Dual hesitant fuzzy group decision making method and its application to supplier selection

Yu, D; Li, DF; Merigó, JM

Dual hesitant fuzzy group decision making method and its application to supplier selection

Yu, D Li, DF Merigó, JM

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Publisher:: SPRINGER HEIDELBERG
Publication Type:: Journal Article
Citation:: International Journal of Machine Learning and Cybernetics, 2016, 7, (5), pp. 819-831
Issue Date:: 2016-10-01

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Field	Value	Language
dc.contributor.author	Yu, D
dc.contributor.author	Li, DF
dc.contributor.author	Merigó, JM
dc.date.accessioned	2022-04-25T22:41:21Z
dc.date.available	2022-04-25T22:41:21Z
dc.date.issued	2016-10-01
dc.identifier.citation	International Journal of Machine Learning and Cybernetics, 2016, 7, (5), pp. 819-831
dc.identifier.issn	1868-8071
dc.identifier.issn	1868-808X
dc.identifier.uri	http://hdl.handle.net/10453/156585
dc.description.abstract	The concept of dual hesitant fuzzy set arising from hesitant fuzzy set is generalized by including a function reflecting the decision maker’s fuzziness about the non-membership degree of the information provided. This paper studies some dual hesitant fuzzy information aggregation operators for aggregating dual hesitant fuzzy elements, such as dual hesitant fuzzy Heronian mean operator and dual hesitant fuzzy geometric Heronian mean operator. The research resulting dual hesitant fuzzy information aggregation operators finds an important role in group decision making (GDM) applications. It can fusion the experts’ opinion to the comprehensive ones and based on which an optimal decision making scheme can be determined. The properties of the proposed operators are studied and the application on GDM are investigated. The effectiveness of the GDM method is demonstrated on the case study about supplier selection.
dc.language	English
dc.publisher	SPRINGER HEIDELBERG
dc.relation.ispartof	International Journal of Machine Learning and Cybernetics
dc.relation.isbasedon	10.1007/s13042-015-0400-3
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0801 Artificial Intelligence and Image Processing
dc.title	Dual hesitant fuzzy group decision making method and its application to supplier selection
dc.type	Journal Article
utslib.citation.volume	7
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
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
dc.date.updated	2022-04-25T22:41:18Z
pubs.issue	5
pubs.publication-status	Published
pubs.volume	7
utslib.citation.issue	5

Abstract:

The concept of dual hesitant fuzzy set arising from hesitant fuzzy set is generalized by including a function reflecting the decision maker’s fuzziness about the non-membership degree of the information provided. This paper studies some dual hesitant fuzzy information aggregation operators for aggregating dual hesitant fuzzy elements, such as dual hesitant fuzzy Heronian mean operator and dual hesitant fuzzy geometric Heronian mean operator. The research resulting dual hesitant fuzzy information aggregation operators finds an important role in group decision making (GDM) applications. It can fusion the experts’ opinion to the comprehensive ones and based on which an optimal decision making scheme can be determined. The properties of the proposed operators are studied and the application on GDM are investigated. The effectiveness of the GDM method is demonstrated on the case study about supplier selection.

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http://hdl.handle.net/10453/156585