Bonferroni weighted logarithmic averaging distance operator applied to investment selection decision making
Date
2022Author
Alfaro Garcia, Victor
Blanco Mesa, Fabio
León Castro, Ernesto
Merigo, Jose
Publisher
MathematicsDescription
Artículo de publicación SCOPUS - WOSMetadata
Show full item recordAbstract
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.