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2023 | OriginalPaper | Chapter

Forecasting in Shipments: Comparison of Machine Learning Regression Algorithms on Industrial Applications for Supply Chain

Authors : Nunzio Carissimo, Raffaele D’Ambrosio, Milena Guzzo, Sabino Labarile, Carmela Scalone

Published in: Computational Science and Its Applications – ICCSA 2023

Publisher: Springer Nature Switzerland

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Abstract

Supply chains are very complex systems and their correct and efficient management represents a fundamental challenge, in which the practical needs of the corporate world can find answers together with the advanced skills of the academic world. This paper fits exactly in this area. In particular, starting from a project by the company Code Architects, we will illustrate how it is possible to make forecasts on shipments with machine learning tools, which can support business decisions.

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Title: Forecasting in Shipments: Comparison of Machine Learning Regression Algorithms on Industrial Applications for Supply Chain
Authors: Nunzio Carissimo
Raffaele D’Ambrosio
Milena Guzzo
Sabino Labarile
Carmela Scalone
Publisher: Springer Nature Switzerland
Book: Computational Science and Its Applications – ICCSA 2023
Print ISBN: 978-3-031-36807-3

Electronic ISBN: 978-3-031-36808-0

Copyright Year: 2023
DOI: https://doi.org/10.1007/978-3-031-36808-0_33

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