung</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>
  </doc>
  <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>
  <doc>
    <id>221</id>
    <completedYear/>
    <publishedYear>2013</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>794</pageFirst>
    <pageLast>800</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2020-01-29</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Simulation of robust  Master Production Scheduling in an industrially relevant planning environment</title>
    <abstract language="eng">This paper presents a simulation analysis on the effects of robust master production scheduling. Up to now, relatively highly aggregated planning models for robust master production scheduling were regarded and the realizability of the planning results was not considered. This paper analyses a more detailed model for master production scheduling than in previous works. The evaluation of the planning results is made by providing the planning results to the subsequent planning levels in a hierarchical production planning system and realizing them in a realistic production system. The primary objective of the production system is to minimise tardiness of customer order deliveries. The secondary objective is to minimise inventory of end products. It is shown that robust master production scheduling in such a planning system leads to significant reductions of tardiness of customer order shipment. Compared to an equivalent deterministic approach for master production scheduling, the mean customer order backlog is reduced more than the mean inventory levels are increased.</abstract>
    <parentTitle language="eng">Proceedings of the 27th EUROPEAN Conference on Modeling and Simulationn, May 27th - 30th, 2013, Ålesund, Norway</parentTitle>
    <identifier type="doi">10.7148/2013-0794</identifier>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <author>Julian Englberger</author>
    <author>Frank Herrmann</author>
    <author>Thorsten Claus</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Hierarchische Produktionsplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Auftragsabwicklung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Optimierung</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>robust optimisation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>production planning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>simulation</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>
  </doc>
  <doc>
    <id>229</id>
    <completedYear/>
    <publishedYear>2012</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>Vol. 1(1)</volume>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2020-01-29</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Independent Requirements Consumption in Master Production Scheduling in an Uncapacitated Environment</title>
    <parentTitle language="eng">Informatics, Microsystems, Information Systems. Proceedings. 2012</parentTitle>
    <identifier type="isbn">9785733909301</identifier>
    <author>Julian Englberger</author>
    <author>Frank Herrmann</author>
    <author>Thorsten Claus</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Produktionsplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Kundenorientierung</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16316">Produktion und Systeme</collection>
  </doc>
  <doc>
    <id>202</id>
    <completedYear/>
    <publishedYear>2016</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>6192</pageFirst>
    <pageLast>6215</pageLast>
    <pageNumber/>
    <edition/>
    <issue>20</issue>
    <volume>54</volume>
    <type>article</type>
    <publisherName>Taylor &amp; Francis</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2020-01-21</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Two-stage stochastic master production scheduling under demand uncertainty in a rolling planning environment</title>
    <abstract language="eng">This paper proposes a scenario-based two-stage stochastic programming model with recourse for master production scheduling under demand uncertainty. We integrate the model into a hierarchical production planning and control system that is common in industrial practice. To reduce the problem of the disaggregation of the master production schedule, we use a relatively low aggregation level (compared to other work on stochastic programming for production planning). Consequently, we must consider many more scenarios to model demand uncertainty. Additionally, we modify standard modelling approaches for stochastic programming because they lead to the occurrence of many infeasible problems due to rolling planning horizons and interdependencies between master production scheduling and successive planning levels. To evaluate the performance of the proposed models, we generate a customer order arrival process, execute production planning in a rolling horizon environment and simulate the realisation of the planning results. In our experiments, the tardiness of customer orders can be nearly eliminated by the use of the proposed stochastic programming model at the cost of increasing inventory levels and using additional capacity.</abstract>
    <parentTitle language="eng">International Journal of Production Research</parentTitle>
    <identifier type="doi">10.1080/00207543.2016.1162917</identifier>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Julian Englberger</author>
    <author>Frank Herrmann</author>
    <author>Michael Manitz</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Hierarchische Produktionsplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Fertigungsprogrammplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Nachfrageverhalten</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Stochastische Optimierung</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Master production scheduling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Demand uncertainty</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Two-stage stochastic programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Scenario-based stochastic programming with recourse</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Hierarchical production planning</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>
  </doc>
  <doc>
    <id>217</id>
    <completedYear/>
    <publishedYear>2013</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2020-01-29</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Estimating Capacity Load Factors in Master Production Scheduling by the use of Stochastic Optimization</title>
    <parentTitle language="deu">Tagungsband zu der Tagung Logistikmanagement 2013, 10. - 13. Oktober 2013, Bremen, Deutschland</parentTitle>
    <author>Julian Englberger</author>
    <author>Frank Herrmann</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Produktionsplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Ablaufplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Kapazitätsplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Stochastische Optimierung</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>
  </doc>
  <doc>
    <id>2758</id>
    <completedYear/>
    <publishedYear>2021</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>39</pageFirst>
    <pageLast>61</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>bookpart</type>
    <publisherName>Springer Gabler</publisherName>
    <publisherPlace>Berlin, Heidelberg</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Robuste Optimierung zur Produktionsprogrammplanung</title>
    <parentTitle language="deu">Produktionsplanung und -steuerung</parentTitle>
    <identifier type="isbn">978-3-662-64290-0</identifier>
    <identifier type="doi">10.1007/978-3-662-64291-7_4</identifier>
    <enrichment key="opus.import.date">2022-02-09T06:20:59+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Frank Herrmann</author>
    <author>Julian Englberger</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16316">Produktion und Systeme</collection>
  </doc>
  <doc>
    <id>5612</id>
    <completedYear/>
    <publishedYear>2022</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>16</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>15</volume>
    <type>article</type>
    <publisherName>Bundesvereinigung Logistik (BVL) e.V.</publisherName>
    <publisherPlace>Bremen</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Master production scheduling with scenario-based capacity-load factors in a rolling planning environment</title>
    <abstract language="eng">This paper proposes two stochastic programming models for master production scheduling with capacity-load factor scenarios. In contrast to other work on production planning with load-dependent lead times or dynamic capacity loads, we iteratively build a set of realistic capacity-load factor scenarios by simulating the realization of the master production schedules in a rolling horizon environment. Therefore, we integrate the models into a hierarchical production planning and control system that is common in industrial practice and measure the effective capacity-load factors. With these factors, we resolve the master production scheduling problem. Toa evaluate the performance of the proposed models, we compare the stochastic models with the common approach to reduce the nominally available capacity for master production scheduling. In our experiments, the stochastic models signiﬁcantly reduce the tardiness of production orders caused by capacity bottlenecks.</abstract>
    <parentTitle language="eng">Logistics Research, Special Issue “Supply Chain Analytics in the 2020s”</parentTitle>
    <identifier type="doi">10.23773/2022_12</identifier>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Julian Englberger</author>
    <author>Frank Herrmann</author>
    <author>Michael Manitz</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16316">Produktion und Systeme</collection>
  </doc>
</export-example>
