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A Full Ranking for Decision Making Units Using Ideal and Anti-Ideal Points in DEA

We propose a procedure for ranking decision making units in data envelopment analysis, based on ideal and anti-ideal points in the production possibility set. Moreover, a model has been introduced to compute the performance of a decision making unit for these two points through using common set of w...

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Autores principales: Barzegarinegad, A., Jahanshahloo, G., Rostamy-Malkhalifeh, M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4134803/
https://www.ncbi.nlm.nih.gov/pubmed/25147844
http://dx.doi.org/10.1155/2014/282939
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author Barzegarinegad, A.
Jahanshahloo, G.
Rostamy-Malkhalifeh, M.
author_facet Barzegarinegad, A.
Jahanshahloo, G.
Rostamy-Malkhalifeh, M.
author_sort Barzegarinegad, A.
collection PubMed
description We propose a procedure for ranking decision making units in data envelopment analysis, based on ideal and anti-ideal points in the production possibility set. Moreover, a model has been introduced to compute the performance of a decision making unit for these two points through using common set of weights. One of the best privileges of this method is that we can make ranking for all decision making units by solving only three programs, and also solving these programs is not related to numbers of decision making units. One of the other advantages of this procedure is to rank all the extreme and nonextreme efficient decision making units. In other words, the suggested ranking method tends to seek a set of common weights for all units to make them fully ranked. Finally, it was applied for different sets holding real data, and then it can be compared with other procedures.
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spelling pubmed-41348032014-08-21 A Full Ranking for Decision Making Units Using Ideal and Anti-Ideal Points in DEA Barzegarinegad, A. Jahanshahloo, G. Rostamy-Malkhalifeh, M. ScientificWorldJournal Research Article We propose a procedure for ranking decision making units in data envelopment analysis, based on ideal and anti-ideal points in the production possibility set. Moreover, a model has been introduced to compute the performance of a decision making unit for these two points through using common set of weights. One of the best privileges of this method is that we can make ranking for all decision making units by solving only three programs, and also solving these programs is not related to numbers of decision making units. One of the other advantages of this procedure is to rank all the extreme and nonextreme efficient decision making units. In other words, the suggested ranking method tends to seek a set of common weights for all units to make them fully ranked. Finally, it was applied for different sets holding real data, and then it can be compared with other procedures. Hindawi Publishing Corporation 2014 2014-07-24 /pmc/articles/PMC4134803/ /pubmed/25147844 http://dx.doi.org/10.1155/2014/282939 Text en Copyright © 2014 A. Barzegarinegad et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Barzegarinegad, A.
Jahanshahloo, G.
Rostamy-Malkhalifeh, M.
A Full Ranking for Decision Making Units Using Ideal and Anti-Ideal Points in DEA
title A Full Ranking for Decision Making Units Using Ideal and Anti-Ideal Points in DEA
title_full A Full Ranking for Decision Making Units Using Ideal and Anti-Ideal Points in DEA
title_fullStr A Full Ranking for Decision Making Units Using Ideal and Anti-Ideal Points in DEA
title_full_unstemmed A Full Ranking for Decision Making Units Using Ideal and Anti-Ideal Points in DEA
title_short A Full Ranking for Decision Making Units Using Ideal and Anti-Ideal Points in DEA
title_sort full ranking for decision making units using ideal and anti-ideal points in dea
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4134803/
https://www.ncbi.nlm.nih.gov/pubmed/25147844
http://dx.doi.org/10.1155/2014/282939
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