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Geomechanics and Engineering
  Volume 1, Number 1, March 2009, pages 85-96
DOI: https://doi.org/10.12989/gae.2009.1.1.085
 


Searching for critical failure surface in slope stability analysis by using hybrid genetic algorithm
Shouju Li, Zichang Shangguan, Hongxia Duan, Yingxi Liu and Maotian Luan

 
Abstract
    The radius and coordinate of sliding circle are taken as searching variables in slope stability analysis. Genetic algorithm is applied for searching for critical factor of safety. In order to search for critical factor of safety in slope stability analysis efficiently and in a robust manner, some improvements for simple genetic algorithm are proposed. Taking the advantages of efficiency of neighbor-search of the simulated annealing and the robustness of genetic algorithm, a hybrid optimization method is presented. The numerical computation shows that the procedure can determine the minimal factor of safety and be applied to slopes with any geometry, layering, pore pressure and external load distribution. The comparisons demonstrate that the genetic algorithm provides a same solution when compared with elasto-plastic finite element program.
 
Key Words
    hybrid genetic algorithm; slope stability; critical factor of safety; hybrid optimization.
 
Address
Shouju Li; State Key Lab. of Struct. Anal. of Ind. Equip, Dalian University of Technology, Dalian 116023, P R China
Zichang Shangguan; School of Civil and Hydraulic Engineering, Dalian University of Technology, Dalian 116023, P R China
Institute of Civil Engineering, Dalian Fishery University, Dalian 116023, P R China
Hongxia Duan; State Key Lab. of Struct. Anal. of Ind. Equip, Dalian University of Technology, Dalian 116023, P R China
College of Architecture & Civil Engineering, Dalian Nationalities University, Dalian 116605, P R China
Yingxi Liu; State Key Lab. of Struct. Anal. of Ind. Equip, Dalian University of Technology, Dalian 116023, P R China
Maotian Luan; School of Civil and Hydraulic Engineering, Dalian University of Technology, Dalian 116023, P R China
 

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