通过对基本粒子群优化算法的分析,提出一种用于求解多层非线性规划问题的算法,实现对多层非线性规划问题的 Stackelberg-Nash 均衡解的搜索.该算法使用动态区域搜索方法保证全局收敛性,采取自适应扰动策略增强跳出局部最优点的能力,通过基于约束适应度的更新机制保证解的可行性.实验结果证明算法的有效性. By analyzing the basic particle swarm optimization algorithm, an algorithm for solving multi-level nonlinear programming problems is proposed to search for the Stackelberg-Nash equilibrium solution of multi-level nonlinear programming problems. The algorithm uses dynamic region search method to ensure Global convergence, adaptive disturbance strategy is used to enhance the ability to jump out of local optimum, and the feasibility of the solution is guaranteed by the renewal mechanism based on constraint fitness.The experimental results show the effectiveness of the algorithm.