This paper presents results for the CEC 2009 Special Session on "Performance Assessment of Constrained / Bound Constrained Multi-Objective Optimization Algorithms" when Generalized Differential Evolution 3 has been used to solve a given set of test problems. The set consist of 23 problems having two, three, or five objectives. Problems have different properties in the sense of separability, modality, and geometry of the Pareto-front. The most of the problems are unconstrained, but 10 problems have one or two constraints. According to the numerical results with an inverted generational distance, Generalized Differential Evolution 3 performed well with all the problems except with one five objective problem. It was noticed that a low crossover control parameter value provides the best average results according to the metric.