Bonferroni Weighted Logarithmic Averaging Distance Operator Applied to Investment Selection Decision Making

Alfaro‐garcía, VG; Blanco‐mesa, F; León‐castro, E; Merigo, JM

Bonferroni Weighted Logarithmic Averaging Distance Operator Applied to Investment Selection Decision Making

Alfaro‐garcía, VG Blanco‐mesa, F León‐castro, E Merigo, JM

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Publisher:: MDPI
Publication Type:: Journal Article
Citation:: Mathematics, 2022, 10, (12)
Issue Date:: 2022-06-01

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Field	Value	Language
dc.contributor.author	Alfaro‐garcía, VG
dc.contributor.author	Blanco‐mesa, F
dc.contributor.author	León‐castro, E
dc.contributor.author	Merigo, JM
dc.date.accessioned	2023-03-20T21:45:35Z
dc.date.available	2023-03-20T21:45:35Z
dc.date.issued	2022-06-01
dc.identifier.citation	Mathematics, 2022, 10, (12)
dc.identifier.issn	2227-7390
dc.identifier.issn	2227-7390
dc.identifier.uri	http://hdl.handle.net/10453/167797
dc.description.abstract	Distance measures in ordered weighted averaging (OWA) operators allow the modelling of complex decision making problems where a set of ideal values or characteristics are required to be met. The objective of this paper is to introduce extended distance measures and logarithmic OWA‐based decision making operators especially designed for the analysis of financial investment options. Based on the immediate weights, Bonferroni means and logarithmic averaging operators, in this paper we introduce the immediate weights logarithmic distance (IWLD), the immediate weights ordered weighted logarithmic averaging distance (IWOWLAD), the hybrid weighted logarithmic distance (HWLD), the Bonferroni ordered weighted logarithmic averaging distance (B‐ OWLAD) operator, the Bonferroni immediate weights ordered weighted logarithmic averaging distance (B‐IWOWLAD) operator and the Bonferroni hybrid weighted logarithmic distance (HWLD). A financial decision making illustrative example is proposed, and the main benefits of the characteristic design of the introduced operators is shown, which include the analysis of the interrelation between the modelled arguments required from the decision makers and the stakeholders, and the comparison to an ideal set of characteristics that the possible companies in the example must portray. Moreover, some families, particular cases and brief examples of the proposed operators, are studied and presented. Finally, among the main advantages are the modeling of diverse perspectives, attitudinal characteristics and complex scenarios, through the interrelation and comparison between the elements with an ideal set of characteristics given by the decision makers and a set of options.
dc.language	English
dc.publisher	MDPI
dc.relation.ispartof	Mathematics
dc.relation.isbasedon	10.3390/math10122100
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Bonferroni Weighted Logarithmic Averaging Distance Operator Applied to Investment Selection Decision Making
dc.type	Journal Article
utslib.citation.volume	10
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	open_access	*
dc.date.updated	2023-03-20T21:45:33Z
pubs.issue	12
pubs.publication-status	Published
pubs.volume	10
utslib.citation.issue	12

Abstract:

Distance measures in ordered weighted averaging (OWA) operators allow the modelling of complex decision making problems where a set of ideal values or characteristics are required to be met. The objective of this paper is to introduce extended distance measures and logarithmic OWA‐based decision making operators especially designed for the analysis of financial investment options. Based on the immediate weights, Bonferroni means and logarithmic averaging operators, in this paper we introduce the immediate weights logarithmic distance (IWLD), the immediate weights ordered weighted logarithmic averaging distance (IWOWLAD), the hybrid weighted logarithmic distance (HWLD), the Bonferroni ordered weighted logarithmic averaging distance (B‐ OWLAD) operator, the Bonferroni immediate weights ordered weighted logarithmic averaging distance (B‐IWOWLAD) operator and the Bonferroni hybrid weighted logarithmic distance (HWLD). A financial decision making illustrative example is proposed, and the main benefits of the characteristic design of the introduced operators is shown, which include the analysis of the interrelation between the modelled arguments required from the decision makers and the stakeholders, and the comparison to an ideal set of characteristics that the possible companies in the example must portray. Moreover, some families, particular cases and brief examples of the proposed operators, are studied and presented. Finally, among the main advantages are the modeling of diverse perspectives, attitudinal characteristics and complex scenarios, through the interrelation and comparison between the elements with an ideal set of characteristics given by the decision makers and a set of options.

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http://hdl.handle.net/10453/167797