Expiry Based Dynamic Discount System – A Review

Food waste remains a persistent challenge in the retail sector, largely caused by fixed pricing systems that do not account for product freshness or expiry proximity. The Expiry Based Dynamic Discount System seeks to minimize this waste while maintaining retailer profitability by automatically adjusting prices according to predicted expiry dates and real-time demand. This review paper surveys ten key studies addressing dynamic pricing, expiry prediction, and inventory optimization for perishable products. Techniques such as ARIMA, LSTM, Q- learning, Genetic Algorithms, and Dynamic Shelf- Life modeling are compared to understand their roles in forecasting demand, optimizing stock rotation, and enabling sustainable retail operations. The findings indicate that integrating artificial intelligence and optimization models can significantly reduce waste and improve sales efficiency in perishable-goods management