The aim of the project is optimum design of suspension parts for multi usage municipal light truck. Therefore the equations of motion for vehicle are optioned with using of suspension system modeling in quarter vehicle, half vehicle and full vehicle. If the modeling of suspension system with higher degree of freedoms is used, more accurate to real vehicle will be achieved and the number of performance indices and design parameters are increased. In the continue, new method for optimization with multi objective function is used for suspension system. Because of advantage of genetic algorithm in the optimization problem, it is used in this problem. Result of this problem is clearly showed the benefit of optimization quarter vehicle modeling, half vehicle modeling and full vehicle modeling. Description of target functions in previous model has more performance indices if the model has more degree of freedoms. There performance indices are selected to achieve comfort and considering a limitation of space and place of parameter of suspension system. The constrains are handled in this optimization is limitation the suspension system parameters. Then for any considering modeling, equations of motion, mass matrix, stiffness matrix and damp matrix are optioned. Vehicle is subjective to random excitation. After this, analysis for mean square of all target functions response have been carried out by considering the power spectral density (PSD) of the road excitation. In addition to the study of the response, the optimization of vehicle parameters is performed on the basis of Multi Objective Programming (MOP) based genetic algorithm. Vehicle parameters are stiffness of springs and coefficient of dampers. Comparison performance indices before optimization with performance indices after optimization obviously showed that performance indices are better.
