Abstract
ABSTRACT In limit equilibrium slope stability analysis, surface altering optimisation (SAO) is a novel approach to minimise the factor of safety for a given slip surface using spline curves in 2D. It is a local search algorithm that when combined with a global search method, can form a powerful hybrid optimisation technique used in slope stability analysis. Probabilistic analysis of a slope with spatial variability is a computationally intensive example that would demonstrate the accuracy and speed of optimisation techniques. In this paper, the probabilistic analysis results of three different slopes with both complicated and straightforward geometries are presented, and the application of SAO in spatial variability analysis using random limit equilibrium method (RLEM) is demonstrated. It was found that SAO combined with a global search method provides fairly accurate results and yields curtailed computational effort.
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