Two-layer preference models with methodologies using induced aggregation in management administration and decision making

Zhu, C; Mesiar, R; Yager, RR; Merigo, J; Qin, J; Feng, X; Jin, L

Two-layer preference models with methodologies using induced aggregation in management administration and decision making

Zhu, C Mesiar, R Yager, RR Merigo, J Qin, J Feng, X Jin, L

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Publisher:: IOS PRESS
Publication Type:: Journal Article
Citation:: Journal of Intelligent and Fuzzy Systems, 2019, 37, (1), pp. 1213-1221
Issue Date:: 2019-01-01

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Field	Value	Language
dc.contributor.author	Zhu, C
dc.contributor.author	Mesiar, R
dc.contributor.author	Yager, RR
dc.contributor.author	Merigo, J
dc.contributor.author	Qin, J
dc.contributor.author	Feng, X
dc.contributor.author	Jin, L
dc.date.accessioned	2022-08-02T01:15:06Z
dc.date.available	2022-08-02T01:15:06Z
dc.date.issued	2019-01-01
dc.identifier.citation	Journal of Intelligent and Fuzzy Systems, 2019, 37, (1), pp. 1213-1221
dc.identifier.issn	1064-1246
dc.identifier.issn	1875-8967
dc.identifier.uri	http://hdl.handle.net/10453/159472
dc.description.abstract	In this work, we propose some two-layer preference models that can be appropriately applied in management problems such as the group decision making about predicting the future market share of certain product. By introducing the convex IOWA operator paradigm and some related properties and definitions, we list some detailed preference and inducing preference models to demonstrate and exemplify the proposed conceptual frame of two-layer preference model. The convex IOWA operator paradigm facilitates the modeling process and, from mathematical view, makes it stricter. When relevant inducing information and aggregation selection change, the proposed models can be easily adapted to accommodate more different applications in decision making and evaluation.
dc.language	English
dc.publisher	IOS PRESS
dc.relation.ispartof	Journal of Intelligent and Fuzzy Systems
dc.relation.isbasedon	10.3233/JIFS-182671
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0801 Artificial Intelligence and Image Processing, 1702 Cognitive Sciences
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	Two-layer preference models with methodologies using induced aggregation in management administration and decision making
dc.type	Journal Article
utslib.citation.volume	37
utslib.for	0801 Artificial Intelligence and Image Processing
utslib.for	1702 Cognitive Sciences
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	2022-08-02T01:15:04Z
pubs.issue	1
pubs.publication-status	Published
pubs.volume	37
utslib.citation.issue	1

Abstract:

In this work, we propose some two-layer preference models that can be appropriately applied in management problems such as the group decision making about predicting the future market share of certain product. By introducing the convex IOWA operator paradigm and some related properties and definitions, we list some detailed preference and inducing preference models to demonstrate and exemplify the proposed conceptual frame of two-layer preference model. The convex IOWA operator paradigm facilitates the modeling process and, from mathematical view, makes it stricter. When relevant inducing information and aggregation selection change, the proposed models can be easily adapted to accommodate more different applications in decision making and evaluation.

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http://hdl.handle.net/10453/159472