An adaptive genetic algorithm based on arctangent function

To speed up convergence rate and improve local convergence in genetic algorithm, nonlinear adaptive crossover probability and mutation probability function are designed. They are based on the arctangent function with three parameters of maximal fitness, minimal fitness and average fitness. An improved adaptive genetic algorithm is proposed based on the two designed functions. Simulation results prove that the proposed improved adaptive genetic algorithm possesses faster convergence speed than GA and AGA presented by Srinvas, stronger optimization ability and avoid the premature effectively.