In this study, a multi level reverse logistics network is developed for a single product. Reverse logistics is a logistic activity beginning from intake of products returned by customers to selling of remanufactured or new products in market; so, it is considered that reverse flow of used products is from various sources like customers, dealers, retailers, manufacturers, etc., to remanufacturer and followed by transportation to secondary market. Due to uncertainties, any traditional supply chain approach to identify potential manufacturing facilities in this situation cannot be employed. Hence, Genetic Algorithm (GA) is used for optimization and minimization of various costs involved in reverse logistics process. A sample numerical data is considered to test performance of the proposed model.