The design of closed-loop logistics (forward and reverse logistics) has attracted growing attention with the stringent pressures of customer expectations, environ- mental concerns and economic factors. This paper con- siders a multi-product, multi-period and multi-objective closed-loop logistics network model with regard to facility expansion as a facility location-allocation problem, which more closely approximates real-world conditions. A multi- objective mixed integer nonlinear programming formula- tion is linearized by defining new variables and adding new constraints to the model. By considering the aforemen- tioned model under uncertainty, this paper develops a hybrid solution approach by combining an interactive fuzzy goal programming approach and robust counterpart optimization based on three well-known robust counterpart optimization formulations. Finally, this paper compares the results of the three formulations using different test sce- narios and parameter-sensitive analysis in terms of the quality of the final solution, CPU time, the level of con- servatism, the degree of closeness to the ideal solution, the degree of balance involved in developing a compromise solution, and satisfaction degree.