A pixelated source mask optimization (SMO) method based on multi chromosome genetic algorithm (GA) is introduced. This method uses multi chromosome genetic algorithm to optimize the pixelated source and pixelated mask simultaneously. In comparison with the single chromosome GASMO method that uses rectilinear mask representation, multi chromosome GASMO method can get high imaging quality and fast convergence speed. Simulation results show that the multi chromosome method can get an optimum solution with the fitness value is 7.6%, which is smaller than that of the single chromosome method. The multi chromosome method only needs 132 generations to converge to an optimal result with the fitness value of 5200, 127 generations less than the single chromosome method, and the optimization convergence speed is accelerated.