基于遗传算法的边坡关键概率滑面搜索

摘要

Considering the fact that common optimization methods can't be adapted well to seek for key probabilistic slip surfaces of slopes whose optimization function is non-smooth, non-convex and multi-extremum functional, an improved genetic algorithm is used to realize the searching for the maximum of failure probability and key probabilistic slip surfaces. Based on the Bishop method, the limit state function of slope stability is deduced and an optimization model based on genetic algorithm is put forward. Furthermore, searching for key probabilistic slip surface is realized by design point method on the platform of Visual C + + and an engineering example is analyzed. The simulating results show that the proposed method can be used to determine the key probabilistic slip surface and the biggest failure probability of slope efficiently. The speed of convergence are good. The simulating results have good consistency with the engineering facts.%针对常规优化方法难以在非光滑、非凸且可能存在多个极值的边坡关键概率滑面搜索问题中取得较好效果的问题,研究了采用改进遗传算法来实现边坡最大失效概率和关键滑面的搜索.在简化Bishop法的基础上推导了边坡稳定极限状态方程,提出了基于改进遗传算法的边坡分析优化模型;结合验算点法,在Visual C ++的平台上实现了关键概率滑面的搜索,并对某边坡工程进行了分析.结果表明,文中方法能有效地确定边坡关键概率滑面和最大失效概率,且收敛速度和收敛性均较好,所得结果与工程实际基本吻合.