The elitist non-dominated sorting genetic algorithm(NSGA-II) can't adjust the operation parameters adaptively according to the change of environment, so it is difficult to search the solution space efficiently. To solve the problem, an adaptive non-dominated sorting genetic algorithm is proposed. The proposed algorithm dynamically adjusts the operating parameters of evolutionary individuals according to the running phase, the evolutional generation and the number of non-dominated individuals in the current temporary population, via improving the adaptive ability of the evolutionary operator to make the algorithm adaptive. The experimental results show that the proposed algorithm can increase the original algorithm in two aspects, such as convergence and diversity, and also improve the searching ability.