Machine Learning in Different Applications of Supply - based Chain Management Systems
Abstract: This paper explores the ways different machine learning (ML) algorithms are applied to different areas of supply - based chain management systems. The demand for Machine learning technology is increasing, so supply ? based chain management has become more efficient, effective, and sustainable. This paper analyzes various Machine learning techniques and algorithms, such as clustering, classification, and regression are helpful in improvising supply chains processes such as demand forecasting, inventory management, and logistics optimization. It also explains the challenges associated with mapping ML algorithms with SCM systems. Through this analysis, this paper concludes that Machine learning has excellent potential in enhancing supply ? based chain management systems and is an essential tool for businesses to sustain market competition intact.
Keywords: Machine Learning, supply chain management, Artificial Intelligence
How to Cite?: Gurjapna Anand, "Machine Learning in Different Applications of Supply - based Chain Management Systems", Volume 12 Issue 7, July 2023, International Journal of Science and Research (IJSR), Pages: 1207-1210, https://www.ijsr.net/getabstract.php?paperid=SR23626111517, DOI: https://dx.doi.org/10.21275/SR23626111517