In solving earth pressure problems, many input parameters are needed to account for more realistic soil properties and complex boundary conditions. Finding an optimal output while considering many inputs can be costly and time consuming. The input parameters themselves may be significantly uncertain due to lack of laboratory test data and variations in design and construction stages. Adopting an optimisation technique can be useful in such a problem. In this study, a chaotic particle swamp optimisation algorithm is applied to three different earth pressure problems – that is, a retaining wall problem, a plane strain tunnel problem and a suffosion sinkhole problem, to determine their global optimal outputs and corresponding input parameters. The problems are solved using a slip line theory satisfying static equilibrium and the Mohr–Coulomb failure criterion. This improved particle swamp optimisation algorithm is found to show better performances, in accuracy and computational effort, compared to conventional Monte Carlo simulations.

中文翻译：

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使用混沌沼泽优化算法优化滑移线场的输出

在解决土压力问题时，需要许多输入参数来考虑更真实的土壤特性和复杂的边界条件。在考虑许多输入的同时找到最佳输出可能既昂贵又耗时。由于缺乏实验室测试数据以及设计和施工阶段的变化，输入参数本身可能存在很大的不确定性。采用优化技术在此类问题中可能很有用。在这项研究中，混沌粒子沼泽优化算法应用于三个不同的土压力问题，即挡土墙问题、平面应变隧道问题和窒息天坑问题，以确定它们的全局最优输出和相应的输入参数。使用满足静态平衡的滑移线理论和 Mohr-Coulomb 失效准则来解决这些问题。与传统的蒙特卡罗模拟相比，这种改进的粒子沼泽优化算法在准确性和计算量方面表现出更好的性能。