Using Ordered Weighted Average for Weighted Averages Inflation

Espinoza-Audelo, LF; León-Castro, E; Olazabal-Lugo, M; Merigó, JM; Gil-Lafuente, AM

Using Ordered Weighted Average for Weighted Averages Inflation

Espinoza-Audelo, LF León-Castro, E Olazabal-Lugo, M Merigó, JM Gil-Lafuente, AM

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Publisher:: WORLD SCIENTIFIC PUBL CO PTE LTD
Publication Type:: Journal Article
Citation:: International Journal of Information Technology and Decision Making, 2020, 19, (2), pp. 601-628
Issue Date:: 2020-03-01

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Field	Value	Language
dc.contributor.author	Espinoza-Audelo, LF
dc.contributor.author	León-Castro, E
dc.contributor.author	Olazabal-Lugo, M
dc.contributor.author	Merigó, JM
dc.contributor.author	Gil-Lafuente, AM
dc.date.accessioned	2021-02-23T11:55:04Z
dc.date.available	2021-02-23T11:55:04Z
dc.date.issued	2020-03-01
dc.identifier.citation	International Journal of Information Technology and Decision Making, 2020, 19, (2), pp. 601-628
dc.identifier.issn	0219-6220
dc.identifier.issn	1793-6845
dc.identifier.uri	http://hdl.handle.net/10453/146336
dc.description.abstract	© 2020 World Scientific Publishing Company. This paper presents the ordered weighted average weighted average inflation (OWAWAI) and some extensions using induced and heavy aggregation operators and presents the generalized operators and some of their families. The main advantage of these new formulations is that they can use two different sets of weighting vectors and generate new scenarios based on the reordering of the arguments with the weights. With this idea, it is possible to generate new approaches that under- or overestimate the results according to the knowledge and expertise of the decision-maker. The work presents an application of these new approaches in the analysis of the inflation in Chile, Colombia, and Argentina during 2017.
dc.language	English
dc.publisher	WORLD SCIENTIFIC PUBL CO PTE LTD
dc.relation.ispartof	International Journal of Information Technology and Decision Making
dc.relation.isbasedon	10.1142/S0219622020500066
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0801 Artificial Intelligence and Image Processing, 1503 Business and Management
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	Using Ordered Weighted Average for Weighted Averages Inflation
dc.type	Journal Article
utslib.citation.volume	19
utslib.for	0801 Artificial Intelligence and Image Processing
utslib.for	1503 Business and Management
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 Information, Systems and Modelling
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	closed_access	*
dc.date.updated	2021-02-23T11:55:03Z
pubs.issue	2
pubs.publication-status	Published
pubs.volume	19
utslib.citation.issue	2

Abstract:

© 2020 World Scientific Publishing Company. This paper presents the ordered weighted average weighted average inflation (OWAWAI) and some extensions using induced and heavy aggregation operators and presents the generalized operators and some of their families. The main advantage of these new formulations is that they can use two different sets of weighting vectors and generate new scenarios based on the reordering of the arguments with the weights. With this idea, it is possible to generate new approaches that under- or overestimate the results according to the knowledge and expertise of the decision-maker. The work presents an application of these new approaches in the analysis of the inflation in Chile, Colombia, and Argentina during 2017.

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http://hdl.handle.net/10453/146336