Joint Discount and Replenishment Parametric Policies for Perishable Products

We consider a joint discount and replenishment problem in a discrete periodic review fashion for the sale of a perishable product, characterized by limited deterministic shelf life, replenishment lead times, and stochastic demand. Customers decide what to buy according to a linear discrete choice model, balancing price and perceived quality, uniquely determined by the residual shelf life. The decisions we consider are: How many new items to order, the age of the items to be discounted, and how much discount to offer. In this context, we compare a set of policies mixing the constant order policy and the base stock one with some easy discounting policies, optimizing their parameters using a simulation-based optimization framework. To evaluate their performance in terms of revenue and quantity of scraped items, we consider four realistic instances for a grocery retailer characterized by products of different shelf life and variance of demand. Experiments show that best results are achieved by a base stock policy that discounts products of different ages based on a threshold: If the quantity of the inventory of a given age is greater than a threshold it applies a discount, otherwise no discount is proposed. In the presented configurations, this policy increases the average reward compared to policies that do not discount