A fuzzy adaptive metaheuristic algorithm for identifying sustainable, economical, and earthquake-resistant reinforced concrete cantilever retaining walls

Keivanian, F; Chiong, R; Kashani, AR; Gandomi, AH

A fuzzy adaptive metaheuristic algorithm for identifying sustainable, economical, and earthquake-resistant reinforced concrete cantilever retaining walls

Keivanian, F Chiong, R Kashani, AR Gandomi, AH

Permalink

Publisher:: ELSEVIER
Publication Type:: Journal Article
Citation:: Journal of Computational Science, 2023, 70
Issue Date:: 2023-06-01

Closed Access

	Filename	Description	Size
	1-s2.0-S1877750323000388-main.pdf	Published version	9.95 MB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Keivanian, F
dc.contributor.author	Chiong, R
dc.contributor.author	Kashani, AR
dc.contributor.author	Gandomi, AH
dc.date.accessioned	2024-03-17T20:21:51Z
dc.date.available	2024-03-17T20:21:51Z
dc.date.issued	2023-06-01
dc.identifier.citation	Journal of Computational Science, 2023, 70
dc.identifier.issn	1877-7503
dc.identifier.issn	1877-7511
dc.identifier.uri	http://hdl.handle.net/10453/176809
dc.description.abstract	In earthquake-prone zones, the seismic performance of reinforced concrete cantilever (RCC) retaining walls is a critical factor. In this study, the seismic performance was investigated using horizontal and vertical pseudo-static coefficients. To tackle RCC weights and forces resulting from these earth pressures, 26 constraints for structural strengths and geotechnical stability along with 12 geometric variables are associated with each design. These constraints and design variables form a constraint optimization problem with a 12-dimensional solution space. To conduct effective search and produce sustainable and economical RCC designs that are robust against earthquake hazards, a novel adaptive fuzzy-based metaheuristic algorithm is proposed. The proposed method divides the search space into sub-regions and establishes exploration, information sharing, and exploitation search capabilities based on its novel search components. Further, fuzzy inference systems are employed to address parameterization and computational cost evaluation issues. It was found that the proposed algorithm can achieve low-cost, low-weight, and low-CO2 emission RCC designs under nine seismic conditions when compared with several classical and best-performing design optimizers.
dc.language	English
dc.publisher	ELSEVIER
dc.relation.ispartof	Journal of Computational Science
dc.relation.isbasedon	10.1016/j.jocs.2023.101978
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0802 Computation Theory and Mathematics, 0806 Information Systems
dc.subject.classification	4602 Artificial intelligence
dc.subject.classification	4606 Distributed computing and systems software
dc.subject.classification	4901 Applied mathematics
dc.title	A fuzzy adaptive metaheuristic algorithm for identifying sustainable, economical, and earthquake-resistant reinforced concrete cantilever retaining walls
dc.type	Journal Article
utslib.citation.volume	70
utslib.for	0802 Computation Theory and Mathematics
utslib.for	0806 Information Systems
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	*
dc.date.updated	2024-03-17T20:21:46Z
pubs.publication-status	Published
pubs.volume	70

Abstract:

In earthquake-prone zones, the seismic performance of reinforced concrete cantilever (RCC) retaining walls is a critical factor. In this study, the seismic performance was investigated using horizontal and vertical pseudo-static coefficients. To tackle RCC weights and forces resulting from these earth pressures, 26 constraints for structural strengths and geotechnical stability along with 12 geometric variables are associated with each design. These constraints and design variables form a constraint optimization problem with a 12-dimensional solution space. To conduct effective search and produce sustainable and economical RCC designs that are robust against earthquake hazards, a novel adaptive fuzzy-based metaheuristic algorithm is proposed. The proposed method divides the search space into sub-regions and establishes exploration, information sharing, and exploitation search capabilities based on its novel search components. Further, fuzzy inference systems are employed to address parameterization and computational cost evaluation issues. It was found that the proposed algorithm can achieve low-cost, low-weight, and low-CO2 emission RCC designs under nine seismic conditions when compared with several classical and best-performing design optimizers.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/176809