This document describes using a genetic algorithm to optimize the parameters of a vehicle suspension system. A quarter-car model with 5 parameters is developed in Matlab and Simulink. The objective is to minimize sprung mass acceleration. A genetic algorithm is run for 51 generations to optimize the parameters. The optimized parameters found are reported, and plots show the genetic algorithm converged on optimal solutions. The optimized suspension model response matches the goal of minimizing sprung mass acceleration compared to initial arbitrary parameter values.