Preliminary communication
https://doi.org/10.17559/TV-20160615204011
Demand forecasting: a comparison between the Holt-Winters, trend analysis and decomposition models
Güzin Tirkeş
orcid.org/0000-0003-0884-4876
; Atılım University, Faculty of Engineering, Dept. of Computer Engineering, Kızılcaşar Mahallesi, 06830 Gölbaşı/Ankara, Turkey
Cenk Güray
; Yıldırım Beyazıt University, Güvenevler Mahallesi, Cinnah Cd. No. 16, 06690 Çankaya/Ankara, Turkey
Neş’e Çelebi
; Atılım University, Faculty of Engineering, Dept. of Industrial Engineering, 06836 İncek/Ankara, Turkey
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.
Keywords
decomposition; demand forecasting; food industry; Holt-Winters; time series
Hrčak ID:
186094
URI
Publication date:
2.9.2017.
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