基于量子遗传算法的边坡稳定性分析  

Slope Stability Analysis Based on the Quantum Genetic Algorithm

作　　者：赵建强[1,2] 陈必科 戴青松[3] 

机构地区：[1]中国矿业大学矿业工程学院,江苏徐州221008 [2]徐州工程学院数学与物理科学学院,江苏徐州221111 [3]徐州工程学院环境工程学院,江苏徐州221111

出　　处：《沈阳建筑大学学报（自然科学版）》2015年第1期18-26,共9页Journal of Shenyang Jianzhu University：Natural Science

基　　金：国家自然科学青年基金项目(11001129)

摘　　要：目的以量子遗传算法为基础,分析斜边坡的最危险滑动面与其稳定系数,为露天矿安全生产提供理论保障.方法以滑动面稳定系数最小为目标函数、以简化的Bishop法确定的稳定系数的递推方程为约束条件,建立边坡稳定性分析的非线性多目标优化数学模型,设计求解该模型的量子遗传算法步骤,利用MATLAB编程求解.结果实例1求得的最危险滑动面圆心坐标为(-11.91,37.126)m,半径为38.83 m,稳定性系数为1.314,迭代次数为30,迭代更少,但是计算结果与遗传模拟退火算法结果相近;实例2求解的稳定性系数为1.715,计算结果与改进遗传算法结果相近,迭代次数为15,迭代次数更少.结论设计的边坡稳定性评价多目标优化模型合理,设计的量子遗传算法迭代次数更少,收敛速度更快,计算结果可靠.The aim of this paper is to analysis the slope stability and determine the most dangerous sliding surface so as to provide a theoretical guarantee for open pit mine production safety. Taking the sliding surface stability coefficient as a objective function,recurrence equations of stability coefficient which were determined by the simplified Bishop method as constraint conditions, a nonlinear mathematical model of multi-objective optimization was constructed to analyze the slope stability. Based on the quantum genetic algorithm and MATLAB, the built model was solved. Calculated results show that in example 1, center coordinates of the most dangerous sliding surface are （ -11.91,37. 126）,radius is 38.83, slope stability coefficient is 1. 314,iterations is 30. The resuits are similar to that solved by the enetic simulated annealing algorithm： In examole 2. slooestability coefficient is 1.715, the results are very approximate to the results solved by the improved genetic algorithm,but with fewer iterations 15. Conclusion is that the multi-objective optimization model is scientific and reasonable;the calculation with the designed quantum genetic algorithm has faster convergence with fewer iterations and more reliable results.

关 键 词：边坡稳定性 稳定系数 最危险滑动面 多目标优化 量子遗传算法 

分 类 号：TU457[建筑科学—岩土工程]