slope stability analysis using a self-adaptive genetic algorithm

This paper introduces a methodology for soil slope stability analysis based on optimization, limit equilibrium principles and method of slices. in this study, the slope stability analysis problem is transformed into a constrained nonlinear optimization problem. to solve that, a self-adaptive genetic algorithm (ga) is utilized. in this study, the slope stability safety factors are the objective functions, slip surface parameters are the decision variables and, the equilibrium equations are the problem constraints. the proposed model satisfies all conditions of the equilibrium completely. it is also applicable to problems with different soil layers, variable soil properties and including pore water pressure. the model is applied against a benchmark example and the results are compared with previous studies. accordingly, it is found computationally efficient and reliable.