Application of Machine Learning in Supply Chain Management

Jiaming Luo ()
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Jiaming Luo: Southwestern University of Finance and Economics

A chapter in Proceedings of the 2022 3rd International Conference on Big Data Economy and Information Management (BDEIM 2022), 2023, pp 489-498 from Springer

Abstract: Abstract With the continuous development of information technology, machine learning, and other artificial intelligence technology has gradually developed and perfected. Supply chain management is an important link in business, its importance is self-evident. Supply chain management is to make the supply chain operation achieve optimization, with the least cost, so that the supply chain from procurement to meet the final customer all the process. It is closely connected with China’s economy and society and develops rapidly. This article will explore the convergence of machine learning techniques and supply chain management. After reviews of machine learning techniques, this paper introduces several commonly used machine learning techniques, and then studies the application of support vector machines and decision trees in the field of supply chain management, and enumerates the corresponding successful cases. Finally, the possible future development direction of machine learning technology is proposed. In this paper, the machine learning technology and its application are summarized and the future development of this technology prospects.

Keywords: Machine learning; supply chain management; support vector machine; logistic regression (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-124-1_58

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DOI: 10.2991/978-94-6463-124-1_58

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