Abstract
This paper presents a stochastic optimization model for a closed-loop supply chain. The core component can be recycled from either new or used market. The quality of recycled core component is uncertain. In each period, the manager has to decide how many new products to produce, how many used products to remanufacture, and how many core components to recycle from new and used market. The objective is to maximize the profit.An efficient value iteration algorithm is developed to solve the problem. The stationary solutions provide relationships between values of decision variables and inventory levels. The performance of dynamic policy is compared with two common practices. The result shows that dynamic policy is desirable in certain conditions. Managerial insights regarding how parameters impact decision variables are discussed.