Price Optimization for Perishable Products with Freshness Transition Function *

Because different items of the perishable products have different deterioration extents in an inventory system, the deterioration process of these perishable products cannot be captured accurately by a single number like deterioration rate. Instead, it is more appropriate to capture their deterioration process on different freshness levels by employing the freshness transition function. Especially, time-temperature indicator (TTI) technology can detect the freshness deterioration process accurately. Therefore, the freshness transition function of perishable products can be constructed based on the data collected by the TTIs. The accuracy of a freshness transition function depends on the detection quality of the TTIs deployed in the perishable inventory system and affects the performance of the pricing decision, because this decision is made based on the observation accuracy of the products' freshness. In this research, we develop the method of optimal pricing decision to obtain the maximum total profit based on the freshness transition function. This method is implemented in three steps: constructing the freshness transition function, designing the pricing optimization policy based on Deep Q-network method, and analyzing the impact of the accuracy of the freshness transition function on the performance of the pricing decision. Finally, we conduct some numerical experiments to examine the performance of the proposed optimal pricing method based on the freshness transition function and found that (1) the retailers should increase the price to obtain more total profit within a sale cycle; (2) the accuracy of the freshness transition function has great influence on the proposed pricing optimization policy.