DEMAND FORECASTING: A COMPARISON BETWEEN THE HOLT-WINTERS, TREND ANALYSIS AND DECOMPOSITION MODELS
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Date
2017
Journal Title
Journal ISSN
Volume Title
Publisher
Univ Osijek, Tech Fac
Abstract
In food production industry, forecasting the timing of demands is crucial in planning production scheduling to satisfy customer needs on time. In the literature, several statistical models have been used in demand forecasting in Food and Beverage (F&B) industry and the choice of the most suitable forecasting model remains a central concern. In this context, this article aims to compare the performances between Trend Analysis, Decomposition and Holt-Winters (HW) models for the prediction of a time series formed by a group of jam and sherbet product demands. Data comprised the series of monthly sales from January 2013 to December 2014 obtained from a private company. As performance measures, metric analysis of the Mean Absolute Percentage Error (MAPE) is used. In this study, the HW and Decomposition models obtained better results regarding the performance metrics.
Description
Turkmen, Guzin/0000-0003-0884-4876
Keywords
decomposition, demand forecasting, food industry, Holt-Winters, time series
Turkish CoHE Thesis Center URL
Citation
10
WoS Q
Q4
Scopus Q
Q3
Source
Volume
24
Issue
Start Page
503
End Page
509