Slope stability analysis using evolutionary optimization techniques

Gandomi, AH; Kashani, AR; Mousavi, M; Jalalvandi, M

Slope stability analysis using evolutionary optimization techniques

Gandomi, AH Kashani, AR Mousavi, M Jalalvandi, M

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Publisher:: John Wiley and Sons
Publication Type:: Journal Article
Citation:: International Journal for Numerical and Analytical Methods in Geomechanics, 2017, 41, (2), pp. 251-264
Issue Date:: 2017-02-10

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Field	Value	Language
dc.contributor.author	Gandomi, AH
dc.contributor.author	Kashani, AR
dc.contributor.author	Mousavi, M
dc.contributor.author	Jalalvandi, M
dc.date.accessioned	2022-08-25T01:26:44Z
dc.date.available	2022-08-25T01:26:44Z
dc.date.issued	2017-02-10
dc.identifier.citation	International Journal for Numerical and Analytical Methods in Geomechanics, 2017, 41, (2), pp. 251-264
dc.identifier.issn	0363-9061
dc.identifier.issn	1096-9853
dc.identifier.uri	http://hdl.handle.net/10453/160812
dc.description.abstract	Slope stability optimization, in the presence of a band of a weak layer between two strong layers, is accounted for in complicated geotechnical problems. Classical optimization algorithms are not suitable for solving such problems as they need a proper preliminary solution to converge to a valid result. Therefore, it is necessary to find a proper algorithm which is capable of finding the best global solution. Recently a lot of metaheuristic algorithms have been proposed which are able to evade local minima effectively. In this study four evolutionary algorithms, including well-known and recent ones, such as genetic algorithm, differential evolution, evolutionary strategy and biogeography-based optimization (BBO), are applied in slope stability analysis and their efficiencies are explored by three benchmark case studies. Result show BBO is the most efficient among these evolutionary algorithms and other proposed algorithms applied to this problem. Copyright © 2016 John Wiley & Sons, Ltd.
dc.language	English
dc.publisher	John Wiley and Sons
dc.relation.ispartof	International Journal for Numerical and Analytical Methods in Geomechanics
dc.relation.isbasedon	10.1002/nag.2554
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0905 Civil Engineering
dc.subject.classification	Geological & Geomatics Engineering
dc.title	Slope stability analysis using evolutionary optimization techniques
dc.type	Journal Article
utslib.citation.volume	41
utslib.for	0905 Civil Engineering
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2022-08-25T01:26:43Z
pubs.issue	2
pubs.publication-status	Published
pubs.volume	41
utslib.citation.issue	2

Abstract:

Slope stability optimization, in the presence of a band of a weak layer between two strong layers, is accounted for in complicated geotechnical problems. Classical optimization algorithms are not suitable for solving such problems as they need a proper preliminary solution to converge to a valid result. Therefore, it is necessary to find a proper algorithm which is capable of finding the best global solution. Recently a lot of metaheuristic algorithms have been proposed which are able to evade local minima effectively. In this study four evolutionary algorithms, including well-known and recent ones, such as genetic algorithm, differential evolution, evolutionary strategy and biogeography-based optimization (BBO), are applied in slope stability analysis and their efficiencies are explored by three benchmark case studies. Result show BBO is the most efficient among these evolutionary algorithms and other proposed algorithms applied to this problem. Copyright © 2016 John Wiley & Sons, Ltd.

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http://hdl.handle.net/10453/160812