An efficient genetic algorithm for locating critical failure surfaces in slope stability analysis with limit equilibrium method

The determination of the critical failure surface in geotechnical field is carried out in the process of evaluating the stability of slopes, embankments, dam, excavations, retaining walls and many others. As in many other studies, the problem of slope stability is analyze by limit equilibrium method (LEM) in homogeneous soil. These methods frequently make it possible to identify the critical circular slip surface (CFS) corresponding to the minimum factor of safety (FOS). Finding the critical slip surface (CFS) and minimum safety factor (FOS) in slope stability analysis can be performed using global optimization metaheuristic techniques. The paper presents a new modified genetic algorithm (MGA), based on Multi-Parametric Convex Crossover (MPCX), to search the critical circular for locating failure surfaces (CFS) and determining the lowest (FOS). The performance of the modified genetic algorithm proposed based on (MPCX), is explored by solving four benchmark applications from the literature. This proposed program converge rapidly to the optimal solution in function of the number of iterations, the results demonstrate that using the approach proposed (MGA) can be applied within the very well result including the analysis of the stability of the slopes, since it presents improved performances compared to the other methods such as grid search and genetic algorithm.