A new dominance intensity method to deal with ordinal information about a DM's preferences within MAVT

Aguayo Garcia, Ernesto Aaron and Mateos Caballero, Alfonso and Jiménez Martín, Antonio (2014). A new dominance intensity method to deal with ordinal information about a DM's preferences within MAVT. "Knowledge-Based Systems", v. null (n. null); pp.. ISSN 0950-7051. https://doi.org/10.1016/j.knosys.2014.05.017.

Description

Title: A new dominance intensity method to deal with ordinal information about a DM's preferences within MAVT
Author/s:
  • Aguayo Garcia, Ernesto Aaron
  • Mateos Caballero, Alfonso
  • Jiménez Martín, Antonio
Item Type: Article
Título de Revista/Publicación: Knowledge-Based Systems
Date: 2014
ISSN: 0950-7051
Volume: null
Subjects:
Faculty: E.T.S. de Ingenieros Informáticos (UPM)
Department: Inteligencia Artificial
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Dominance measuring methods are a new approach to deal with complex decision-making problems with imprecise information. These methods are based on the computation of pairwise dominance values and exploit the information in the dominance matrix in dirent ways to derive measures of dominance intensity and rank the alternatives under consideration. In this paper we propose a new dominance measuring method to deal with ordinal information about decision-maker preferences in both weights and component utilities. It takes advantage of the centroid of the polytope delimited by ordinal information and builds triangular fuzzy numbers whose distances to the crisp value 0 constitute the basis for the de?nition of a dominance intensity measure. Monte Carlo simulation techniques have been used to compare the performance of this method with other existing approaches.

Funding Projects

TypeCodeAcronymLeaderTitle
Madrid Regional GovernmentS-0505/TIC/0230UnspecifiedUnspecifiedUnspecified
Government of SpainTIN2008-06796-C04-02UnspecifiedUnspecifiedUnspecified
Government of SpainMTM2011-28983-C03-03UnspecifiedUnspecifiedUnspecified

More information

Item ID: 29091
DC Identifier: http://oa.upm.es/29091/
OAI Identifier: oai:oa.upm.es:29091
DOI: 10.1016/j.knosys.2014.05.017
Official URL: http://www.journals.elsevier.com/knowledge-based-systems/
Deposited by: Memoria Investigacion
Deposited on: 25 Jul 2014 10:20
Last Modified: 11 Apr 2019 10:09
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