A COMPREHENSIVE STUDY ON INTELLIGENT INVENTORY MANAGEMENT AND PRODUCT DEMAND FORECASTING USING MACHINE LEARNING TECHNIQUES

Abstract

 In the rapidly evolving Indian retail ecosystem efficient inventory management has become critical to maintaining product avail-ability while minimizing overstocking and understocking losses. Tradi-tional inventory control methods often fail to adapt to the complexity of local consumer behavior shaped by regional diversity seasonal demand shifts and culturally significant events such as festivals. This paper presents an intelligent inventory management system designed for In-dian retailers which integrates real time stock monitoring demand fore-casting and automated decision support. The proposed system lever-ages machine learning algorithms to analyze historical sales data pricing trends and temporal factors including weekdays seasons and festivals to generate predictive insights that guide stock replenishment.