A Simple Model for Computing ( s, S ) Inventory Policies when Demand is Lumpy

In recent decades there has been much interest and activity in the application of mathematical ideas for controlling inventory. However most of this has been related to the control of stock products whose demand is smooth and continuous. When demand is lumpy these methods are inefficient in their attempts to minimise thé operating cost. A simple regression model is developed for computing optimal (s, S) policies for items with lumpy demand patterns. Continuous review of inventory level is assumed and the lead time demand is approximated by the stuttering Poisson distribution. A grid of 864 known optimal policies has been used to provide the data for the calibration of the regression models. Numerical models are used to illustrate this approach. Extensive computational results show that this model provides excellent performance in estimating the optimal values of the control parameters s and S for wide ranges of demand and cost parameters.