Lightning search algorithm: a comprehensive survey

Abualigah, L; Elaziz, MA; Hussien, AG; Alsalibi, B; Jalali, SMJ; Gandomi, AH

Lightning search algorithm: a comprehensive survey

Abualigah, L Elaziz, MA Hussien, AG Alsalibi, B Jalali, SMJ Gandomi, AH

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Publisher:: Springer
Publication Type:: Journal Article
Citation:: Applied Intelligence, 2021, 51, (4), pp. 2353-2376
Issue Date:: 2021

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Field	Value	Language
dc.contributor.author	Abualigah, L
dc.contributor.author	Elaziz, MA
dc.contributor.author	Hussien, AG
dc.contributor.author	Alsalibi, B
dc.contributor.author	Jalali, SMJ
dc.contributor.author	Gandomi, AH
dc.date.accessioned	2022-03-23T02:23:22Z
dc.date.available	2020-09-12
dc.date.available	2022-03-23T02:23:22Z
dc.date.issued	2021
dc.identifier.citation	Applied Intelligence, 2021, 51, (4), pp. 2353-2376
dc.identifier.issn	0924-669X
dc.identifier.issn	1573-7497
dc.identifier.uri	http://hdl.handle.net/10453/155478
dc.description.abstract	The lightning search algorithm (LSA) is a novel meta-heuristic optimization method, which is proposed in 2015 to solve constraint optimization problems. This paper presents a comprehensive survey of the applications, variants, and results of the so-called LSA. In LSA, the best-obtained solution is defined to improve the effectiveness of the fitness function through the optimization process by finding the minimum or maximum costs to solve a specific problem. Meta-heuristics have grown the focus of researches in the optimization domain, because of the foundation of decision-making and assessment in addressing various optimization problems. A review of LSA variants is displayed in this paper, such as the basic, binary, modification, hybridization, improved, and others. Moreover, the classes of the LSA’s applications include the benchmark functions, machine learning applications, network applications, engineering applications, and others. Finally, the results of the LSA is compared with other optimization algorithms published in the literature. Presenting a survey and reviewing the LSA applications is the chief aim of this survey paper.
dc.format	Print-Electronic
dc.language	eng
dc.publisher	Springer
dc.relation.ispartof	Applied Intelligence
dc.relation.isbasedon	10.1007/s10489-020-01947-2
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0801 Artificial Intelligence and Image Processing
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	Lightning search algorithm: a comprehensive survey
dc.type	Journal Article
utslib.citation.volume	51
utslib.location.activity	Netherlands
utslib.for	0801 Artificial Intelligence and Image Processing
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	open_access	*
pubs.consider-herdc	false
dc.date.updated	2022-03-23T02:23:15Z
pubs.issue	4
pubs.publication-status	Published
pubs.volume	51
utslib.citation.issue	4

Abstract:

The lightning search algorithm (LSA) is a novel meta-heuristic optimization method, which is proposed in 2015 to solve constraint optimization problems. This paper presents a comprehensive survey of the applications, variants, and results of the so-called LSA. In LSA, the best-obtained solution is defined to improve the effectiveness of the fitness function through the optimization process by finding the minimum or maximum costs to solve a specific problem. Meta-heuristics have grown the focus of researches in the optimization domain, because of the foundation of decision-making and assessment in addressing various optimization problems. A review of LSA variants is displayed in this paper, such as the basic, binary, modification, hybridization, improved, and others. Moreover, the classes of the LSA’s applications include the benchmark functions, machine learning applications, network applications, engineering applications, and others. Finally, the results of the LSA is compared with other optimization algorithms published in the literature. Presenting a survey and reviewing the LSA applications is the chief aim of this survey paper.

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http://hdl.handle.net/10453/155478