The traditional adaptive genetic algorithm is slow in convergence and easy to fall into the local optimal solution. In order to resolve this problem, an adaptive genetic algorithm with density weighted is put forward in this study. Based on distribution density of population, this new algorithm can dynamically change the crossover probability and mutation probability of genetic algorithm, and combine with the best individual method. The results of the experiment show that the new algorithm can change the stability of local population, speed up the convergence, and improve its robustness and application.