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基于万有引力搜索算法(GSA)提出了一种改进的万有引力搜索算法(MGSA)。针对GSA在处理优化问题时会出现发散的情况,通过限制粒子的速度同时更改算法中的参数来改善这一问题。算法改进后显著提高了GSA中粒子的探索能力与开发能力,可以获得较强的优化能力。采用MATLAB对8个测试基准函数进行仿真实验,并将该方法引入到边坡稳定分析中。对于边坡稳定性分析,利用MGSA搜索出临界滑动面并结合极限平衡法计算出相应的最小安全系数。结果表明:与GSA法及其他方法相比,MGSA在求解最危险滑动面安全系数时具有更好的优化性能。
Based on the universal gravitation search algorithm (GSA), an improved universal gravitation search algorithm (MGSA) is proposed. In the light of the divergence of the GSA in handling optimization problems, this problem can be ameliorated by limiting the speed of the particles while changing the parameters in the algorithm. After the algorithm is improved, the ability of exploration and development of particles in GSA is significantly improved, and the optimization ability can be obtained. The simulation experiments of eight test reference functions are carried out by MATLAB, and the method is introduced into the slope stability analysis. For the slope stability analysis, the MGSA was used to search the critical slip surface and calculate the minimum safety factor according to the limit equilibrium method. The results show that compared with GSA method and other methods, MGSA has better performance in solving the most dangerous slip surface safety factor.