Demand Sensing and Replenishment Intelligence: Neural Network-Driven Inventory Velocity Optimization in Omnichannel Retail

Authors

  • Imene Dahmane Professor of Computer Science

Keywords:

demand sensing, replenishment intelligence, neural network-driven inventory velocity optimization, omnichannel retail, machine learning

Abstract

Optimizing inventory turnover is a critical operational hurdle for a retailer looking to increase competitive advantage. As e-commerce continues to reshape consumer shopping behavior and competition becomes increasingly global, the need for leveraging technology to keep up with consumers' increasing demands rises as well. The role that a retailer's merchandise plays in its competitive strategy is determined largely by the return on assets metric of the firm.

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Published

31-12-2024

How to Cite

[1]
“Demand Sensing and Replenishment Intelligence: Neural Network-Driven Inventory Velocity Optimization in Omnichannel Retail”, Adv. in Deep Learning Techniques, vol. 4, no. 2, pp. 37–46, Dec. 2024, Accessed: Jun. 05, 2026. [Online]. Available: https://thesciencebrigade.com/adlt/article/view/765