引入退火机制的智能单粒子算法在复杂边坡最危险滑动面搜索中的应用

复杂边坡的安全系数可能存在多个局部极小值点,如何确定边坡的最小安全系数是复杂边坡稳定性分析中的一个关键问题。本文结合简化Bishop法,采用一种新的启发式全局优化算法——智能单粒子算法(ISPO)来搜索复杂边坡的最危险滑动面。为帮助该算法快速跳出局部极值点,本文将模拟退火(SA)机制引入到智能单粒子算法中,结合了两种算法各自的优点,提出了引入退火机制的智能单粒子算法SA-ISPO。将本文提出的SA-ISPO算法用于搜索两个复杂边坡的最危险滑动面,并与其它方法相比较,验证了SA-ISPO算法的优越性,该算法搜索效率高,计算结果不受搜索范围的影响,是一种较好的全局优化算法。

APPLICATION OF INTELLIGENT SINGLE PARTICLE OPTIMIZER WITH SIMULATED ANNEALING MECHANISM TO SEARCHING FOR CRITICAL SLIP SURFACE OF COMPLEX SLOPE

More than one local minimum of the factor of safety can be encountered in stability analysis of complex slopes. So, how to obtain minimal factor of safety remains a significant issue in stability analysis of complex slopes. Based on simplified Bishop method, a new heuristic global optimization algorithm called Intelligent Single Particle Optimizer (ISPO) is proposed to search for the critical slip surface of complex slope in this paper. The simulated annealing mechanism is considered so as to help ISPO to escape from local minimums quickly. The ISPO with simulated annealing (SA) mechanism combines the merits of the two algorithms. The proposed algorithm is applied to searching for the critical slip surfaces of two complex slopes in the paper. Comparing with other methods, the results demonstrate that the combined SA-ISPO algorithm has sufficient calculating precision and stability, as well as high searching efficiency. And also the SA-ISPO has efficient global searching ability because the result is independent of searching range.