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Artificial Intelligence-Driven Inventory Management: Optimizing Stock Levels and Reducing Costs Through Advanced Machine Learning Techniques

Osman Çaylı1✉,
Zeki Oralhan2
1VBT Yazılım A.Ş.
2Nuh Naci Yazgan University
Published:December 31, 2024
DOI: 10.56038/ejrnd.v4i4.615
Vol. 4, No. 4

Abstract

This study investigates the implementation of artificial intelligence (AI) algorithms to enhance inventory management processes in small and medium-sized enterprises (SMEs) within the retail sector. Accurate inventory level determination is a critical factor in improving organizational performance. Inventory levels are subject to a wide range of influences, including seasonal fluctuations, promotional campaigns, and macroeconomic conditions, which introduce significant complexity and variability. Such complexities often render manual management approaches inefficient. This research focuses on addressing these challenges through AI-based methodologies, particularly by employing machine learning and data analytics techniques to optimize inventory control. The findings of the study contribute to the literature by highlighting the potential of AI-driven approaches in reducing inventory costs and improving supply chain efficiency.

Keywords
Machine LearningLSTMAIInventory Management

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Cite This Article
Çaylı, O., Oralhan, Z. (2024). Artificial Intelligence-Driven Inventory Management: Optimizing Stock Levels and Reducing Costs Through Advanced Machine Learning Techniques. *The European Journal of Research and Development*, 4(4), 427-439. https://doi.org/10.56038/ejrnd.v4i4.615

Bibliographic Info

JournalThe European Journal of Research and Development
Volume4
Issue4
Pages427–439
PublishedDecember 31, 2024
eISSN2822-2296