In this paper, we develop a multi-objective model for the design and planning of closed-loop supply chains under demand uncertainty that maximizes the expected net present value (ENPV) and minimizes risk. Four different risk measures are implemented and compared: variance, variability index, downside risk and conditional value-at-risk (CVaR) so as to conclude on these measures adequacy. The model is applied to a European supply chain and the optimal solutions are drawn in a Pareto curve obtained through the ε-constraint method.