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  <doc>
    <id>6480</id>
    <completedYear/>
    <publishedYear>2022</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>142</pageNumber>
    <edition>1. Auflage</edition>
    <issue/>
    <volume>2022</volume>
    <type>doctoralthesis</type>
    <publisherName>Cuvillier Verlag</publisherName>
    <publisherPlace>Göttingen</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Betrachtung der inhärenten Stochastizität durch das Scheduling in Verbindung mit der mehrstufigen Losbildung in einem hierarchischen Planungskonzept</title>
    <abstract language="deu">In der Dissertationsschrift „Betrachtung der inhärenten Stochastizität durch das Scheduling in Verbindung mit der mehrstufigen Losbildung in einem hierarchischen Planungskonzept“ werden mehrere Modellformulierungen für die Lösung von mehrstufigen kapazitierten Losgrößenproblemen erarbeitet. Bei der Losgrößenplanung mit Mikroperiodenmlodelen entstehen durch die üblicherweise integrierte Reihenfolgeplanung keine Verspätungen durch Wartezeiten. Jedoch sind die Rechenzeiten für optimale Lösungen in praxisrelevanten Problemgrößen nahezu unbeherrschbar. Bei einer Lösung mit Makroperiodenmodellen und einer nachfolgenden Reihenfolgeplanung mit Prioritätsregeln entstehen hingegen durch die unzureichenden Kapazitätsberechnungen immer wieder unvorhergesehene Wartezeiten. Deshalb werden in der Arbeit drei Modifikationen für das Makroperiodenmodell MLCLSP vorgeschlagen, mit denen diese Wartezeiten geschätzt werden können. Im ersten Ansatz werden Kapazitätskorrekturfaktoren eingeführt und deren Werte simulativ ermittelt, womit das Problem der reihenfolgebedingten Wartezeiten teilweise behoben werden kann. In einem zweiten Modellvorschlag werden diese Kapazitätskorrekturfaktoren mit einer Analogie aus der Warteschlangetheorie geschätzt. Ein drittes Modell wird vorgeschlagen, in dem ein Parameter eingeführt wird mit dem die Robustheit gegenüber der inhärenten Stochastizität zwischen den Losgrößen- und Scheduling-Problemen gesteuert werden kann.</abstract>
    <identifier type="isbn">9783736975958</identifier>
    <enrichment key="TitelVerleihendInstitution">Universität Duisburg-Essen, Fakultät für Betriebswirtschaftslehre</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>Maximilian Munninger</author>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Hierarchische Produktionsplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Mehrstufige kapazitierte Losgrößenplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Materialbedarfsplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Scheduling</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Reihenfolgeplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Ressourceneinsatzplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Robuste Planung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Makroperiodenmodelle</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Big-Bucket-Modelle</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Sukzessivplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>MLCLSP</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Multi-level Capacitated Lotsizing Problem</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Kapazitätskorrekturfaktoren</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Warteschlangentheorie</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Verspätungen</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>gemischt-ganzzahlige lineare Optimierung</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Operations Research</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Werkstattfertigung</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Hierarchical production planning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Multi-level Capacitated Lotsizing Problem</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Material requirements planning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Scheduling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Robust planning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Big-Bucket-Models</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Consecutive planning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Capacity Correction Factors</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Queueing Theory</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Tardiness</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>mixed-integer linear programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Job shop</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>stochasticity</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Stochastizität</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Kapazitätslotsenproblem</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Zentrale Recheneinheit</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>capacity correction factors</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Arbeitsgangfolge</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>work sequence</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Lagerkosten</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>storage costs</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Totalplanungsmodelle</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>total planning models</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>gleichgestellte Partialmodelle</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>equivalent partial models</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Beschäftigungsglättung</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>employment smoothing</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Direktbedarfskoeffizient</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>direct demand coefficient</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Produktionslogistik</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>production logistics</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Informationstechnik</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>information technology</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>simulation software</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Simulationssoftware</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>delay values</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Verzögerungswerte</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Rüstzeit</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>set-up time</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Mindestvorlaufzeit</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>minimum lead time</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16316">Produktion und Systeme</collection>
    <collection role="othpublikationsherkunft" number="">Dissertation in Kooperation</collection>
  </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>300</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>ACM</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2020-02-13</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Scheduling tardiness constrained flow shop with simultaneously loaded stations using Genetic Algorithm</title>
    <abstract language="eng">In this study, a real world flow shop with a transportation restriction is regarded. This restriction reduces the set of feasible schedules even more than the no-buffer restrictions discussed in the literature in the case of limited storage. Still this problem is NP-hard. Since this scheduling problem is integrated in the usual hierarchical planning, the tardiness is minimised. Compared to even specific priority rule for this class of problems the suggested genetic algorithm delivers significant better results. The specific structure of this class of problems complicates the calculation of the performance criteria. This is solved by a simulation algorithm.</abstract>
    <parentTitle language="eng">Proceedings of the 4th International Conference on Intelligent Systems, Metaheuristics &amp; Swarm Intelligence (ISMSI 2020): Thimphu, Kingdom of Bhutan during March 21-22, 2020</parentTitle>
    <identifier type="doi">10.1145/3396474.3396475</identifier>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Donald Davendra</author>
    <author>Frank Herrmann</author>
    <author>Magdalena Bialic-Davendra</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>simulation of restrictions</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>scheduling,</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>flow-shop</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>no-buffer (blocking)</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>no-wait</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>genetic algorithm</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>real world application</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Ablaufplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Hierarchische Produktionsplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Flow-shop-Problem</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Reihenfolgeproblem</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Genetischer Algorithmus</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>219</id>
    <completedYear/>
    <publishedYear>2013</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>775</pageFirst>
    <pageLast>781</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 based priority rules for scheduling of a flow shop with simultaneously loaded stations</title>
    <abstract language="eng">In this study, a real world flow shop with a transportation restriction is regarded. This restriction reduces the set of feasible schedules even more than the no-buffer restrictions discussed in the literature in the case of limited storage. Since this scheduling problem is integrated in the usual hierarchical planning, the tardiness is minimised. This NP-hard problem is solved by priority rules, because of the addressed dynamic environment (and a high number of jobs) at the company site. Due to the technological restrictions the real duration of a job is significantly larger than its net processing time. By a simulation of the processing time many priority rules are improved and some even significantly. With extensive simulations successful priority rules in the literature are analysed.</abstract>
    <parentTitle language="eng">Proceedings of the 27th EUROPEAN Conference on Modeling and Simulation, May 27th - 30th, 2013, Ålesund, Norway</parentTitle>
    <identifier type="doi">10.7148/2013-0775</identifier>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <author>Frank Herrmann</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>simulation of processing time</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>scheduling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>flow-shop</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>no-buffer (blocking)</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>no-wait</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>priority rules</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>real world application</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Hierarchische Produktionsplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Flow-shop-Problem</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Reihenfolgeproblem</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>265</id>
    <completedYear/>
    <publishedYear>2014</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <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">Order release within hierarchical production planning and control using product specific clearing functions</title>
    <parentTitle language="eng">Proceedings of the International Annual Conference of the German Operations Research Society 2014 (OR 2014), Aachen, September 2 - 5, 2014, Germany</parentTitle>
    <author>Frank Herrmann</author>
    <author>Frederick Lange</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>Auftragsabwicklung</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>clearing functions</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>264</id>
    <completedYear/>
    <publishedYear>2014</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <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">Capacity estimation based on clearing functions for the capacitated lot-sizing problem</title>
    <abstract language="eng">Single-stage capacitated lot-sizing problems (CLSP) are essential for manyplanning  tasks in  production  systems. Due to the hierarchical  planning  approach, which is widely used in industrial practice and implemented in commercial enterprise resource planning as well as production planning and controlsystems, a subsequent scheduling is  necessary to gain executable productionplans. Capacity consumption depends on many factors as, for example, systems workload, machine  availability, or yield.  Thus, a feasible and optimalsolution of the CLSP may lead to unplanned delays after sequencing and processing the orders on the shop floor. Using a so called clearing function (CF),which represents the relationship between the workload and the output of a production system, this capacity consumption in a CLSP is improved in various ways and tested on a real-world application.</abstract>
    <parentTitle language="eng">Proceedings of the 5th International Workshop on Lot-Sizing, August 26th - 29th, 2014, Porto, Portugal</parentTitle>
    <identifier type="url">https://www.emse.fr/~absi/IWLS2014/proceedings_IWLS_2014.pdf</identifier>
    <author>Frank Herrmann</author>
    <author>Frederick Lange</author>
    <author>Christian Almeder</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Hierarchische Produktionsplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Kapazitätsplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Losgröße</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>clearing functions</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>262</id>
    <completedYear/>
    <publishedYear>2014</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <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">Genetic algorithm with simulation for scheduling of a flow shop with simultaneously loaded stations</title>
    <abstract language="eng">In this study, a real world flow shop with a transportation restriction is regarded. This restriction reduces the set of feasible schedules even more than the no-buffer restrictions discussed in the literature in the case of limited storage. Still this problem is NP-hard. Since this scheduling problem is integrated in the usual hierarchical planning, the tardiness is minimised. Compared to even specific priority rule for this class of problems the suggested genetic algorithm delivers significant better results. The specific structure of this class of problems complicates the calculation of the performance criteria. This is solved by a simulation algorithm. Proceedings 28th European Conference on Modelling and Simulation.</abstract>
    <parentTitle language="eng">Proceedings of the 28th EUROPEAN Conference on Modeling and Simulation, May 27th - 30th, 2014, Brescia, Italy</parentTitle>
    <identifier type="url">http://www.scs-europe.net/dlib/2014/ecms14papers/simo_ECMS2014_0076.pdf</identifier>
    <author>Frank Herrmann</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Ablaufplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Hierarchische Produktionsplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Flow-shop-Problem</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Reihenfolgeproblem</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Genetischer Algorithmus</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>simulation of restrictions</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>scheduling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>flow-shop</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>no-buffer (blocking)</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>no-wait</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>genetic algorithm</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>real  world  application</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>273</id>
    <completedYear/>
    <publishedYear>2016</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2020-02-05</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Social and Ecological Capabilities for a sustainable Hierarchical Production Planning</title>
    <abstract language="eng">Production planning and production control mainly focus on optimising the entire production system of a company. On the basis of hierarchical planning as a suitable method for solving this task, this paper shows - besides the economic dimension taken into account so far - that there are also social and ecological effects which will have to be considered in the process of planning. For this purpose, we would like to indicate here which social and ecological parameters can be or have already been taken into account for master production scheduling, for lot sizing and resource scheduling. As a result, an overview has been created which presents the existing concepts of sustainable production planning and production control as well as the existing deficits regarding the sustainability perspective.</abstract>
    <parentTitle language="eng">Proceedings of the 30th EUROPEAN Conference on Modeling and Simulation (ECMS 2016), May 31st - June 3rd, 2016, Regensburg, Germany</parentTitle>
    <identifier type="doi">10.7148/2016-0432</identifier>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Marco Trost</author>
    <author>Thorsten Claus</author>
    <author>Enrico Teich</author>
    <author>Maximilian Selmair</author>
    <author>Frank Herrmann</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Hierarchische Produktionsplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Soziale Verantwortung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Ökologie</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>production planning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>hierarchical planning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>social variables</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>ecological variables</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>sustainable 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>277</id>
    <completedYear/>
    <publishedYear>2016</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>4 S.</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2020-02-05</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Die soziale Dimension in der nachhaltigen hierarchischen Produktionsplanung – Stand der Forschung und Ansätze zur Weiterentwicklung bestehender Planungsmodelle</title>
    <abstract language="deu">Bei der  Produktionsplanung steht die Optimierung des Produktionssystems eines Unternehmens im Vordergrund. In diesem Beitrag wird auf Basis der hierarchischen Produktionsplanung aufgezeigt, dass neben ökonomischen und ökologischen Aspekten insbesondere auch soziale Effekte bei der Entscheidungsfindung zu berücksichtigen sind. Dazu werden für  die Hauptproduktionsprogrammplanung, die Losgrößenplanung und die  Ressourcenbelegungsplanung dargelegt, welche sozialen Größen berücksichtigt werden können  beziehungsweise bereits berücksichtigt sind. Überdies wird ein  Modellansatz zur Hauptproduktionsprogrammplanung vorgestellt, der auf die Beseitigung identifizierter Forschungslücken abzielt.</abstract>
    <parentTitle language="deu">Proceedings zur NAMA 2016 (NAMA 2016), October 5th - 7th, 2016, Dresden, Germany</parentTitle>
    <author>Marco Trost</author>
    <author>Thorsten Claus</author>
    <author>Enrico Teich</author>
    <author>Frank Herrmann</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Hierarchische Produktionsplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Nachhaltigkeit</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Soziale Verantwortung</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>195</id>
    <completedYear/>
    <publishedYear>2017</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>155</pageFirst>
    <pageLast>162</pageLast>
    <pageNumber/>
    <edition/>
    <issue>2</issue>
    <volume>23</volume>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2020-01-21</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Can Aggregate Production Planning (APP) be modified to be as good as Master Production Scheduling (MPS)</title>
    <abstract language="deu">In diesem Beitrag wird anhand einer Fallstudie die Bedeutung der Hauptproduktionsprogrammplanung (HPPLAN) für die hierarchische Produktionsplanung herausgearbeitet werden. Dazu wird versucht das Ergebnis der aggregierten Gesamtplanung (AGGRPLAN) durch Veränderung einzelner Paramater so zu verbessern, dass es dem Ergebnis der HPPLAN entspricht. Im Rahmen der Untersuchungen konnten dabei Verbesserungen für einzelne Planungssituationen erzielt werden, eine generelle Lösung konnte jedoch nicht gefunden werden. Insbesondere der Einsatz eines geeigneten Kapazitätsreduktionsfaktors in Verbindung mit der Berücksichtigung der Durchlaufzeit führt zu einer Verbesserung der Lösung. Bei der Planung von mehr als einem Produkt ist allerdings schwierig einen geeigneten Kapazitätsreduktionsfaktor zu finden, da dieser abhängig von der Nachfrage ist.</abstract>
    <parentTitle language="eng">ACC Journal</parentTitle>
    <identifier type="doi">10.15240/tul/004/2017-2-012</identifier>
    <enrichment key="ConferenceStatement">The 13th International Conference Liberec Economic Forum, 11th - 13th September 2017, Liberec, Czech Republic, EU</enrichment>
    <author>Thorsten Vitzthum</author>
    <author>Thorsten Claus</author>
    <author>Frank Herrmann</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>Fallstudie</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Hierarchical production planning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Aggregate production planning (APP)</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Master production scheduling (MPS)</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Material requirement planning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Resource profiles</value>
    </subject>
    <collection role="ddc" number="67">Industrielle Fertigung</collection>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="oaweg" number="">Gold Open Access- Erstveröffentlichung in einem/als Open-Access-Medium</collection>
    <collection role="othforschungsschwerpunkt" number="16316">Produktion und Systeme</collection>
  </doc>
  <doc>
    <id>201</id>
    <completedYear/>
    <publishedYear>2017</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>71</pageFirst>
    <pageLast>80</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>25</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2020-01-21</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Ein lineares Optimierungsmodell zur Hauptproduktionsprogrammplanung mit Berücksichtigung sozialer Größen</title>
    <abstract language="deu">Aufgrund weniger existenter sozialorientierter Forschungen im Rahmen der Produktionsplanung und -steuerung stellt dieser Beitrag ein lineares Optimierungsmodell für die Hauptproduktionsprogrammplanung vor, welches soziale Kriterien berücksichtigt. Erste Ergebnisse deuten an, dass geringe Kosten nicht durch eine maximierte Mitarbeiterauslastung entstehen sondern durch geringe Kapazitätsschwankungen.</abstract>
    <parentTitle language="deu">uwf UmweltWirtschaftsForum</parentTitle>
    <identifier type="doi">10.1007/s00550-017-0454-7</identifier>
    <author>Marco Trost</author>
    <author>Enrico Teich</author>
    <author>Thorsten Claus</author>
    <author>Frank Herrmann</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Sustainability</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Social dimension</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Production planning and control</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Master production scheduling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Linear optimisation</value>
    </subject>
    <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>Personaleinsatz</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Lineare 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>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>199</id>
    <completedYear/>
    <publishedYear>2017</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2020-01-21</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Evidence of the Relevance of Master Production Scheduling for Hierarchical Production Planning.</title>
    <abstract language="eng">This paper deals with the significance of master production scheduling for hierarchical production planning. Production planning in a typical manufacturing organization is a sequence of complex decisions which depends on a number of factors, such as number of products, complexity of products, number of production sites, and number of work centres in each production site. The main idea in hierarchical production planning is to break down larger problems into smaller, more manageable sub problems. Starting with aggregate production planning, the benefits of using master production scheduling for material requirements planning will be conveyed. The main benefit of master production scheduling is more detailed planning. The production groups are thereby disaggregated into final products and the production site disaggregated into work centres. In order to plan capacities, resource profiles are used. By working with resource profiles production lead time data are taken into account to provide time-phased projections of the capacity requirements for each work centre (Vollmann et al. 2005). The case study will show that more accurate planning and consideration of production lead time through master production scheduling results in a demand program that can be realized without shortages or delays.</abstract>
    <parentTitle language="eng">Proceedings, 31st European Conference on Modelling and Simulation (ECMS) 2017, 23rd - May 26th, Budapest, Hungary</parentTitle>
    <identifier type="isbn">978-0-9932440-4-9</identifier>
    <identifier type="doi">10.7148/2017-0475</identifier>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Thorsten Vitzthum</author>
    <author>Frank Herrmann</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Hierarchische Produktionsplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Fertigungsprogrammplanung</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>
</export-example>
