基于改进生物地理学算法的均质土坡滑动面搜索研究  

Locating the Critical Slip Surface of Homogeneous Soil Slope Based on Modified Biogeography-Based Optimization Algorithm

作　　者：张新启 龚爱民 徐兴倩 罗聪聪 谢非 ZHANG Xinqi;GONG Aimin;XU Xingqian;LUO Congcong;XIE Fei(College of Water Conservancy,Yunnan Agricultural University,Kunming 650201,China)

机构地区：[1]云南农业大学水利学院,昆明650201

出　　处：《河南科学》2021年第2期276-281,共6页Henan Science

基　　金：国家自然科学基金项目(41867040)。

摘　　要：临界滑移面是边坡稳定性评价及防治的基本依据,其搜索过程可以看作是一个约束性的全局优化问题.基于传统的生物地理学算法(BBO)理论,在该算法迁移过程中引入随机拓扑结构,以瑞典圆弧法数学表达式为目标函数,提出了改进的生物地理学算法(MBBO),实现了对边坡临界滑动面的全局优化搜索.以某典型均质土坡为例,分别利用遗传算法(GA)、粒子群算法(PSO)、BBO算法和MBBO算法计算得到了边坡的最小安全系数及对应的临界圆弧滑动面.通过对比分析可知,改进的生物地理学算法全局寻优能力与迭代速度均有显著提高.The critical slip surface is on the basic of slope stability evaluation and prevention,and its search process is a constrained global optimization problem.Based on the traditional biogeography algorithm(BBO)theory,an improved biogeography algorithm(MBBO)was proposed in this paper,which introduces the random topology structure in the algorithm migration process and takes the mathematical expression of Swedish arc method as the objective function.Taking a typical homogeneous soil slope as an example,genetic algorithm(GA),particle swarm optimization(PSO),BBO algorithm and MBBO algorithm were used to calculate the minimum safety factor and corresponding critical arc slip surface of the slope.Through comparative analysis,the improved biogeography-based optimization algorithm has higher calculation accuracy,significantly improved global optimization ability and iteration speed.

关 键 词：土质边坡 瑞典圆弧法 临界滑动面 BBO算法 安全系数 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TU441[自动化与计算机技术—控制科学与工程]