Reverse logistics is becoming a very important and necessary part of any business wanting to excel and move forward. One important aspect of reverse logistics is product returns. It is becoming essential to make sound decisions at all levels; strategic, tactical and operational, concerning the return flow of products. Thus, most firms have begun to explore the possibility of managing product returns in a more cost efficient manner. However, few studies have addressed the problem of determining the number and location of centralized return centers (i.e., reverse consolidation points) where returned products from retailers or end customers were collected, sorted, and consolidated into a large shipment destined for manufacturers or distributors' repair facilities. To fill the void in such a line of research, this paper proposes a nonlinear integer programming model that is subsequently transformed into an equivalent mixed integer linear programming model.