Demand-Supply Synchronisation Through Predictive Modelling: A Machine Learning Framework for End-to-End Supply Chain Optimisation

Authors

  • Charalampos Stylios Professor of Electrical and Computer Engineering, National and Kapodistrian University of Athens

Keywords:

demand-supply synchronisation, predictive modelling, machine learning framework, end-to-end supply chain optimisation

Abstract

In the contemporary global marketplace, supply chain management and operational efficiency are key to success. Supply chains need to be able to adapt and plan for changing customer and business requirements but are often measured on how efficiently resources are used within their operations, since a highly efficient supply chain is a cost-effective one and a cost-effective supply chain can offer increased return on investment for both suppliers and customers.

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Published

31-12-2023

How to Cite

[1]
“Demand-Supply Synchronisation Through Predictive Modelling: A Machine Learning Framework for End-to-End Supply Chain Optimisation”, Blockchain Tech. & Distributed Sys., vol. 3, no. 2, pp. 40–50, Dec. 2023, Accessed: Jun. 05, 2026. [Online]. Available: https://thesciencebrigade.com/btds/article/view/845