In this article, we consider a continuous review perishable inventory system with a finite number of homogeneous sources generating demands. The demand time points form quasi random process and demand is for single item. The maximum storage capacity is assumed to be The life time of each item is assumed to have exponential distribution. The order policy is policy, that is, whenever the inventory level drops to a prefixed level an order for items is placed. The ordered items are received after a random time which is distributed as exponential. We assume that the demands that occur during the stock out periods either enter a pool or leave the system which is according to a Bernoulli trial. The demands in the pool are selected one by one, while the stock is above the level with interval time between any two successive selections is distributed as exponential. The joint probability distribution of the number of customers in the pool and the inventory level is obtained in the steady state case. Various system performance measures are derived to compute the total expected cost per unit time in the steady state. The optimal cost function and the optimal are studied numerically.
A good approximation of the inventory level in a (Q, r) perishable inventory system