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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Review

Machine Learning and Deep Learning Models for Demand Forecasting in Supply Chain Management: A Critical Review

by
Kaoutar Douaioui
1,*,
Rachid Oucheikh
2,*,
Othmane Benmoussa
3 and
Charif Mabrouki
1
1
Laboratory of Engineering, Industrial Management and Innovation, Faculty of Sciences and Techniques, Hassan 1st University, Settat 26000, Morocco
2
Physical Geography and Ecosystem Science, Lund University, Sölvegatan 12, 223 62 Lund, Sweden
3
Euromed Polytechnic School, Euromed University of Fes, Fez 30030, Morocco
*
Authors to whom correspondence should be addressed.
Appl. Syst. Innov. 2024, 7(5), 93; https://doi.org/10.3390/asi7050093
Submission received: 6 June 2024 / Revised: 25 August 2024 / Accepted: 23 September 2024 / Published: 26 September 2024
(This article belongs to the Special Issue Advancements in Deep Learning and Its Applications)
Versions Notes

Abstract

This paper presents a comprehensive review of machine learning (ML) and deep learning (DL) models used for demand forecasting in supply chain management. By analyzing 119 papers from the Scopus database covering the period from 2015 to 2024, this study provides both macro- and micro-level insights into the effectiveness of AI-based methodologies. The macro-level analysis illustrates the overall trajectory and trends in ML and DL applications, while the micro-level analysis explores the specific distinctions and advantages of these models. This review aims to serve as a valuable resource for improving demand forecasting in supply chain management using ML and DL techniques.
Keywords: AI-driven demand forecasting; supply chain; Scopus; literature review; macro-level analysis; micro-level evaluation AI-driven demand forecasting; supply chain; Scopus; literature review; macro-level analysis; micro-level evaluation

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MDPI and ACS Style

Douaioui, K.; Oucheikh, R.; Benmoussa, O.; Mabrouki, C. Machine Learning and Deep Learning Models for Demand Forecasting in Supply Chain Management: A Critical Review. Appl. Syst. Innov. 2024, 7, 93. https://doi.org/10.3390/asi7050093

AMA Style

Douaioui K, Oucheikh R, Benmoussa O, Mabrouki C. Machine Learning and Deep Learning Models for Demand Forecasting in Supply Chain Management: A Critical Review. Applied System Innovation. 2024; 7(5):93. https://doi.org/10.3390/asi7050093

Chicago/Turabian Style

Douaioui, Kaoutar, Rachid Oucheikh, Othmane Benmoussa, and Charif Mabrouki. 2024. "Machine Learning and Deep Learning Models for Demand Forecasting in Supply Chain Management: A Critical Review" Applied System Innovation 7, no. 5: 93. https://doi.org/10.3390/asi7050093

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