10.17559/TV-20160615204011

Demand forecasting: a comparison between the Holt-Winters, trend analysis and decomposition models

Abstract

U industriji proizvodnje hrane, predviđanje vremena potražnje je bitno u planiranju proizvodnje kako bi se na vrijeme zadovoljile potrebe kupaca. U literaturi se koristi nekoliko statističkih modela za planiranje potražnje u industriji hrane i pića, a izbor najpogodnijeg modela od osnovnog je značaja. U tom kontekstu cilj je ovoga rada usporedba primjenljivosti modela analize trenda, dekompozicije i Holt-Winters (HW) modela za predviđanje vremenskih serija u potražnji đema i voćnih sokova. Obrađeni su podaci jednog privatnog poduzeća od siječnja 2013 do prosinca 2014. Uspješnost se odredila metričkom analizom Mean Absolute Percentage Error (MAPE) (srednji apsolutni postotak greške). U ovom su radu najbolji rezultati u planiranju potražnje postignuti modelima Holt-Winters i dekompozicije.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

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