Recursive estimation of inventory quality classes using sampling (Q1769999)

Summary: In this paper we propose a new discrete time discrete state inventory model for perishable items of a single product. Items in stock are assumed to belong to one of a finite number of quality classes that are ordered in such a way that Class 1 contains the best quality and the last class contains the pre-perishable quality. By the end of each epoch, items in each inventory class either stay in the same class or lose quality and move to a lower class. The movement between classes is not observed. Samples are drawn from the inventory and based on the observations of these samples, optimal estimates for the number of items in each quality classes are derived.