A Reverse Logistics Inventory Control Model Consider to Gamma Random Intermittent Demanded

Reverse logistics has greater ambiguity and randomness in the number, time and quality. Under the periodic review environment, there are many periods in which no demand occurs and thus no replenishment is needed. In the current paper, a model that makes a replenishment decision at the time when demand transaction occurs is proposed. Based on the actual case, this study assumes that demand, demand intensity and the order interval are the random variable with Gamma distribution. The study develops a simple graphical aid for choosing appropriate replenishment size in consistence with the desired service level without explicitly calculating the reorder point by assuming that the three variables-demand size, demand intensity and lead time, are all Gamma distribution.