On the (R,S,Q) Inventory Model When Demand is Modeling as a Compound Bernoulli Process

In this paper we present an approximation method to compute the reorder point s in a (R; s; Q) inventory model with a service level restriction, where demand is modeled as a compound Bernoulli process; that is, with a xed probability there is positive demand during a time unit, otherwise demand is zero. The demand size and replenishment lead time are stochastic variables. It is shown that this kind of modeling is especially suitable for intermittent demand. Furthermore, an approximation for the expected average physical stock is derived. The quality of both the reorder point determination as well as the approximation for the expected average physical stock turn out to be excellent, as is verified by discrete event simulation