Multi-objective optimization is a popular problem in engineering design. In semi-Active suspension control, comfort and road holding are two essential but conflicting performance objectives. In a previous work, the authors proposed an LPV formulation for semi-Active suspension control of a realistic nonlinear suspension model where the nonlinearities (i.e the bi-viscous and the hysteresis) have been taken into account; an H¿/LPV controller to handle the comfort and road holding has been also designed. The present paper aims at improving the method of  by using Genetic Algorithms (GAs) to select the optimal weighting functions for the H¿/LPV synthesis. First, a general procedure for the optimization of weighting function for the H¿/LPV synthesis is proposed and then applied to the semi-Active suspension control. Thanks to GAs, the comfort and road holding conflicting objectives are handled using a single high level parameter and illustrated via the Pareto optimality. The simulation results performed on a nonlinear vehicle model emphasize the efficiency of the method.