The development of an algorithm to optimize price discounts for maximizing store profit in supermarkets

Abstract

To reduce food waste, supermarkets discount the price of food that is nearing its expiration date. To maximize profits, it is necessary to adjust the discount rate as low as possible while controlling waste due to unsold products. Traditionally, the operational discount rate has been determined based on the experience of each store operator. Inexperienced operators have difficulty in determining the appropriate discount rate for the situation, resulting in excessive discounting and disposal losses. In this study, we developed an algorithm that suggests the optimal discount rate to maximize store profits. Specifically, we developed a demand forecasting model that predicts the expected sales volume per hour for each product based on POS data, etc., and a discount optimization algorithm that uses dynamic programming to calculate the optimal discount rate for each product, time, and number of items in stock based on the forecast results. We conducted a validation experiment of the algorithm in a store, taking into account the constraints of real operations, and observed a constant rate of improvement in discounting and waste loss.