Abstract: Aiming at the defect of premature convergence and low-search efficiency of the standard genetic algorithm(SGA), an adaptive genetic algorithm based on weighted hamming distance is presented in this study. The proposed algorithm considers the Weighted hamming distance and the fitness value, adjusting crossover probability and mutation probability adaptively;Using the method of elite preserving to ensure the best individual is not damaged;Using the criterion of dual stopping to reduce unnecessary computing time and improve the efficiency of genetic search. Finally, some simulation experiments are carried out with classical test functions in the Matlab platform. Experimental results show that the proposed algorithm can effectively improve the global search ability of genetic optimization, and speed up the convergence of genetic algorithm.