Inventory rationing decision models during replenishment lead time

This study considers an inventory rationing problem in which a warehouse maintains inventory to meet various future requests that are classified into a discrete number of priorities. When there is limited inventory quantity in the warehouse, we prefer to fulfill higher priority requests over lower priority requests. When a low priority request does arrive, the warehouse may need to reject the request and reserve the inventory for later higher priority requests. However, we would rather satisfy lower priority requests than have inventory leftover when the replenishment arrives. To face uncertain request arrivals during an uncertain replenishment lead time, we develop two rationing approaches, dynamic stochastic inventory rationing decision procedure (DSIR) and risk level inventory rationing decision procedure (RLIR), to determine whether to fulfill or reject an arrival request. The simulation experiments show that RLIR provides the highest fill rate for the first priority requests among all simulated approaches, whereas DSIR provides the best overall fill rate while still maintaining a good fill rate for first priority requests. Furthermore, unlike previous studies, the proposed approaches can handle inventory systems with not only random request quantity, but also random replenishment lead time. In addition, most previous studies can only deal with two priority classes, whereas this study can handle a problem of more than two classes. (c) 2013 Elsevier B.V. All rights reserved.