This study addresses the problem of optimizing mechanical components during the first stage of the design process. While a previous work focused on parameterized designs with fixed configurations - which led to the development of the PAMUC (Preferences Applied to MUltiobjectivity and Constraints) method, for solving multicriteria constrained problems within evolutionary algorithms (EAs) -, the models analyzed in this work are enriched by the presence of topological variables enabling, to consider simultaneously different configurations.
Therefore, in order to create optimal but also realistic designs, i.e. fulfilling not only technical requirements but also technological constraints (e.g. related to the machining or the assembly), which are more naturally expressed in terms of rules, an original approach is proposed, named PAMUC II. It consists in integrating an inference engine within the EA, and repairing the individuals (with a given probability of replacement) violating the technological constraints (written as 0-order logical rules). PAMUC II is illustrated on a mechanical benchmark and an industrial case: the multicriteria optimization of a poppet valve design from the VINCI engine of launcher Ariane 5. Results show the efficiency of the proposed method to provide at once optimal and feasible designs.