Product return network design usually may involve multi-objective decision making, for example total reverse logistics costs, loads balance for product return operations on product collection points and the convenience of customers who return products, etc. In this study, a fuzzy multi-objective reverse logistics network for product returns is developed. The goal of the proposed model is to determine the optimal number and location of initial collection points for returned products and the location/allocation of centralized return centers. We employ a weighted max-min approach for fuzzy goal programming to formulate the multi-objective product return system. A soft computing, differential evolution (DE) is proposed to solve the problem. We show that the solution derived from the fuzzy method satisfies the decision maker??s desirable achievement level of the objectives. A case example is presented to illustrate the model implementation.