This paper presents an optimised algorithm implementing the method of slices for analysing the stability of slopes. The algorithm adopts an improved physically based parameterisation of slip lines according to their geometrical characteristics at the endpoints, which facilitates the identification of all viable failure mechanisms while excluding unrealistic ones. The minimisation routine combines a preliminary discrete calculation of the factor of safety over a coarse grid covering the above parameter space with a subsequent continuous exploration of the most promising region via the simplex optimisation. This reduces computational time up to about 92% compared to conventional approaches that rely on the discrete calculation of the factor of safety over a fine grid covering the entire search space. Significant savings of computational time are observed with respect to recently published heuristic algorithms, which enable a continuous exploration of the entire parametric space. These efficiency gains are particularly advantageous for numerically demanding applications like, for example, the statistical assessment of slopes with uncertain mechanical, hydraulic and geometrical properties. The novel physically based parametrisation of the slip geometry and the adoption of a continuous local search allow exploration of parameter combinations that are necessarily neglected by standard grid-based approaches, leading to an average improvement in accuracy of about 5%.

翻译：本文提出了一种优化的条分法算法，用于分析边坡稳定性。该算法根据滑移线在端点处的几何特征，采用了一种改进的、基于物理的参数化方法，从而有助于识别所有可能的破坏机制，同时排除不切实际的机制。最小化流程结合了两种方法：首先在覆盖上述参数空间的粗网格上对安全系数进行初步离散计算，随后通过单纯形优化法对最有希望的区域进行连续探索。与依赖在整个搜索空间的细网格上进行安全系数离散计算的传统方法相比，该算法将计算时间减少了约92%。与近期发表的、能够对整个参数空间进行连续探索的启发式算法相比，也观察到计算时间的显著节省。这些效率提升对于计算量要求高的应用尤其有利，例如，对具有不确定力学、水力和几何特性的边坡进行统计评估。新颖的、基于物理的滑移几何参数化方法以及连续局部搜索的采用，使得可以探索标准网格方法必然忽略的参数组合，从而将精度平均提高了约5%。