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Revista Cubana de Ciencias Informáticas
versión On-line ISSN 2227-1899
Resumen
PERDIGON LLANES, Rudibel; VILTRES SALA, Hubert y ORELLANA GARCIA, Arturo. Models for predicting perishable products demands in food trading companies. Rev cuba cienc informat [online]. 2020, vol.14, n.1, pp. 110-135. Epub 01-Mar-2020. ISSN 2227-1899.
Determining the demands for products and services is an issue of interest to the international scientific community and represents an effective tool to raise the economic profits and competitiveness of business in the market. Currently, research on models for forecasting perishable food demands is few compared to the amount of forecasting research in other fields. Accurate forecasting of perishable foods prevents the loss of these products and contributes to increased customer satisfaction. In this article, we conducted a systematic review of the literature on the main models for forecasting perishable food demands in small and medium enterprises developed during the period 2013-2018. The analysis of the available information allowed the authors to determine that forecasting methods using soft computing techniques and time series are the most used in the literature. The main input variables of these models and the factors that influence the variation in the demands were also determined.
Palabras clave : forecasting models; demands; perishable food; business.