APPLICATION OF PARTICLE SWARM OPTIMIZATION BASED ON HARMONY SEARCH STRATEGY IN SLOPE STABILITY ANALYSIS

Li Liang; Yu Guangming; Lu Shibao; Chu Xuesong

doi:10.13204/j.gyjz200912017

Volume 39 Issue 12

Dec. 2014

Turn off MathJax

Article Contents

Article Navigation > INDUSTRIAL CONSTRUCTION > 2009 > 39(12): 65-69,129

Li Liang, Yu Guangming, Lu Shibao, Chu Xuesong. APPLICATION OF PARTICLE SWARM OPTIMIZATION BASED ON HARMONY SEARCH STRATEGY IN SLOPE STABILITY ANALYSIS[J]. INDUSTRIAL CONSTRUCTION, 2009, 39(12): 65-69,129. doi: 10.13204/j.gyjz200912017

Citation:

Li Liang, Yu Guangming, Lu Shibao, Chu Xuesong. APPLICATION OF PARTICLE SWARM OPTIMIZATION BASED ON HARMONY SEARCH STRATEGY IN SLOPE STABILITY ANALYSIS[J]. INDUSTRIAL CONSTRUCTION, 2009, 39(12): 65-69,129. doi: 10.13204/j.gyjz200912017

Citation:

PDF( 0 KB)

APPLICATION OF PARTICLE SWARM OPTIMIZATION BASED ON HARMONY SEARCH STRATEGY IN SLOPE STABILITY ANALYSIS

doi: 10.13204/j.gyjz200912017

1.
School of Civil Engineering,Qingdao Technological University,Qingdao 266033,China

Received Date: 2009-03-30
Publish Date: 2009-12-20

Abstract

Abstract

The determination of critical slip surfaces within soil slope stability analysis based on limit equilibrium method is a complicated optimization problem.However,there may exist such disadvantages as more related parameters,difficult to be determined and the possibility of exceeding the allowed ranges,when original particle swarm optimization(PSO) is used to locate the critical slip surfaces of soil slopes.The search procedure used in original PSO and the harmony search procedure are combined to generate a new position of particle in the new algorithm presented in this paper.The new algorithm takes good advantage of both PSO and HSA(harmony search algorithm),the new algorithm is applied to perform the slope stability analysis and the comparative study shows that the new algorithm is simple and can be used for slope stability analysis.
- slope stability,
- factor of safety,
- particle swarm optimization,
- harmony search strategy

FullText(HTML)

References(20)

References

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.

[2] 李亮,迟世春,林皋.一类新复合形法及其在临界滑动面搜索中的应用[J].岩土工程学报,2005,27(4):448-453.

[3] 李亮,迟世春,林皋.基于最大伪梯度搜索的多样复合形法及其在边坡稳定分析中的应用[J].水力发电学报,2005,24(6):20-24.

[4] 李亮,迟世春,林皋.基于最大熵原理的复合形法及其在边坡稳定分析中的应用[J].中国工程科学,2005,7(4):64-68.

[5] Chen Z Y.Random Trials Used in Determining Global MinimumFactors of Safety of Slopes[J].Canadian Geotechnical Journal,1992,29(2):225-233.

[6] 张鲁渝,张建民.基于Monte Carlo技术的临界滑动面搜索算法的实现及其改进[J].岩土工程学报,2006,28(7):857-862.

[7] 肖专文,张奇志,顾兆岑,等.边坡最小安全系数的遗传算法[J].沈阳建筑工程学院学报,1996,12(2):144-147.

[8] Zolfaghari A R,Heath A C,McCombie P F.Simple GeneticAlgorithm Search for Critical Non-Circular Failure Surface in SlopeStability Analysis.Computers and Geotechnics,2005,32(3):139-152.

[9] 李守巨,刘迎曦,何翔,等.基于模拟退火算法的边坡最小安全系数全局搜索方法[J].岩石力学与工程学报,2003,22(2):236-240.

[10] 谭新,丁万涛,李术才.一个新的非圆弧滑动全局最优化算法[J].岩石力学与工程学报,2005,24(12):2060-2064.

[11] 陈昌富,龚晓南,王贻荪.自适应蚁群算法及其在边坡工程中的应用[J].浙江大学学报:工学版,2003,37(5):566-569.

[12] 王成华,夏绪勇,李广信.基于应力场的土坡临界滑动面的蚂蚁算法搜索技术[J].岩石力学与工程学报,2003,22(5):813-819.

[13] 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.

[14] 李亮,迟世春,林皋.基于粒子群优化的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.

[15] 李亮,迟世春,林皋.禁忌鱼群算法及其在边坡稳定分析中的应用[J].工程力学,2006,23(3):6-10.

[16] 李亮,迟世春,林皋.改进和声搜索算法及其在土坡稳定分析中的应用[J].土木工程学报,2006,39(5):107-111.

[17] Spencer E.A Method of Analysis for Stability of Embankments UsingParallel Inter-Slice Forces[J].Geotechnique,1967,17:11-26.

[18] Kennedy J,Eberhart R.Particle Swarm Optimization[C]∥International Conference on Neural Networks.New Jersey:IEEEService Center,Piscataway,1995:1942-1948.

[19] Geem Z W,Kim J H,Loganathan G V.Harmony Search[J].Simulation,2001,76(2):60-68.

[20] 李亮,迟世春,郑榕明,等.混合粒子群算法搜索土坡危险滑动面[J].工业建筑,2007,37(2):52-57.

Relative Articles

Supplements(0)

Cited By

Proportional views