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@article{179025,
        author = {Devi Sathvika Chilamkuri and Ayisha Nazeer Mohammed and Merlyn Rani R and Dr.Sakthivel S},
        title = {Algorithmic approaches to Inventory Forecasting},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {7080-7085},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179025},
        abstract = {The implementation of algorithms in the field of Inventory Forecasting system for minimizing business costs, optimizing stock levels and meeting customer demands efficiently. The key for Inventory Forecasting focuses on the flow of the stocks from the manufacturers to warehouses and from manufacturers to sales point. This leverages historical sales data, market trends, and advanced forecasting techniques to predict the demand of the product in the future. We maintain stocks to make certain that the proper quantity of stock is available at the right time and of the right quality. The proposed idea focuses on the implementation of the algorithmic models for the efficiency of the model. The key features of this work are inventory control, automated replenishment, quantitative forecasting, sales report, real time tracking of inventory across multiple locations and optimize storage utilization. Certain models with algorithms make it easier to foresee service frequencies, maintain supply chain management and predict the demand of particular services. Implementation of this includes system configuration, data management, user training, user authentication and real-time monitoring. The expected outcomes of this work include data management for both manufacturers and suppliers, reduced stock-outs and overstocking, improved order fulfilment rates, data accuracy issues, forecasting errors and changing demand due to market conditions.},
        keywords = {Inventory forecasting, Algorithmic models, Management, stocks.},
        month = {May},
        }