A Survey of Learning-Based Intelligent Optimization Algorithms

Li, W; Wang, GG; Gandomi, AH

A Survey of Learning-Based Intelligent Optimization Algorithms

Li, W Wang, GG Gandomi, AH

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Publisher:: SPRINGER
Publication Type:: Journal Article
Citation:: Archives of Computational Methods in Engineering, 2021, 28, (5), pp. 3781-3799
Issue Date:: 2021-08-01

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Field	Value	Language
dc.contributor.author	Li, W
dc.contributor.author	Wang, GG
dc.contributor.author	Gandomi, AH
dc.date.accessioned	2021-09-29T20:26:37Z
dc.date.available	2021-09-29T20:26:37Z
dc.date.issued	2021-08-01
dc.identifier.citation	Archives of Computational Methods in Engineering, 2021, 28, (5), pp. 3781-3799
dc.identifier.issn	1134-3060
dc.identifier.issn	1886-1784
dc.identifier.uri	http://hdl.handle.net/10453/150737
dc.description.abstract	A large number of intelligent algorithms based on social intelligent behavior have been extensively researched in the past few decades, through the study of natural creatures, and applied to various optimization fields. The learning-based intelligent optimization algorithm (LIOA) refers to an intelligent optimization algorithm with a certain learning ability. This is how the traditional intelligent optimization algorithm combines learning operators or specific learning mechanisms to give itself some learning ability, thereby achieving better optimization behavior. We conduct a comprehensive survey of LIOAs in this paper. The research includes the following sections: Statistical analysis about LIOAs, classification of LIOA learning method, application of LIOAs in complex optimization scenarios, and LIOAs in engineering applications. The future insights and development direction of LIOAs are also discussed.
dc.language	English
dc.publisher	SPRINGER
dc.relation.ispartof	Archives of Computational Methods in Engineering
dc.relation.isbasedon	10.1007/s11831-021-09562-1
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	01 Mathematical Sciences, 08 Information and Computing Sciences, 09 Engineering
dc.subject.classification	Applied Mathematics
dc.title	A Survey of Learning-Based Intelligent Optimization Algorithms
dc.type	Journal Article
utslib.citation.volume	28
utslib.for	01 Mathematical Sciences
utslib.for	08 Information and Computing Sciences
utslib.for	09 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	*
dc.date.updated	2021-09-29T20:26:36Z
pubs.issue	5
pubs.publication-status	Published
pubs.volume	28
utslib.citation.issue	5

Abstract:

A large number of intelligent algorithms based on social intelligent behavior have been extensively researched in the past few decades, through the study of natural creatures, and applied to various optimization fields. The learning-based intelligent optimization algorithm (LIOA) refers to an intelligent optimization algorithm with a certain learning ability. This is how the traditional intelligent optimization algorithm combines learning operators or specific learning mechanisms to give itself some learning ability, thereby achieving better optimization behavior. We conduct a comprehensive survey of LIOAs in this paper. The research includes the following sections: Statistical analysis about LIOAs, classification of LIOA learning method, application of LIOAs in complex optimization scenarios, and LIOAs in engineering applications. The future insights and development direction of LIOAs are also discussed.

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http://hdl.handle.net/10453/150737