改进GEP方法在边坡非圆临界滑动面搜索中的应用

基因表达式编程(Genetic Expression Programming,简称GEP)是模拟生物遗传进化过程的一种新型优化方法,其结合遗传算法(GA)和遗传编程(GP)各自的优点,使编码更为方便、简单。为了进一步改善GEP方法的局部搜索能力和克服"早熟"现象,将局部搜索能力很强的单纯形法和回溯机制引入GEP中,提出了混合GEP方法。以安全系数为目标函数,将混合GEP法和不平衡推力法结合,提出确定非圆弧临界滑动面的新方法。2个经典算例的计算结果表明:该新方法可以准确地搜索到边坡非圆临界滑动面及相应的安全系数,且混合GEP方法的局部搜索精度和全局搜索能力均优于标准GEP方法,同时收敛速度得到明显提高。

Improved Genetic Expression Programming Applied to Searching for Non-circular Critical Slip Surface of Slope

Genetic expression programming (GEP) is a new method of simulating the evolutional process of biology. It makes encoding more convenient and simple by combining the advantages of genetic algorithm and genetic pro-gramming. In this article, a mixed GEP is presented by introducing simplex algorithm and backtracking mechanism into GEP to improve local searching capability and avoid precociousness. On this basis, a new method which in-tegrates the mixed GEP algorithm and Imbalanced Thrust Force Method and takes safety factor as objective function is proposed to search for the non-circular critical slip surface. The results of two classical examples show that the proposed method could exactly find the non-circular critical slip surface and safety factor of slope. Moreover, the mixed GEP is superior to standard GEP in terms of local searching precision and global searching ability as well as convergence rate.