Modeling Lead Time Demand in Continuous Review Inventory Systems
Inventory systems that use continuous review policy are under risk during lead time, when stock-out can occur. Therefore, system must have enough on-hand units to prevent such situations. Generally, in inventory control literature it can be found that lead time demand follows normal distribution and all other conclusions are derived from this assumption. However, in real life this does not have to be true, so it is of crucial importance to get better estimates of stochastic demand parameters over lead time. The objective of this research is to estimate the optimal (s, Q) continuous review inventory policy parameters that reduce risk of stock-out during lead time and to enhance robustness of such estimated parameters. This is done using approach we propose for demand modeling. Performances and adequacy of the proposed approach for lead time demand modeling, with various demand patterns, and its application in (s, Q) continuous inventory models are obtained by simulation and show very good results.