Result: A new approach for multiobjective decision making based on fuzzy distance minimization

Title:
A new approach for multiobjective decision making based on fuzzy distance minimization
Authors:
BILBAO TEROL, Amelia
Source:
Mathematical and computer modelling. 47(9-10):808-826
Publisher Information:
Oxford: Elsevier Science, 2008.
Publication Year:
2008
Physical Description:
print, 27 ref
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Mathematics, Mathématiques, Sciences exactes et technologie, Exact sciences and technology, Sciences et techniques communes, Sciences and techniques of general use, Mathematiques, Mathematics, Combinatoire. Structures ordonnées, Combinatorics. Ordered structures, Combinatoire, Combinatorics, Plans d'expériences et configurations, Designs and configurations, Analyse mathématique, Mathematical analysis, Calcul des variations et contrôle optimal, Calculus of variations and optimal control, Analyse numérique. Calcul scientifique, Numerical analysis. Scientific computation, Analyse numérique, Numerical analysis, Méthodes numériques en programmation mathématique, optimisation et calcul variationnel, Numerical methods in mathematical programming, optimization and calculus of variations, Méthodes de calcul scientifique (y compris calcul symbolique, calcul algébrique), Methods of scientific computing (including symbolic computation, algebraic computation), Analyse assistée, Computer aided analysis, Análisis asistido, Analyse numérique, Numerical analysis, Análisis numérico, Calcul scientifique, Scientific computation, Computación científica, Mathématiques appliquées, Applied mathematics, Matemáticas aplicadas, Minimisation fonction, Function minimization, Minimización función, Modèle mathématique, Mathematical model, Modelo matemático, Méthode numérique, Numerical method, Método numérico, Méthode optimisation, Optimization method, Método optimización, Prise de décision, Decision making, Toma decision, Programmation linéaire, Linear programming, Programación lineal, Programmation mathématique, Mathematical programming, Programación matemática, Programmation multiobjectif, Multiobjective programming, Programación multiobjetivo, Résolution problème, Problem solving, Resolución problema, 05Bxx, 49XX, 65Kxx, Ambiguity and fuzziness, Compromise programming, Distance minimization, Fuzzy multiobjective programming, Fuzzy number, Goal programming, Value
Document Type:
Academic journal Article
File Description:
text
Language:
English
Author Affiliations:
Department of Quantitative Economics, University of Oviedo, Spain
ISSN:
0895-7177
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=20267877
Rights:
Copyright 2008 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Mathematics
Accession Number:
edscal.20267877
Database:
PASCAL Archive

Further Information

The aim of this paper is to design flexible decision making models in the distance metric optimization framework for problems including parameters which are represented by fuzzy numbers. Multi-criteria decision making methodologies based on distance functions involve the minimization of some form of distance from a desired point (ideal or specified by a decision marker). If it is assumed that the parameters of problem are fuzzy numbers, then it is natural to expect that this point also is so. Thus, in this paper it is supposed that the desired point is a vector of fuzzy numbers obtained from the imprecise information provided by the decision marker or, alternatively, composed by the individual optimum of each objective under consideration. The methodological proposal is an extension of the distance-based models and relies in the first instance, on the constructing of a fuzzy minimum distance obtained by solving linear programming problems. Secondly, it is shown that this fuzzy minimum distance possesses suitable features with respect to the quality and handling of information such that it can be incorporated in distance-based ordinary models which are necessary in order to determine an optimum decision. To illustrate the suitability of the method, a numerical example has been included.