Journal of Digital Information Management Adrian Florea,Ioana Ileana Cofaru, Lucian ROMAN, Nicolae Cofaru 14 6 2016 http://dline.info/fpaper/jdim/v14i6/jdimv14i6_2.pdf The questionable quality of the roads represents the main factor of discomfort, being directly responsible for the accidents, affecting car components, but also the security of passengerscausing death and serious injuries. According to statistics released by the World Health Organization, road accidents, in underdeveloped countries, tends to increase by 80 % in 2020 compared to 2000. In terms of road infrastructure,the lowand middle-income countries are characterized by a higher accident rate, reason for which the cars designers must approach the suspension problem slightly different and the parameters obtained by optimization algorithms should be differentfrom the same model of car depending on where they will be driven / sold.This paper presents the optimization of a quarter-car model with two degree-offreedom using evolutionary algorithms to determine the optimal parameters for a vehicle suspension, in order to improve ride comfort. The optimization problem consists in minimizing the sprung mass acceleration and sprung mass displacement subject to several constraints that arise from kinematic considerations. The vehicle model is considered to travel at a constant speed on a random road profile generated according to the ISO 8608 standard. The design variables to be optimized are the suspension stiffness and damping coefficients. We analyzed the algorithms in multiple scenarios so we can compare their performance in terms of fast convergence and solution diversity. The results showed that the optimization algorithms find solutions in small number of iterations, with slightly better performance obtained by Fast Pareto Genetic Algorithm.