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WORKLOAD FORECASTING UNDER ERRATIC DEMAND USING FAST FOURIER TRANSFORM ALGORITHM

Authors: Onur KOYUNCU; Erdem TURFAN;

WORKLOAD FORECASTING UNDER ERRATIC DEMAND USING FAST FOURIER TRANSFORM ALGORITHM

Abstract

Forecasting process may become cumbersome under erratic demand structures where no conventional methodology seems to provide plausible outcomes. The company investigated in this paper is subject to this condition and needs to forecast the workload in order to plan the indispensable process enhancement activities. Two parameters to be forecasted are the total production volume and the ratio of in-house production ratio with respect to the total production. The required forecasts for relatively regular structured in-house production to total production ratio were computed via static forecasting. The more important erratic structured total production volume forecasts were computed using FFT (Fast Fourier Transform) algorithm. Total production was further observed during the next year to check the reliability of the forecasts. The resulting respective MAPEs (Mean Absolute Percentage Errors) of approximately 11% (in-house ratio) and 14-22% (total production) were considered acceptable under the erratic demand structure.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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