One of the current challenges in the domain of the multiobjective shape optimization is to reduce the calculation time required by conventional methods. The high computational cost is due to the high number of simulation or function calls required by these methods. Recently, several studies have been led to overcome this problem by integratinga metamodel in the overall optimization loop. In this thesis, we perform a coupling between the Normal Boundary Intersection -NBI- algorithm and The Normalized Normal constraint Method -NNCM- algorithm with Radial Basis Function -RBF- metamodel in order to have asimple tool with a reasonable calculation time to solve multicriteria optimization problems. First, we apply our approach to academic test cases. Then, we validate our method against two industrial cases, namely, shape optimization of the bottom of a can undergoing nonlinear elasto-plastic deformation and an optimization of an automotive twist beam. Then, in order to select solutions among the Pareto efficient ones, we use the same surrogate approach to implement a method to compute Nash and Kalai-Smorodinsky equilibria.
