• 全国中文核心期刊
  • 中国科技核心期刊
  • 美国工程索引(EI)收录期刊
  • Scopus数据库收录期刊

边坡临界滑面搜索的改进粒子群优化算法

杨善统, 姜清辉, 尹涛, 姚池, 陈娜, 周彬

杨善统, 姜清辉, 尹涛, 姚池, 陈娜, 周彬. 边坡临界滑面搜索的改进粒子群优化算法[J]. 岩土工程学报, 2015, 37(8): 1411-1417. DOI: 10.11779/CJGE201508008
引用本文: 杨善统, 姜清辉, 尹涛, 姚池, 陈娜, 周彬. 边坡临界滑面搜索的改进粒子群优化算法[J]. 岩土工程学报, 2015, 37(8): 1411-1417. DOI: 10.11779/CJGE201508008
YANG Shan-tong, JIANG Qing-hui, YIN Tao, YAO Chi, CHEN Na, ZHOU Bin. Search of critical slip surface of slopes using improved particle swarm optimization method[J]. Chinese Journal of Geotechnical Engineering, 2015, 37(8): 1411-1417. DOI: 10.11779/CJGE201508008
Citation: YANG Shan-tong, JIANG Qing-hui, YIN Tao, YAO Chi, CHEN Na, ZHOU Bin. Search of critical slip surface of slopes using improved particle swarm optimization method[J]. Chinese Journal of Geotechnical Engineering, 2015, 37(8): 1411-1417. DOI: 10.11779/CJGE201508008

边坡临界滑面搜索的改进粒子群优化算法  English Version

基金项目: 国家重点基础研究发展计划(“973”项目)(2011CB013506); 重庆市应用开发计划重点项目(cstc2014yykfB30003)
详细信息
    作者简介:

    杨善统(1989- ),男,硕士研究生,主要从事边坡稳定分析。E-mail: 952811382@qq.com。

  • 中图分类号: P642

Search of critical slip surface of slopes using improved particle swarm optimization method

  • 摘要: 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。
    Abstract: The location of the critical slip surface is a very important issue in slope stability analysis and reinforcement design. In this study, an improved particle swarm optimization (VSPSO) algorithm is proposed to search for the critical slip surface based on particle variation (PV) and sequential quadratic programming (SQP). PV enhances the ability of PSO in jumping out of the local optimum, and SQP accelerates local search. The combination of PV and SQP greatly promotes the capacity of the original PSO in looking for the global optimum. An example with analytical solution is analyzed by the VSPSO, and the results demonstrate the accuracy and efficiency of the proposed model. Three typical examples from ACADS are then given, which are respectively homogeneous slope, multilayer soil slope and slope with weak layer. It is shown that results from the VSPSO are more approximate to the recommended values than those from the PSO. Furthermore, the VSPSO has a quite well robustness for the slopes with very complicated geometries and material properties.
  • [1] 孙君实. 条分法的提法及数值计算的最优化方法[J]. 水力发电学报, 1983(1): 52-64. (SUN Jun-shi. Slice method and numerical optimization methods[J]. Journal of Hydroelectric Engineering, 1983(1): 52-64. (in Chinese))
    [2] 陈祖煜, 邵长明. 最优化方法在确定边坡最小安全系数方面的应用[J]. 岩土工程学报, 1988, 10(4): 1-13. (CHEN Zu-yu, SHAO Chang-ming. Application of optimization methods in determining the minimum safety factor of the slope[J]. Chinese Journal of Geotechnical Engineering, 1988, 10(4): 1-13. (in Chinese))
    [3] 王成华, 夏绪勇. 边坡稳定分析中的临界滑动面搜索方法述评[J]. 四川建筑科学研究, 2002, 28(3): 34-39. (WANG Cheng-hua, XIA Xu-yong. Commentary of searching for critical slip surface in slope stability analysis[J]. Sichuan Building Science, 2002, 28(3): 34-39. (in Chinese))
    [4] 高 玮. 刘泉声. 基于仿生计算智能的地下工程反分析-理论和应用[M]. 科学出版社, 2009: 43-47. (GAO Wei, LIU Quan-sheng. Underground engineering back analysis based on bio-simulated evolution-theory and application[M]. Beijing: Science Press, 2009: 43-47. (in Chinese))
    [5] SHI Y H, EBERHART R C. Experical study of particle swarm optimization[C]// Proceedings of SCI Conference. Orlando, 2000.
    [6] 张 慧. 李立增. 王成华. 粒子群算法在确定边坡最小安全系数中的应用[J]. 石家庄铁道学院学报, 2004, 17(2): 1-5. (ZHANG Hui, LI Li-zeng, WANG Cheng-hua. Application of particle swarm algorithm in determining the minimum safety factor of slope[J]. Journal of Shijiazhuang Tiedao University, 2004, 17(2): 1-5. (in Chinese))
    [7] 李 亮, 迟世春, 林 皋. 粒子群优化复合形法求解复杂土坡最小安全系数[J]. 岩土力学, 2005, 26(9): 1393-1398. (LI Liang, CHI Shi-chun, LIN Gao. Improved complex method based on particle swarm optimization algorithm and its application to slope stability analysis[J]. Rock and Soil Mechanics, 2005, 26(9): 1393-1398. (in Chinese))
    [8] 李爱国, 覃 征, 鲍复民, 等. 粒子群优化算法[J]. 计算机工程与应用, 2002, 38(21): 1-3. (LI Ai-guo, QIN Zheng, BAO Fu-min, et al. Particle swarm optimization algorithms[J]. Computer Engineering and Applications, 2002, 38(21): 1-3. (in Chinese))
    [9] 杨 维, 李歧强. 粒子群优化算法综述[J]. 中国工程科学, 2004, 6(5): 87-94. (YANG Wei, LI Qi-qiang. Summary of particle swarm optimization algorithm[J]. Engineering Science, 2004, 6(5): 87-94. (in Chinese))
    [10] SHI Y, EBERHART R. Parameter selection in particle swarm optimiza-tion[C]// Proceedings of 7th Annual Conference on Evolution Com-putation. San Diego , 1998: 591-601.
    [11] SHI Y, EBERHART R. Empirical study of particle swarm optimization[C]// Proceedings of the 1999 Congress on Evolutionary Computation. Washington, 1999: 1945-1950.
    [12] ZHANG Hai-xia, YUAN Dong-feng, JIANG Ming-yan, et al. Research of DFT-OFDM and DWT-OFDM on different transmission scenarios[C]// ICITA . Harbin, 2004: 31-33.
    [13] 崔红梅, 朱庆保. 微粒群算法的参数选择及收敛性分析[J]. 计算机工程与应用, 2007, 43(23): 89-91. (CUI Hong-mei, ZHU Qing-bao. Convergence analysis and parameter selection in particle swarm optimization[J]. Computer Engineering and Applications, 2007, 43(23): 89-91. (in Chinese))
    [14] Kennedy. The particle swarm: social adaptation of knowledge[C]// Proceedings of the 1997 International Conference on Evolutionary Cornputation. Piseataway, 1997: 303-308.
    [15] 王 伟. 改进粒子群优化算法在边坡工程力学参数反演中的应用[D]. 南京: 河海大学, 2007. (WANG Wei. The application of an improved particle swarm optimization in inversion of mechanical parameter of slope engineering[D]. Nanjing: Hohai University, 2007. (in Chinese))
    [16] 漆祖芳, 姜清辉, 周创兵, 等. 基于v-SVR和MVPSO算法的边坡位移反分析方法及其应用[J]. 岩石力学与工程学报, 2013, 32(6): 1185-1196. (QI Zu-fang, JIANG Qing-hui, ZHOU Chuang-bing, et al. A new displacement back analysis method based on v-SVR and MVPSO algorithm and its application[J]. Chinese Journal of Rock Mechanics and Engineering, 2013, 32 (6): 1185-1196. (in Chinese))
    [17] JIANG Y, HU T, HUANG C C, et al. An improved particle swarm optimization algorithm[J]. Applied Mathematics and Computation, 2007, 193(1): 231-239.
    [18] 吕振肃, 侯志容. 自适应变异的粒子群优化算法[J]. 电子学报, 2004, 32(3): 416-420. (LÜ Zhen-su, HOU Zhi-rong. Particle swarm optimization with adaptive mutation[J]. Acta Electronica Sinica, 2004, 32(3): 416-420. (in Chinese))
    [19] WILSON R B. A simplicial algorithm for concave programming[D]. Boston: Graduate School of Business Administration, Harvard University, 1963.
    [20] 夏晓华, 刘 波, 金以慧. 基于微粒群优化的序贯二次规划方法[J]. 计算机工程与应用, 2006, 23: 69-71. (XIA Xiao-hua, LIU Bo, JIN Yi-hui. Suquential quadratic programming based on particleswarm optimization[J]. Computer Engineering and Applications, 2006, 23: 69-71. (in Chinese))
    [21] 徐文星, 耿志强, 朱群雄, 等. 基于SQP局部搜索的混沌粒子群优化算法[J]. 控制与决策, 2012, 27(4): 557-561. (XU Wen-xing, GENG Zhi-qiang, ZHU Qun-xiong, et al. Chaos particle swarm optimization algorithm integrated with sequential quadratic programming local search[J]. Control and Decision, 2012, 27(4): 557-561. (in Chinese))
    [22] 陈云敏, 魏新江, 李育超. 边坡非圆弧临界滑动面的粒子群优化算法[J]. 岩石力学与工程学报, 2006, 25(7):1443-1449. (CHEN Yun-min, WEI Xin-jiang, LI Yu-chao. Locating non-circular critical slip surfaces by particle swarm optimization algorithm[J]. Chinese Journal of Rock Mechanics and Engineering, 2006, 25(7): 1443-1449. (in Chinese))
    [23] SUN J, LI J, LIU Q. Search for critical slip surface in slope stability analysis by spline-based GA method[J]. Journal of Geotechnical and Geoenvironmental Engineering, 2008, 134(2): 252-256.
    [24] 陈祖煜. 土质边坡稳定分析—原理、方法、程序[M]. 北京: 中国水利电力出版社, 2002. (CHEN Zu-yu. Stability analysis of soil slope—theory, method and application[M]. Beijing: China Water Resources and Electric Power Press, 2002. (in Chinese))
    [25] LI K S, WHITE W. Rapid evaluation of the critical slip surface in slope stability problems[J]. International Journal for Numerical and Analytical Methods in Geomechanics, 1987, 11(5): 449-473.
    [26] BOUTRUP E, LOVELL C W. Search technique in slope stability analysis[J]. Engineering Geology, 1980, 16(1): 51-61.
    [27] MALLIPEDDI R, SUGANTHAN P N. Problem definitions and evaluation criteria for the CEC 2010 competition on constrained real-parameter optimization[D]. Singapore: Nanyang Technological University, 2010.
    [28] 东南大学, 浙江大学, 湖南大学, 等. 土力学[M]. 北京: 中国建筑工业出版社, 2005: 256-257. (Southeast University, Zhejiang University, Hunan University, et al. Soil mechanics[M]. Beijing: China Architecture & Building Press, 2005: 256-257. (in Chinese)
  • 期刊类型引用(19)

    1. 梁贤伟,郭子亮,袁梓文,穆保岗. 基于MRA-BP神经网络的桩基托换桥墩沉降预测模型研究. 特种结构. 2025(01): 82-86+97 . 百度学术
    2. 杜策,张振,张力,周振,叶怀文. 桩基托换对邻近深基坑历史建筑的变形影响控制研究. 施工技术(中英文). 2024(23): 23-28 . 百度学术
    3. 李旭,郑少强,佟庆伟,绳虎. 多种支护模式下基坑监测数据处理与分析. 山西建筑. 2023(05): 80-84 . 百度学术
    4. 徐现启,马炜,邓才兵,孙书淳. 岩质顺层破碎采石场开挖边坡稳定性分析. 云南水力发电. 2023(02): 17-24 . 百度学术
    5. 田书广,高佳豪,周喻,李想,裴博文,刘汝辉,田峰,李坤. 不断流情况下明挖基坑穿河施工变形特性研究. 建筑结构. 2023(S2): 2024-2032 . 百度学术
    6. 孙若翔. 复杂环境下城市建筑深基坑变形与数值模拟分析. 江西建材. 2022(01): 37-40 . 百度学术
    7. 臧一平,卜成,邵苏文,孙晋晶. 地铁盾构隧道下穿桥梁桩基被动托换加固研究. 山西建筑. 2022(06): 139-143 . 百度学术
    8. 高成雷. 城区明挖基坑地下连续墙支撑体系稳定性研究及监测分析. 建筑技术开发. 2022(10): 148-151 . 百度学术
    9. 阮小勇. 桥梁桩基的门架式托换结构及工作特性研究. 科技创新与应用. 2022(31): 82-88 . 百度学术
    10. 陈治雄. 福州火车站南广场深基坑支护和土方开挖施工关键技术. 建筑技术开发. 2022(19): 139-142 . 百度学术
    11. 杨正华,段军朝,郭庆军,鄢玉胜. 异型变宽连续梁桩基托换变形监测分析. 城市轨道交通研究. 2022(12): 106-111 . 百度学术
    12. 李红,王初生. 隧道桩基主动托换加固效果仿真评价方法. 计算机仿真. 2021(04): 188-192 . 百度学术
    13. 朱会强,张明,张波,张建设,郭波锋. 黄河中下游冲洪积地层PRC管桩深基坑支护. 河南科学. 2021(06): 964-970 . 百度学术
    14. 陈祉阳,王文柱. 地铁车站明挖基坑下穿互通立交桥基础的施工关键技术及变形影响分析. 建筑结构. 2021(S1): 1952-1956 . 百度学术
    15. 吴毅彬,郑伟. 某城际铁路车站天桥主动托换施工方案. 厦门理工学院学报. 2021(03): 62-69 . 百度学术
    16. 闫强,廉向东,凌建明. 边坡开挖支护时序有限元分析. 交通运输工程学报. 2020(03): 61-71 . 百度学术
    17. 郭在旭,向俐蓉,刘会娟,孙晓. 藏东南砂层路堑分层开挖下钻孔桩响应研究. 高速铁路技术. 2020(05): 51-56 . 百度学术
    18. 陈伟志,蒋关鲁,刘勇,陈虹羽. 川藏铁路钻孔桩加固斜坡路基的振动台试验研究. 岩石力学与工程学报. 2020(12): 2540-2556 . 百度学术
    19. 付艳军. 车站基坑开挖对邻近立交桥的影响特性研究. 云南水力发电. 2019(06): 117-121 . 百度学术

    其他类型引用(5)

计量
  • 文章访问数: 
  • HTML全文浏览量:  0
  • PDF下载量: 
  • 被引次数: 24
出版历程
  • 收稿日期:  2014-10-06
  • 发布日期:  2015-08-24

目录

    /

    返回文章
    返回