Optimal (r, Q) Models Considering Inventory Shrinkage

Abstract

Although inventory shrinkage negatively affects firms' operations decisions in nearly every type of industry, it is generally ignored in practice. Most of the available mathematical models are not considering inventory shrinkage caused by lost or misplaced inventory items, because of the mathematical complexity. Therefore, we develop new (r, Q) models addressing shrinkage. Besides misplaced items, we consider perished or lost items, which are common in the retail industry. We further propose an algorithm to solve the models developed. To demonstrate the applicability of our models and solution algorithm, we assume normal and exponential demand distributions. We show that total inventory costs obtained using our models are significantly lower than those from available models, which does not consider misplaced items and the sensitivity analysis leads us to several managerial implications.