Abstract
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.
Highlights
Remanufacturing is the process by which used products are collected, processed and sold as new products
We study a dynamic production control problem of remanufacturing systems based on a queueing system with level dependent returns
Since the optimization problems are especially challenging and difficulty when the state space of the system is multidimensional as in the case of this present model, we propose a performance evolution method to compute the optimal production policy and average cost based on the structure of optimal policies and the theory of QBD process
Summary
Remanufacturing is the process by which used products are collected, processed and sold as new products. We consider a remanufacturing system in stochastic environment where the processing, remanufacturing and discarded time are all nondeterministic In such a system, it can be used to model many real-world systems, for example, an optimal control problem arising in a company which produces and remanufactures airplane engines [4]. We take the queueing theory and Markov decision process to analyze the optimal control of a remanufacturing system. We study a dynamic production control problem of remanufacturing systems based on a queueing system with level dependent returns. We provide insights into the optimal policy and present a method for computing the optimal average cost by constructing a performance evaluation model with QBD process.
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