Locating the critical failure surface of a soil slope is rendered erroneous and cumbersome due to the existence of local minima points. In case of large soil slopes, engineers face with a search space too large to employ the trial and error method in a computationally efficient fashion. An evolutionary algorithm is proposed to locate the critical surface under general conditions with general constraints. Convergence to any prescribed degree of precision was achieved with the algorithm. The algorithm has been demonstrated to be computationally superior to other optimization routines, Monte-Carlo method and grid-points approach.
Keywords: slope stability, critical failure surface, evolutionary algorithm.