| Perishable inventories exist in several forms, such as produce, human blood, etc. Although the inventory management, and, therefore, the inventory modeling of perishable inventory, is of considerable importance, the research on optimal policies and/or heuristics in a perishable environment scenario is sparse. This can be attributed to the complex nature of the inventory problem which in turn is due to the fact that a good ordering policy has to consider the on-hand inventory not as a whole, but the various age groups that are due to perish at different times.; (s, S) policies are order-up-to policies where one would order up-to S whenever the inventory position reaches s. This research focuses on the modeling of (s, S) policies in a perishable inventory situation and assumes the following: (a) constant lead time, (b) constant lifetime, (c) poisson demand, (d) lost sales. Since the mathematical modeling of the problem is extremely complex, this research narrows its focus to a subset of the (s, S) policy space: specifically the region of focus is where s = 0 and {dollar}S - s > s.{dollar} When {dollar}S - s > s,{dollar} the batch size or the order quantity is greater than the re-order point, and therefore the system would have at most one outstanding order at any time (when lost sales are assumed).; Mathematical models for the on-hand probabilities and the cost function were developed for the subcase {dollar}m tau{dollar} could not be solved completely by analytical methods, the probability equations were verified using numerical integration. Intuitive results are discussed and future directions suggested. |
