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Optimal Production Control of Remanufacturing Systems Based on a Queueing Model With Returns

This paper analyzes an optimal dynamic production control problem of a remanufacturing system in stochastic environment. The system consists of one inventory for serviceable items and one virtual inventory for the items used by customers which will be either remanufactured to be serviceable items or discarded. Demands will be lost if there is no serviceable items available. At any decision epoch, the decision maker has to decide whether to produce items or not by raw materials, so as to minimize the long run average cost. The optimization problem is constructed as a Markov decision process (MDP). We show that the optimal policy has a multi-threshold structure (switching curve) and it is monotonic in system parameters. Furthermore, based on the structure of the optimal policy, we construct a performance evaluation model for computing efficiently the optimal thresholds. The expression of the average cost is given by a quasi-birth-death (QBD) process. Finally, we provide some numerical results to show the effectiveness of our approach and the impact of different parameters on the optimal policy and average cost.