A continuous review inventory system in a random environment

In this thesis, we develop a continuous review inventory model in a random environment where holding, ordering, and purchasing cost parameters are dependent on the state of the environment. We derive the exact expressions of the operating characteristics of the model and discuss some convexity properties of the expected cost rate. A numerical analysis is provided to examine the sensitivity of the optimal policy parameters with respect to various system parameters. We compare the instantaneous shock model with our model and illustrate that ignoring finite duration of environmental states results in considerable error. Moreo\er. we compare our model with a time-average EOQ and myopic model. The results illustrate that when ordering and purchasing cost parameters change, our model performs significantly better.