Web-Based Perishable Inventory Optimization for Waste and Financial Loss Reduction in Quick Commerce

Quick-commerce platforms, such as Blinkit, have changed the way customers purchase groceries, dairy products, bakery items, fresh food, and other dailyuse products by providing fast delivery through local and dark stores.However, managing perishable products is a major challenge because these products have a limited shelf life and their demand can change from day to day.Existing stock prediction methods can predict the expected daily demand of products; however, the predicted quantity does not guarantee that the products will actually be sold.When actual sales are lower than expected, some products may remain unsold and can become near-expiry, resulting in product wastage and financial loss.Therefore, there is a need for a system that can identify unsold or near-expiry stock and provide suitable corrective actions.This study proposes a web-based support system for managing unsold and near-expiry perishable products in quick-commerce stores.The proposed system uses product quantity, sales history, expiry date, price, predicted demand, and actual end-of-day sales to identify products that remain unsold or are approaching expiry.After identifying such products, the system provides suitable recommendations based on the condition of the inventory.For example, products that are still within a safe selling period can continue under normal sales, while products that are closer to expiry can be offered with an appropriate discount to encourage customers to purchase them before expiry.The system can also recommend other corrective inventory actions when required, helping store operators make timely decisions instead of allowing products to remain unsold until they expire.The main purpose of the proposed system is to reduce the loss that occurs when the predicted product demand is not achieved and the stock remains unsold.By identifying unsold and near-expiry products at the end of the day and providing appropriate actions, such as discounting, the system aims to reduce product wastage and financial losses.It can also improve the utilization of available inventory and support better decision-making for quick-commerce store operators.The effectiveness of the proposed approach can be evaluated using historical or simulated inventory data based on measures such as unsold stock reduction, waste reduction, revenue, and stock utilization.This approach provides a practical support system for handling unsold and near-expiry perishable products in quick-commerce stores.