An introduction of Krill Herd algorithm for engineering optimization

Gandomi, AH; Alavi, AH

An introduction of Krill Herd algorithm for engineering optimization

Gandomi, AH Alavi, AH

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Publisher:: VILNIUS GEDIMINAS TECH UNIV
Publication Type:: Journal Article
Citation:: Journal of Civil Engineering and Management, 2016, 22, (3), pp. 302-310
Issue Date:: 2016-04-02

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Field	Value	Language
dc.contributor.author	Gandomi, AH
dc.contributor.author	Alavi, AH
dc.date.accessioned	2022-08-12T20:59:50Z
dc.date.available	2022-08-12T20:59:50Z
dc.date.issued	2016-04-02
dc.identifier.citation	Journal of Civil Engineering and Management, 2016, 22, (3), pp. 302-310
dc.identifier.issn	1392-3730
dc.identifier.issn	1822-3605
dc.identifier.uri	http://hdl.handle.net/10453/160049
dc.description.abstract	A new metaheuristic optimization algorithm, called Krill Herd (KH), has been recently proposed by Gandomi and Alavi (2012). In this study, KH is introduced for solving engineering optimization problems. For more verification, KH is applied to six design problems reported in the literature. Further, the performance of the KH algorithm is compared with that of various algorithms representative of the state-of-the-art in the area. The comparisons show that the results obtained by KH are better than the best solutions obtained by the existing methods.
dc.language	English
dc.publisher	VILNIUS GEDIMINAS TECH UNIV
dc.relation.ispartof	Journal of Civil Engineering and Management
dc.relation.isbasedon	10.3846/13923730.2014.897986
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0905 Civil Engineering, 1202 Building
dc.subject.classification	Civil Engineering
dc.title	An introduction of Krill Herd algorithm for engineering optimization
dc.type	Journal Article
utslib.citation.volume	22
utslib.for	0905 Civil Engineering
utslib.for	1202 Building
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	2022-08-12T20:59:48Z
pubs.issue	3
pubs.publication-status	Published
pubs.volume	22
utslib.citation.issue	3

Abstract:

A new metaheuristic optimization algorithm, called Krill Herd (KH), has been recently proposed by Gandomi and Alavi (2012). In this study, KH is introduced for solving engineering optimization problems. For more verification, KH is applied to six design problems reported in the literature. Further, the performance of the KH algorithm is compared with that of various algorithms representative of the state-of-the-art in the area. The comparisons show that the results obtained by KH are better than the best solutions obtained by the existing methods.

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http://hdl.handle.net/10453/160049