Teaching–learning-based optimisation algorithm and its application in capturing critical slip surface in slope stability analysis

The identification of ideal values for algorithm-specific parameters required for the functioning of metaheuristic approaches at their optimum performance is a difficult task. This paper presents the application of a recently proposed teaching–learning-based optimisation (TLBO) algorithm to determine the lowest factor of safety (FS) along a critical slip surface for soil slope. TLBO is a nature-inspired search algorithm based on the teaching–learning phenomenon of a classroom. Four benchmark slopes are reanalysed to test the performance of the TLBO approach. The results indicate that the present technique can detect the critical failure surface and can be easily implemented by practitioners without fine-tuning the parameters that affect the convergence of results. Statistical analyses indicate a drastic decrease in uncertainty and the number of function evaluations in the estimation of the FS over previous approaches.

[1]  D. Fredlund,et al.  Comparison of slope stability methods of analysis , 1977 .

[2]  R. Venkata Rao,et al.  Teaching-learning-based optimization: A novel method for constrained mechanical design optimization problems , 2011, Comput. Aided Des..

[3]  R. V. Rao,et al.  Teaching–learning-based optimization algorithm for unconstrained and constrained real-parameter optimization problems , 2012 .

[4]  Andrew C. Heath,et al.  Simple genetic algorithm search for critical non-circular failure surface in slope stability analysis , 2005 .

[5]  Marjan Mernik,et al.  Is a comparison of results meaningful from the inexact replications of computational experiments? , 2016, Soft Comput..

[6]  J. M. Duncan.  State of the Art: Limit Equilibrium and Finite-Element Analysis of Slopes , 1996 .

[7]  P. Lumb,et al.  Probabilistic design of slopes , 1987 .

[8]  H. Wang,et al.  Slope stability evaluation using Back Propagation Neural Networks , 2005 .

[9]  Junjie Li,et al.  An artificial bee colony algorithm for locating the critical slip surface in slope stability analysis , 2013 .

[10]  Raheleh Khanduzi,et al.  A modified teaching–learning-based optimization for optimal control of Volterra integral systems , 2018, Soft Comput..

[11]  Wei Gao,et al.  Slope stability analysis based on immunised evolutionary programming , 2015, Environmental Earth Sciences.

[12]  Y. M. Cheng,et al.  Location of critical failure surface and some further studies on slope stability analysis , 2003 .

[13]  Danial Jahed Armaghani,et al.  Applying various hybrid intelligent systems to evaluate and predict slope stability under static and dynamic conditions , 2019, Soft Comput..

[14]  Bin Tian,et al.  Locating the critical slip surface in a slope stability analysis by enhanced fireworks algorithm , 2017, Cluster Computing.

[15]  Damodar Maity,et al.  Ant lion optimisation algorithm for structural damage detection using vibration data , 2018, Journal of Civil Structural Health Monitoring.

[16]  Mehdi Mousavi,et al.  Slope stability analysis using evolutionary optimization techniques , 2017 .

[17]  N. Morgenstern,et al.  The analysis of the stability of general slip surfaces , 1965 .

[18]  Yung-ming Cheng,et al.  Performance studies on six heuristic global optimization methods in the location of critical slip surface , 2007 .

[19]  Wei Gao.  Premium-penalty ant colony optimization and its application in slope stability analysis , 2016, Appl. Soft Comput..

[20]  Mehdi Mousavi,et al.  Slope stability analyzing using recent swarm intelligence techniques , 2015 .

[21]  Rasim Temür,et al.  Teaching learning-based optimization for designof cantilever retaining walls , 2016 .

[22]  D Y Zhu,et al.  A new procedure for computing the factor of safety using the Morgenstern-Price method , 2001 .

[23]  Ling Wang,et al.  Teaching–learning-based optimization algorithm for multi-skill resource constrained project scheduling problem , 2017, Soft Comput..

[24]  Ahmed El-Shafie,et al.  Locating the general failure surface of earth slope using particle swarm optimisation , 2012 .

[25]  K. Arai,et al.  DETERMINATION OF NONCIRCULAR SLIP SURFACE GIVING THE MINIMUM FACTOR OF SAFETY IN SLOPE STABILITY ANALYSIS , 1985 .

[26]  K. M. Neaupane,et al.  Determination of the critical failure surface for slope stability analysis using ant colony optimization , 2009 .

[27]  Damodar Maity,et al.  A COMPARATIVE STUDY OF SLOPE STABILITY ANALYSIS USING TRADITIONAL LIMIT EQUILIBRIUM METHOD AND FINITE ELEMENT METHOD , 2015 .

[28]  Jianping Sun,et al.  Search for Critical Slip Surface in Slope Stability Analysis by Spline-Based GA Method , 2008 .

[29]  Peter John Cleall,et al.  An efficient approach for locating the critical slip surface in slope stability analyses using a real-coded genetic algorithm , 2010 .

[30]  E. Spencer.  A Method of Analysis of the Stability of Embankments Assuming Parallel Inter-Slice Forces , 1967 .

[31]  Rodrigo Salgado,et al.  Stability Analysis of Complex Soil Slopes using Limit Analysis , 2002 .

[32]  Vedat Toğan,et al.  Design of planar steel frames using Teaching–Learning Based Optimization , 2012 .

[33]  Tayfun Dede,et al.  Optimum design of grillage structures to LRFD-AISC with teaching-learning based optimization , 2013 .

[34]  Takuo Yamagami,et al.  SEARCH FOR NONCIRCULAR SLIP SURFACES BY THE MORGENSTERN-PRICE METHOD. PROCEEDINGS OF THE SIXTH INTERNATIONAL CONFERENCE ON NUMERICAL METHODS IN GEOMECHANICS, 11-15 APRIL 1988, INNSBRUCK, AUSTRIA. VOLUMES 1 - 3 , 1988 .

[35]  Wei Gao,et al.  Investigating the critical slip surface of soil slope based on an improved black hole algorithm , 2017 .

[36]  Zhibing Liu,et al.  Assessment of slope stability under uncertain circumstances , 2018, Soft Comput..

[37]  Wei Gao,et al.  Determination of the Noncircular Critical Slip Surface in Slope Stability Analysis by Meeting Ant Colony Optimization , 2016, J. Comput. Civ. Eng..

[38]  Mehdi Mousavi,et al.  Imperialistic Competitive Algorithm: A metaheuristic algorithm for locating the critical slip surface in 2-Dimensional soil slopes , 2016 .

[39]  Ghanshyam G. Tejani,et al.  Truss topology optimization with static and dynamic constraints using modified subpopulation teaching–learning-based optimization , 2016 .

[40]  A. Goh.  Genetic algorithm search for critical slip surface in multiple-wedge stability analysis , 1999 .

[41]  Katsuhiko Arai,et al.  Influence of Strength Anisotropy on the Search for Critical Noncircular Slip Surface , 1986 .

[42]  Y. M. Cheng,et al.  An improved harmony search minimization algorithm using different slip surface generation methods for slope stability analysis , 2008 .

[43]  Dheeraj Joshi,et al.  A hybrid teaching–learning-based optimization technique for optimal DG sizing and placement in radial distribution systems , 2018, Soft Comput..

[44]  Xiaoping Zhou,et al.  Stability analysis of three-dimensional seismic landslides using the rigorous limit equilibrium method , 2014 .

[45]  Timothy W. Simpson,et al.  A genetic algorithm based method for product family design optimization , 2003 .