In the design of mechanical structures, the evolutionary algorithms have taken a more and more important place, mostly because of their ability to explore widely the design space. Furthermore, as several objectives are often pursued simultaneously in industrial applications, multiobjective optimization has become a wide area of research in recent years. However, only a few methods integrate a multicriteria decision aid approach to reflect the userΓs preferences since the beginning of the search process. In this paper, PROMETHEE II, an outranking method developed in the operational research field, has been implemented in an evolutionary algorithm. Furthermore, as the handling of the constraints is very critical, an original technique called PAMUC (Preferences Applied to MUltiobjectivity and Constraints) is proposed to tackle simultaneously the constrained and multiobjective aspects. It has been validated on standard test cases, and applied to the design optimization of two valves of the Vinci engine (from launcher Ariane 5). Results analyzed thanks to the R1 norm introduced by Hansen and Jaszkiewicz show that PAMUC outperforms the classical weighted-sum method (combined with a dynamic penalty-based technique to handle the constraints), and therefore seem to be more appropriate to reflect the userΓs preferences.