Genetic algorithm search for critical slip surface in multiple-wedge stability analysis

Most procedures for determining the critical slip surface in slope-stability analysis rely on traditional nonlinear optimization techniques. The main shortcoming of these techniques is the uncertainty as to robustness of the algorithms to locate the global minimum factor of safety rather than the local minimum factor of safety for complicated and nonhomogeneous geological subsoil conditions. This paper describes the incorporation of a genetic algorithm methodology for determining the critical slip surface in multiple-wedge stability analysis. This search strategy is becoming increasingly popular in engineering optimization problems because it has been shown in a wide variety of problems to be suitably robust for the search not to become trapped in local optima. Three examples are presented to demonstrate the effectiveness of the genetic algorithm approach. The search strategy was found to be sufficiently robust to handle layered soils with weak, thin layers, and as efficient and accurate as the conventional pattern search method.