The distributionally robust optimization model for a remanufacturing system under cap-and-trade policy: a newsvendor approach

This paper considers a remanufacturing system in which the remanufacturer uses both the fresh raw material and recycled material to produce new products. Only partial information of the demand distribution, including the mean and variance, is available in this system. The operational activities of the remanufacturer are major contributors to carbon emissions, and a government agency imposes a cap-and-trade (carbon emission trading) policy on the remanufacturer. In the context of the distributionally robust newsvendor model, a maxmin approach is used to solve the optimal joint collection and production quantities. To study whether implementation of a cap-and-trade policy improves the remanufacturer’s expected profit and reduces corresponding carbon emissions, the case where the government agency does not impose cap-and-trade policy is considered and compared. Finally, numerical analysis is conducted to illustrate and complement the analytical results and to investigate the influences of several main parameters on the distributionally robust newsvendor model for the remanufacturing system under a cap-and-trade policy.