Recently, reverse supply chain (RSC)has received significant attention from researchers, governments and industries. Most current studies assumed that parameters in RSC are deterministic or known in advance. In addition, risk and incentive elements in RSC models are neglected. Risk factors normally come from transportation and treatment processes which can lead to the increasing cost of the RSC system. Incentive fee can support consumers to return their end-of-life products. This research aims to minimize the total cost of an RSC model incorporating risk and incentive factors while some key parameters in the model are represented by fuzzy numbers. Fuzzy mathematical programming is utilized to solve the problem and find the optimal locations of facilities as well as the flow of materials in the network. A numerical example of electronic waste (e-waste)is investigated to demonstrate the usefulness of the proposed model. This study can provide significant implications since it can support managers to determine important strategic decisions in the design of an effective RSC model towards sustainable development.