Extracting an optimal set of parameter values for a MOS device is great importance in contemporary technology is acomplex problem. Traditional methods of parameter extraction can produce far from optimal solutions because of thepresence of local optimum in the solution space. Genetic algorithms are well suited for finding near optimal solutions inirregular parameter spaces.In this study*, We have applied a genetic algorithm to the problem of device model parameter extraction and are able toproduce models of superior accuracy in much less time and with less reliance on human expertise. MOS transistor'sparameters have been extracted and optimized with genetic algorithm. 0.35μm fabricated by C35 process have beenused for the results of experimental studies of parameter extraction. Extracted parameters' characteristic data resultshave been compared with measurement results. Different values of parameters of genetic algorithm, such as populationsize, crossover rate , and generation size are compared by different tests.