Integrating Forecasting and Inventory Decisions Using Machine Learning
Van der Haar, Joost F Sagaert, Yves
Van der Haar, Joost F
Sagaert, Yves
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Publication Type
Journal article with impact factor
Editor
Supervisor
Publication Year
2025
Journal
Foresight
Book
Publication Volume
Q3
Publication Issue
78
Publication Begin page
4
Publication End page
19
Publication Number of pages
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Abstract
Can inventory ordering decisions be improved by integrating forecasting and inventory decisions using machine learning? That is the question addressed in this study of three large Belgian companies in the food industry. Van der Haar, Sagaert, and Boute investigate the performance of methods that predict optimal order quantities directly, instead of !rst forecasting and then calculating optimal inventory quantities. Their results show that using an integrated approach can lead to substantial cost savings for smoother time series, yet the opposite holds when applying it to erratic and lumpy time series.
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Keywords
Forecasting