AVERAGE COST OPTIMALITY IN INVENTORY MODELS WITH MARKOVIAN DEMANDS

This paper is concerned with long-run average cost minimization of a s tochastic inventory problem with Markovian demand, fixed ordering cost , and convex surplus cost. The states of the Markov chain represent di fferent possible states of the environment. Using a vanishing discount approach, a dynamic programming equation and the corresponding verifi cation theorem are established. Finally, the existence of an optimal s tate-dependent (s, S) policy is proved.