Machine learning applied to forecast intermittent demandin a plastic packaging company - Sánchez García, Alex Víctor (2024)
This article compares three demand forecasting methods applied to a Peruvian cosmetic plastic packaging company with intermittent demand. The comparison between the error metrics for forecasting Mean Absolute Error, Mean Percentage Error, and Mean Squared Error obtained by the Croston, Croston TSB, and Exponential Smoothing methods showed that the Croston TSB model outperformed the other two, with an error of less than 20 % compared to actual sales.