Bonferroni Distances and Their Application in Group Decision Making

Blanco-Mesa, F; Merigó, JM

Bonferroni Distances and Their Application in Group Decision Making

Blanco-Mesa, F Merigó, JM

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Publisher:: TAYLOR & FRANCIS INC
Publication Type:: Journal Article
Citation:: Cybernetics and Systems, 2020, 51, (1), pp. 27-58
Issue Date:: 2020-01-02

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Field	Value	Language
dc.contributor.author	Blanco-Mesa, F
dc.contributor.author	Merigó, JM
dc.date.accessioned	2020-11-07T18:52:18Z
dc.date.available	2020-11-07T18:52:18Z
dc.date.issued	2020-01-02
dc.identifier.citation	Cybernetics and Systems, 2020, 51, (1), pp. 27-58
dc.identifier.issn	0196-9722
dc.identifier.issn	1087-6553
dc.identifier.uri	http://hdl.handle.net/10453/143823
dc.description.abstract	© 2019, © 2019 Taylor & Francis Group, LLC. The aim of the paper is to develop new aggregation operators using Bonferroni means, ordered weighted averaging (OWA) operators and some distance measures. We introduce the Bonferroni-Hamming weighted distance (BON-HWD), Bonferroni OWA distance (BON-OWAD), Bonferroni OWA adequacy coefficient (BON-OWAAC) and Bonferroni distances with OWA operators and weighted averages (BON-IWOWAD). The main advantages of using these operators are that they allow the consideration of different aggregations contexts to be considered and multiple comparison between each argument and distance measures in the same formulation. An application is developed using these new algorithms in combination with Pichat algorithm to solve a group decision-making problem. Creative personality is taken as an example for forming creative groups. The results show fuzzy dissimilarity relations in order to establish the maximum similarity subrelations and find groups according to each individual’s creative personality similarities.
dc.language	English
dc.publisher	TAYLOR & FRANCIS INC
dc.relation.ispartof	Cybernetics and Systems
dc.relation.isbasedon	10.1080/01969722.2019.1660540
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	Bonferroni Distances and Their Application in Group Decision Making
dc.type	Journal Article
utslib.citation.volume	51
utslib.for	0801 Artificial Intelligence and Image Processing
utslib.for	1702 Cognitive Sciences
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	2020-11-07T18:52:11Z
pubs.issue	1
pubs.publication-status	Published
pubs.volume	51
utslib.citation.issue	1

Abstract:

© 2019, © 2019 Taylor & Francis Group, LLC. The aim of the paper is to develop new aggregation operators using Bonferroni means, ordered weighted averaging (OWA) operators and some distance measures. We introduce the Bonferroni-Hamming weighted distance (BON-HWD), Bonferroni OWA distance (BON-OWAD), Bonferroni OWA adequacy coefficient (BON-OWAAC) and Bonferroni distances with OWA operators and weighted averages (BON-IWOWAD). The main advantages of using these operators are that they allow the consideration of different aggregations contexts to be considered and multiple comparison between each argument and distance measures in the same formulation. An application is developed using these new algorithms in combination with Pichat algorithm to solve a group decision-making problem. Creative personality is taken as an example for forming creative groups. The results show fuzzy dissimilarity relations in order to establish the maximum similarity subrelations and find groups according to each individual’s creative personality similarities.

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http://hdl.handle.net/10453/143823