Aiming at the defects of weak local search ability and the low solution accuracy of penalty function when solve the nonlinear programming problem,the nonlinear programming algorithm is introduced to the genetic algorithm and a nonlinear programming genetic algorithm is proposed based on dynamic penalty function.Combining the capable of global optimization of the genetic algorithm and the capable of local optimization and introducing dynamic penalty function,according to the value of penalty term is modified adaptively based on the distance of infeasible points to feasible solution space and feasibility degree,the global optimal solution is quickly to calculate.The design of dynamic penalty function and the key technology and process of improved genetic algorithms are introduced.Finally,the reasonability of algorithm is verified based on the example of the optimum design of a certain automobile gearbox.Compared with the traditional genetic algorithm,the solution quality and converged speed of improved genetic algorithms are improved obviously.As a result,a new way of thoughts is provided for genetic algorithm improvement.