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dc.contributor.authorKumar, Vivek
dc.contributor.authorRobert, Lo
dc.contributor.authorLinda, Tsang
dc.date.accessioned2005-05-20T12:50:09Z
dc.date.available2005-05-20T12:50:09Z
dc.date.issued2005-05-20T12:50:09Z
dc.identifier.urihttps://hdl.handle.net/1813/1342
dc.description.abstractThe Defense Logistics Agency generates forecasts for demand from military service warehouses (wholesale demand) using a double exponential smoothing (DES) forecasting model. However, the Agency will be moving to a Fourier forecasting model, which explicitly accounts for seasonality in demand data. We found that obtaining additional demand data from the military maintenance centers (consumption demand) will improve lead-time forecast accuracy in both forecasting models. In addition, we found that different incorporations of the consumption demand data are needed depending on the accuracy metric utilized.en_US
dc.description.sponsorshipLMI AND THE DLA WEAPON SYSTEM SUSTAINMENT PROGRAMen_US
dc.format.extent800066 bytes
dc.format.extent1369461 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.subjectforecasten_US
dc.subjectforecast accuracyen_US
dc.subjectfourieren_US
dc.subjectdouble exponential smoothingen_US
dc.titleAn Analysis of the Consumption Demand Data on The DLA's Lead-time Forecast Accuracyen_US
dc.typearticleen_US
dc.typedissertation or thesisen_US


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