12th Annual International Conference on Industrial Engineering and Operations Management

Artificial Intelligence Demand Forecasting Techniques in Supply Chain Management: A Systematic Literature Review

Saad El Marjani, Safae Er-Rbib & Loubna Benabbou
Publisher: IEOM Society International
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Track: Supply Chain Management
Abstract

Demand forecasting is one of the vital elements of the supply chain management (SCM). It is in constant need of development and improvement given its critical impact on the supply chain. Forecasting the demand should be performed to answer the needs of the customers using efficiently the available resources. We provide in this paper some overviews based on a systematic analysis of the related literature. The paper addresses different techniques and aeras of artificial intelligence (AI) adopted to determine and enhance the demand forecasting in SCM. The research aims at identifying AI techniques that can improve supply chain practices and fill the gaps in some interesting SCM fields, namely: Marketing, Production, Logistics and Supply Chain. We disclosed the most important aspects of the review such as: AI algorithms applied to different fields of the supply chain; potential AI techniques frequently used in demand forecasting and the different related subfields susceptible to be treated with these techniques. 

Published in: 12th Annual International Conference on Industrial Engineering and Operations Management, Istanbul, Turkey

Publisher: IEOM Society International
Date of Conference: March 7-10, 2022

ISBN: 978-1-7923-6131-9
ISSN/E-ISSN: 2169-8767