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                <identifier>oai:data.mendeley.com/f3bs7xkfsf.1</identifier>
                <datestamp>2022-06-09T15:51:48Z</datestamp>
            </header>
            <metadata><oai_dc:dc xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
    <dc:creator id="https://orcid.org/0000-0001-6360-2162">Azzamouri, Ahlam</dc:creator>
    <dc:title>Impact of the continuous and periodic assessment of a buffer replenishment on the DDMRP method</dc:title>
    <dc:publisher>Mendeley Data</dc:publisher>
    <dc:description>Like Kanban or classic inventory management, Demand Driven Material Requirements Planning (DDMRP) assumes that an order is created when the stock level drops below a given level. The assessment of this level can be continuous or periodic. A periodic evaluation can force better repartition of the load over time. DDMRP characterizes the demand for a product by its average daily demand. This aggregation specifies neither the average size of the elementary demands nor the average duration between two elementary demands. Based on a discrete event simulation model, this study suggests that, at least for a flow-shop organization, the DDMRP method, with continuous order generation, is suitable for large mean time between elementary orders, while periodic observation improves the method for small values of it.</dc:description>
    <dc:subject>Discrete Simulation</dc:subject>
    <dc:subject>Inventory Management</dc:subject>
    <dc:contributor id="https://orcid.org/0000-0002-6410-3928">baptiste, pierre</dc:contributor>
    <dc:contributor id="https://orcid.org/0000-0001-7486-3579">Pellerin, Robert</dc:contributor>
    <dc:contributor id="https://orcid.org/0000-0001-5056-7900">Dessevre, Guillaume</dc:contributor>
    <dc:type>Dataset</dc:type>
    <dc:identifier>doi:10.17632/f3bs7xkfsf.1</dc:identifier>
    <dc:identifier>oai:data.mendeley.com/f3bs7xkfsf.1</dc:identifier>
    <dc:rights>Creative Commons Attribution 4.0 International</dc:rights>
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    <dc:date>2022-06-09T15:51:48Z</dc:date>
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