| 挡土墙库仑土压力的遗传算法求解分析 |
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| 引用本文： | 赵同彬,谭云亮,王虹,孙振武,肖亚勋.挡土墙库仑土压力的遗传算法求解分析[J].岩土力学,2009,30(4):1170-1174. |
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| 作者姓名： | 赵同彬 谭云亮 王虹 孙振武 肖亚勋 |
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| 作者单位： | 1. 山东科技大学 矿山灾害预防控制教育部重点实验室，青岛 266510；2. 山东科技大学 研究生教育学院，青岛 266510； 3. 山东科技大学 资源与环境工程学院，青岛 266510 |
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| 基金项目： | 山东科技大学矿山灾害预防控制教育部重点实验室开放基金，国家自然科学基金，山东省教育厅科技计划项目 |
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| 摘 要： | 在对破裂面上滑动土体静力极限平衡分析的基础上，建立了基于优化方法求解无黏性土、黏性土库仑土压力的自变量取值区间和目标函数模型，并采用遗传进化方法进行了实例求解分析。研究结果表明，遗传算法在计算挡土墙库仑主动土压力的过程中，收敛速度快、用时短，并具有较高的计算精度。算例1中5组无黏性土挡土墙的主动土压力的计算结果与经典库仑解析解非常接近，平均误差为1.748 %，平均进化代数为15代。算例2中8组黏性土挡土墙的主动土压力计算结果与文献的解答非常吻合，平均误差仅为0.017 %，平均进化代数为17.125代。遗传算法具有良好的适应性和强大的搜索性能，非常适合求解岩土工程优化问题。
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| 关 键 词： | 库仑土压力 遗传算法 优化求解 目标函数 |
| 收稿时间： | 2007-10-15 |
Analytical solution of Coulomb earth pressure on retaining wall by genetic algorithm |
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| ZHAO Tong-bin,TAN Yun-liang,WANG Hong,SUN Zhen-wu,XIAO Ya-xun.Analytical solution of Coulomb earth pressure on retaining wall by genetic algorithm[J].Rock and Soil Mechanics,2009,30(4):1170-1174. |
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| Authors: | ZHAO Tong-bin TAN Yun-liang WANG Hong SUN Zhen-wu XIAO Ya-xun |
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| Institution: | 1. Key Laboratory of Mine Disaster Prevention and Control, Shandong University of Science and Technology, Qingdao 266510, China; 2. Graduate College, Shandong University of Science and Technology, Qingdao 266510, China; 3. College of Resources and Environmental Engineering, Shandong University of Science and Technology, Qingdao 266510, China |
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| Abstract: | Based on the static limit equilibrium analyses of sliding soil mass on rupture, the range of variable and the model of objective function are built to calculate the Coulomb earth pressure of cohesionless soil and cohesive soil by optimization method, and the genetic evolutionary method is used to carry out an example analytical solution. The results indicate that the genetic algorithm increases the convergence speed, shortens time and has high calculation precision in the process of calculating Coulomb active earth pressure on retaining wall. The numerical results of cohesionless soil active earth pressure on retaining wall about 5 groups from example 1 are very closer to the classical Coulomb solutions; the average error is 1.748 % and the average number of generation is 15. The numerical results of cohesive soil active earth pressure on retaining wall about 8 groups from example 2 also match well with the documents’ solutions; the average error is only 0.017 %; and the average number of generation is 17.125. The genetic algorithm is very suitable for solving optimization problem of geotechnical engineering because of its good adaptability and strong search performance. |
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| Keywords: | Coulomb earth pressure genetic algorithm optimization objective function |
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