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边坡临界滑面的确定对边坡稳定分析和加固设计极为重要,采用基于变异和二次序列规划的改进粒子群优化算法(VSPSO)进行临界滑面搜索。VSPSO算法中通过变异操作增强粒子群跳出局部最优解的能力,并用二次序列规划(SQP)加速局部搜索,大大提高了粒子群获得全局最优的能力。通过对有解析解的边坡算例进行分析,验证了该算法的准确性及优越性;对澳大利亚计算机应用协会(ACADS)提供的均质边坡、多层土边坡以及含软弱层边坡进行分析,结果表明改进的VSPSO算法搜索所得滑面比传统PSO算法更逼近推荐答案,具有更好的鲁棒性,而且随着边坡复杂程度的增加,更能体现改进VSPSO算法的优越性,具有广阔的应用前景。
The determination of the critical slip surface of the slope is very important for slope stability analysis and reinforcement design. The critical slip surface is searched by the improved Particle Swarm Optimization (VSPSO) based on mutation and quadratic sequence programming. VSPSO algorithm enhances the ability of particle swarm to jump out of local optimal solution through mutation operation and accelerates local search with quadratic sequence programming (SQP), which greatly improves the ability of particle swarm to obtain global optimum. The accuracy and superiority of the proposed algorithm are verified by analyzing the slopes with analytic solutions. Homogeneous slopes, multi-layered soil slopes and the weak soil slopes provided by the Australian Institute of Computer Applications (ACADS) The results show that the improved sliding surface of VSPSO algorithm is more approximate to the recommended solution than the traditional PSO algorithm and has better robustness. Moreover, as the complexity of the slope increases, it can better reflect the superiority of the improved VSPSO algorithm, have a broad vision of application.