OPTIMAL ACQUISITION POLICY IN REMANUFACTURING SYSTEMS WITH QUANTITY DISCOUNT AND CARBON TAX SCHEME

High uncertainty and variability of acquirable cores can lead to some difficulties of operations management in the remanufacturing process. Two acquisition models with quantity discount and carbon tax scheme were established to analyze the effect of quality variability and condition uncertainty and to reduce these difficulties. In the first model, quality variability was considered. The optimal acquisition policy was determined by a single closed-form expression because the average cost of remanufactured products is independent of the acquisition quantity for a given discount segment. In the second model, both quality variability and condition uncertainty were considered. The properties of the model were analyzed, and a single algorithm was developed to obtain the optimal acquisition policy based on the bisection method. Finally, numerical simulation examples were provided to explore the effect of quantity discount on the optimal acquisition policy. Results show that the quantity discount schedule impels remanufacturers to acquire more cores and enhances the chances of remanufacturers to select the best cores. Moreover, the total expected cost decreases, especially in the case with both quality variability and condition uncertainty. The proposed model can effectively solve the acquisition problem in remanufacturing systems.