  Companies try to maximize their profits by recovering returned products of
highly uncertain quality and quantity. In this paper, a reverse logistics
network for an Original Equipment Manufacturer (OEM) is presented. Returned
products are selected for remanufacturing or scrapping, based on their quality
and proportional prices are offered to customers. A Mixed Integer Non-linear
Programming (MINLP) model is proposed to determine the location of collection
centers, the optimum price of returned products and the sorting policy. The
risk in the objective function is measured using the Conditional Value at Risk
(CVaR) metric. CVaR measures the risk of an investment in a conservative way by
considering the maximum lost. The results are analyzed for various values of
the risk parameters ({\alpha}, and {\lambda}). These parameters indicate that
considering risk affects prices, the classification of returned products, the
location of collection centers and, consequently, the objective function. The
model performs more conservatively when the weight of the CVaR part ({\lambda})
and the value of the confidence level {\alpha} are increased. The results show
that better profits are obtained when we take CVaR into account.
