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An Analysis of the Consumption Demand Data on The DLA's Lead-time Forecast Accuracy

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Abstract

The 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.

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LMI AND THE DLA WEAPON SYSTEM SUSTAINMENT PROGRAM

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2005-05-20T12:50:09Z

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forecast; forecast accuracy; fourier; double exponential smoothing

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Government Document

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article
dissertation or thesis

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