Dynamic pricing models for used products in remanufacturing with lost-sales and uncertain quality

In this paper, we investigate the remanufacturing problem of pricing single-class used products (cores) in the face of random price-dependent returns and random demand. Specifically, we propose a dynamic pricing policy for the cores and then model the problem as a continuous-time Markov decision process. Our models are designed to address three objectives: finite horizon total cost minimization, infinite horizon discounted cost, and average cost minimization. Besides proving optimal policy uniqueness and establishing monotonicity results for the infinite horizon problem, we also characterize the structures of the optimal policies, which can greatly simplify the computational procedure. Finally, we use computational examples to assess the impacts of specific parameters on optimal price and reveal the benefits of a dynamic pricing policy.