Searching Method of Critical Slip Surface of Slope Based on Improved Wolf Swarm Algorithm

Abstract

Determining the critical sliding surface and calculating the safety factor of slope stability are the key problems of slope stability analysis. Firstly, according to the characteristics of the existing wolf swarm algorithm, an improved wolf swarm algorithm is proposed, which abandons the assumption of a circular sliding surface. Then, a multipoint spline curve is introduced to describe the shape of a slope sliding surface. The optimization of the curve can determine the critical slip surface of slope and avoid falling into the local optimum. This method is programmed and implemented in Python, and then, accuracy and reliability are verified through typical slope cases and engineering examples, and the sensitivity analysis of factors that have great influence is carried out. The research results show that the slope sliding surface search method based on the improved wolf swarm algorithm can effectively and quickly determine the critical sliding surface of the slope. Compared with traditional methods, it has higher convergence accuracy and reliability. It provides an effective method for slope stability analysis.