Multicriteria analysis with unknown preferences: an application of the smaa-2 method

Applications of Multicriteria Decision Aiding are normally dependent on the preferences concerning alternatives for each criterion. They also depend on the measurements of the importance of criteria. Over the last decade, as a response to the fact that such preferences or measurements are often eith...

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Autores principales: Monteiro Gomes, Luis Flavio Autran, Sant’anna, Annibal Parracho, Duncan Rangel, Luís Alberto
Formato: Artículo revista
Lenguaje:Inglés
Publicado: Escuela de Perfeccionamiento en Investigación Operativa 2018
Materias:
multicriteria decision aid
stochastic preferences
modelling of uncertainty - Monte Carlo simulation
Acceso en línea:https://revistas.unc.edu.ar/index.php/epio/article/view/20302
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Revista de la Escuela de Perfeccionamiento en Investigación Operativa de Universidad Nacional de Córdoba
id I10-R359-article-20302
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spelling I10-R359-article-203022018-06-14T15:43:22Z Multicriteria analysis with unknown preferences: an application of the smaa-2 method Monteiro Gomes, Luis Flavio Autran Sant’anna, Annibal Parracho Duncan Rangel, Luís Alberto multicriteria decision aid stochastic preferences modelling of uncertainty - Monte Carlo simulation Applications of Multicriteria Decision Aiding are normally dependent on the preferences concerning alternatives for each criterion. They also depend on the measurements of the importance of criteria. Over the last decade, as a response to the fact that such preferences or measurements are often either not available or highly uncertain, Finnish researchers have developed a family of analytical methods called SMAA. Methods belonging to this family include SMAA-1, SMAA-D, SMAA-O, SMAA-2, SMAA-3, SMAA-A, SMAA-TRI, Ref-SMAA and SMAA-P. They consist, in essence, of formulating inverse problems in the weight space. These problems allow for the solving of multidimensional integrals and can be approached by the Monte Carlo simulation. In this article, the principal concepts of SMAA methods are presented. An example application to real data of one of the most important among these methods, the SMAA-2 method, is developed to demonstrate the main features of this approach. The article closes by addressing the appropriateness of using SMAA methods when the above-mentioned limitations prevail. Escuela de Perfeccionamiento en Investigación Operativa 2018-06-14 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://revistas.unc.edu.ar/index.php/epio/article/view/20302 Revista de la Escuela de Perfeccionamiento en Investigación Operativa; Vol. 21 Núm. 34 (2013): Noviembre; 30-44 1853-9777 0329-7322 eng https://revistas.unc.edu.ar/index.php/epio/article/view/20302/19948
institution Universidad Nacional de Córdoba
institution_str I-10
repository_str R-359
container_title_str Revista de la Escuela de Perfeccionamiento en Investigación Operativa
language Inglés
format Artículo revista
topic multicriteria decision aid
stochastic preferences
modelling of uncertainty - Monte Carlo simulation
spellingShingle multicriteria decision aid
stochastic preferences
modelling of uncertainty - Monte Carlo simulation
Monteiro Gomes, Luis Flavio Autran
Sant’anna, Annibal Parracho
Duncan Rangel, Luís Alberto
Multicriteria analysis with unknown preferences: an application of the smaa-2 method
topic_facet multicriteria decision aid
stochastic preferences
modelling of uncertainty - Monte Carlo simulation
author Monteiro Gomes, Luis Flavio Autran
Sant’anna, Annibal Parracho
Duncan Rangel, Luís Alberto
author_facet Monteiro Gomes, Luis Flavio Autran
Sant’anna, Annibal Parracho
Duncan Rangel, Luís Alberto
author_sort Monteiro Gomes, Luis Flavio Autran
title Multicriteria analysis with unknown preferences: an application of the smaa-2 method
title_short Multicriteria analysis with unknown preferences: an application of the smaa-2 method
title_full Multicriteria analysis with unknown preferences: an application of the smaa-2 method
title_fullStr Multicriteria analysis with unknown preferences: an application of the smaa-2 method
title_full_unstemmed Multicriteria analysis with unknown preferences: an application of the smaa-2 method
title_sort multicriteria analysis with unknown preferences: an application of the smaa-2 method
description Applications of Multicriteria Decision Aiding are normally dependent on the preferences concerning alternatives for each criterion. They also depend on the measurements of the importance of criteria. Over the last decade, as a response to the fact that such preferences or measurements are often either not available or highly uncertain, Finnish researchers have developed a family of analytical methods called SMAA. Methods belonging to this family include SMAA-1, SMAA-D, SMAA-O, SMAA-2, SMAA-3, SMAA-A, SMAA-TRI, Ref-SMAA and SMAA-P. They consist, in essence, of formulating inverse problems in the weight space. These problems allow for the solving of multidimensional integrals and can be approached by the Monte Carlo simulation. In this article, the principal concepts of SMAA methods are presented. An example application to real data of one of the most important among these methods, the SMAA-2 method, is developed to demonstrate the main features of this approach. The article closes by addressing the appropriateness of using SMAA methods when the above-mentioned limitations prevail.
publisher Escuela de Perfeccionamiento en Investigación Operativa
publishDate 2018
url https://revistas.unc.edu.ar/index.php/epio/article/view/20302
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AT santannaannibalparracho multicriteriaanalysiswithunknownpreferencesanapplicationofthesmaa2method
AT duncanrangelluisalberto multicriteriaanalysiswithunknownpreferencesanapplicationofthesmaa2method
first_indexed 2024-09-03T22:23:14Z
last_indexed 2024-09-03T22:23:14Z
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