AHP-Like Matrices and Structures—Absolute and Relative Preferences

David Koloseni, Tove Helldin and Vicenç Torra
Additional contact information
David Koloseni: Department of Mathematics, University of Dar es Salaam, Dar es Salaam 35065, Tanzania
Tove Helldin: School of Informatics, University of Skövde, 54128 Skövde, Sweden
Vicenç Torra: School of Informatics, University of Skövde, 54128 Skövde, Sweden

Mathematics, 2020, vol. 8, issue 5, 1-12

Abstract: Aggregation functions are extensively used in decision making processes to combine available information. Arithmetic mean and weighted mean are some of the most used ones. In order to use a weighted mean, we need to define its weights. The Analytical Hierarchy Process (AHP) is a well known technique used to obtain weights based on interviews with experts. From the interviews we define a matrix of pairwise comparisons of the importance of the weights. We call these AHP-like matrices absolute preferences of weights. We propose another type of matrix that we call a relative preference matrix. We define this matrix with the same goal—to find the weights for weighted aggregators. We discuss how it can be used for eliciting the weights for the weighted mean and define a similar approach for the Choquet integral.

Keywords: aggregation functions; weight selection; fuzzy measures; AHP (Analytical Hierarchy Process) (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/8/5/813/pdf (application/pdf)
https://www.mdpi.com/2227-7390/8/5/813/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:8:y:2020:i:5:p:813-:d:359407

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().