Optimal control of a remanufacturing system

An optimal control problem of a remanufacturing system under stochastic demand is studied. The system is formulated by a Markov decision process, which is a class of stochastic sequential processes in which the reward and transition probability depend only on the current state of the system and the current action. The models have gained recognition in such diverse fields as engineering, economics, communications, etc. Each model consists of states, actions, rewards and transition probabilities. The paper considers two types of inventories: the actual product inventory in a factory and the virtual inventory used by a customer. The state of the remanufacturing system is defined by both inventory levels. One can obtain the optimal production policy that minimizes the expected average cost per period. The paper also considers some scenarios under various conditions and shows the example of controlling the remanufacturing system.