Online Demand Sensing and Inventory Allocation Intelligence: A Real-Time Reinforcement Learning Framework for Supply-Demand Matching

Authors

  • Svetlana Glazkova Associate Professor of Applied Mathematics and Informatics, Belarusian State University

Keywords:

online demand sensing, inventory allocation intelligence, real-time reinforcement learning framework, supply-demand matching, machine learning

Abstract

Understanding the dynamics of demand and supply in real time can be very beneficial, especially in today's volatile and highly competitive market environment. For instance, some online retailers offer items for sale that are already in transit. Estimations of future demand, which are the output of sophisticated data-driven methods, are used in real-time logistics optimization systems.

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Published

30-06-2025

How to Cite

[1]
“Online Demand Sensing and Inventory Allocation Intelligence: A Real-Time Reinforcement Learning Framework for Supply-Demand Matching”, Blockchain Tech. & Distributed Sys., vol. 5, no. 1, pp. 44–51, Jun. 2025, Accessed: Jun. 05, 2026. [Online]. Available: https://thesciencebrigade.com/btds/article/view/857