Simple genetic algorithm search for critical non-circular failure surface in slope stability analysis

Zolfaghari, A R; Heath, Andrew; McCombie, Paul

doi:10.1016/j.compgeo.2005.02.001

Cited by 233 publications

(158 citation statements)

References 11 publications

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“…Whilst the application of stochastic search methodologies is not new both in slope stability [16,17] and mining engineering [18,19], the GA proposed here is a non-standard one and allows a relatively quick convergence to the optimal solution showing excellent stability and robustness, both in case of problems with many variables and enforcing the GA to work with small populations (micro-GA).…”

Section: Introductionmentioning

confidence: 99%

A Genetic Algorithm with Zooming for the Determination of the Optimal Open Pit Mines Layout

Milani

2016

TOCIEJ

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Abstract:A Genetic Algorithm (GA) with nested zooming strategy is proposed for the determination of the optimal open pit mine design.Different genetic procedures are applied to increase robustness, namely two typologies of admissible mutations for the elite subpopulation subjected to zooming and mutation and reproduction for the remaining individuals. In order to further improve convergence rate, a user-defined population percentage, depending on individuals fitness, is replaced with new phenotypes, enforcing chromosomic renewal.Several comparisons with (traditionally used) dynamic programming approaches are provided both for 2D and 3D open pit mines. Both small and large scale mines are analyzed, to benchmark the code in presence of several variables.Results show that the procedure proposed requires a very limited computational effort, both for challenging problems with several variables and when a micro-GA (populations with few individuals) is adopted for small scale problems.

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Section: Introductionmentioning

confidence: 99%

A Genetic Algorithm with Zooming for the Determination of the Optimal Open Pit Mines Layout

Milani

2016

TOCIEJ

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“…Among the modern stochastic global optimization methods that have evolved in recent years, there are only limited applications in geotechnical engineering. The simulated annealing method, PSO, HM, ant-colony and Tabu search are first adopted by Cheng [25][26][27][28], while the genetic algorithm have been adopted by Zolfaghari et al [23] and Cheng et al [27] and the leap-frog algorithm adopted by Bolton et al [24]. Cheng et al [27] have carried out a detailed comparisons between six major types of stochastic global optimization methods, and the sensitivity of these methods under different optimization parameters are investigated.…”

Section: Introductionmentioning

confidence: 99%

“…Greco [21] and Malkawi et al [22] adopted the Monte Carlo technique for searching the critical slip surface with success for some cases, but there is no precision control on the accuracy of the global minimum. Zolfaghari et al [23] adopted the genetic algorithm while Bolton et al [24] used the leap-frog optimization technique to evaluate the minimum factor of safety. Among the modern stochastic global optimization methods that have evolved in recent years, there are only limited applications in geotechnical engineering.…”

Section: Introductionmentioning

confidence: 99%

Improved Harmony Search Methods to Replace Variational Principle in Geotechnical Problems

Cheng

Fang

2011

J. mech.

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Variational principle is an important principle in engineering discipline. This principle is suitable for simple problems where an analytical expression can be determined, but there are many practical problems where the classical variational principle is practically impossible to be applied. In this paper, the authors will try to demonstrate that the variational principle can be replaced by the use of modern artificial intelligence based optimization method (harmony search method) which can be applied to much more complicated problems. Two different improved harmony search algorithms are proposed in this paper. The new algorithms differ from the original algorithm in that: (1) The harmonies are rearranged into several pairs and the better pairs are used to develop several new harmonies; (2) Different probabilities are assigned to different harmonies. The robustness of the proposed methods is demonstrated by using three difficult examples, and the sensitivities of the related optimization parameters are investigated through statistical orthogonal analysis.

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“…Guan et al 2009;Levasseur et al 2008Levasseur et al , 2010, identification of critical slip surfaces in slope stability (see e.g. Zolfaghari et al 2005;Xue and Gavin 2007;Fahd and Jimenez 2008) and the reliability of finite elements (FE) designs (Cui and Sheng 2005). Similarly, in rock mechanics, GAs have been employed to identify the discontinuity frequency in fractured rock masses (Simpson and Priest 1993), for discontinuity clustering and estimation of discontinuity orientation (Kemeny and Post 2003;Cai et al 2005) and to estimate the size and shape of rectangular fractures with constant size and aspect ratio (Decker and Mauldon 2006).…”

Section: Introductionmentioning

confidence: 99%

A Simple Genetic Algorithm for Calibration of Stochastic Rock Discontinuity Networks

Jimenez

Jurado-Piña

2012

Rock Mech Rock Eng

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We present a novel approach for calibration of stochastic discontinuity network parameters based on genetic algorithms (GAs). To validate the approach, examples of application of the method to cases with known parameters of the original Poisson discontinuity network are presented. Parameters of the model are encoded as chromosomes using a binary representation, and such chromosomes evolve as successive generations of a randomly generated initial population, subjected to GA operations of selection, crossover and mutation. Such backcalculated parameters are employed to make assessments about the inference capabilities of the model using different objective functions with different probabilities of crossover and mutation. Results show that the predictive capabilities of GAs significantly depend on the type of objective function considered; and they also show that the calibration capabilities of the genetic algorithm can be acceptable for practical engineering applications, since in most cases they can be expected to provide parameter estimates with relatively small errors for those parameters of the network (such as intensity and mean size of discontinuities) that have the strongest influence on many engineering applications.

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Simple genetic algorithm search for critical non-circular failure surface in slope stability analysis

Cited by 233 publications

References 11 publications

A Genetic Algorithm with Zooming for the Determination of the Optimal Open Pit Mines Layout

A Genetic Algorithm with Zooming for the Determination of the Optimal Open Pit Mines Layout

Improved Harmony Search Methods to Replace Variational Principle in Geotechnical Problems

A Simple Genetic Algorithm for Calibration of Stochastic Rock Discontinuity Networks

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