Ranking efficient DMUs using the Tchebycheff norm with fuzzy data in DEA

In many real applications, the data of production processes cannot be precisely measured. Hence the input and output of Decision Making Units (DMUs) in Data Envelopment Analysis (DEA) may be imprecise or fuzzy-numbered. In original DEA models, inputs and outputs are measured by exact values on a rat...

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Main Authors: S. H. Mirzaei, A. Salehi
Format: Article
Language:English
Published: Ayandegan Institute of Higher Education, 2019-06-01
Series:International Journal of Research in Industrial Engineering
Subjects:
Online Access:http://www.riejournal.com/article_88475_9188efbe5ce5fb746a8b859816eeef1b.pdf
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spelling doaj-3c5601858b1a409cb0a04b1346f52e072021-09-06T05:50:51ZengAyandegan Institute of Higher Education,International Journal of Research in Industrial Engineering2783-13372717-29372019-06-018215817510.22105/riej.2019.169577.107288475Ranking efficient DMUs using the Tchebycheff norm with fuzzy data in DEAS. H. Mirzaei0A. Salehi1Department of Mathematics, Islamic Azad University, Arak Branch, Arak, Iran.Department of Mathematics, Islamic Azad University, Science and Research, Tehran Branch, Tehran, Iran.In many real applications, the data of production processes cannot be precisely measured. Hence the input and output of Decision Making Units (DMUs) in Data Envelopment Analysis (DEA) may be imprecise or fuzzy-numbered. In original DEA models, inputs and outputs are measured by exact values on a ratio scale, therefore conventional DEA can't easily measure the performance of DMUs and rank them. The researchers have introduced mane deferent model for ranking DMUs by fuzzy number. In this paper, we proposed a new method by using the Tchebycheff norm for ranking DMUs with fuzzy data. We explain our method by numerical example with the triangular fuzzy number.http://www.riejournal.com/article_88475_9188efbe5ce5fb746a8b859816eeef1b.pdfdata envelopment analysisrankingtchebycheff normfuzzy system
collection DOAJ
language English
format Article
sources DOAJ
author S. H. Mirzaei
A. Salehi
spellingShingle S. H. Mirzaei
A. Salehi
Ranking efficient DMUs using the Tchebycheff norm with fuzzy data in DEA
International Journal of Research in Industrial Engineering
data envelopment analysis
ranking
tchebycheff norm
fuzzy system
author_facet S. H. Mirzaei
A. Salehi
author_sort S. H. Mirzaei
title Ranking efficient DMUs using the Tchebycheff norm with fuzzy data in DEA
title_short Ranking efficient DMUs using the Tchebycheff norm with fuzzy data in DEA
title_full Ranking efficient DMUs using the Tchebycheff norm with fuzzy data in DEA
title_fullStr Ranking efficient DMUs using the Tchebycheff norm with fuzzy data in DEA
title_full_unstemmed Ranking efficient DMUs using the Tchebycheff norm with fuzzy data in DEA
title_sort ranking efficient dmus using the tchebycheff norm with fuzzy data in dea
publisher Ayandegan Institute of Higher Education,
series International Journal of Research in Industrial Engineering
issn 2783-1337
2717-2937
publishDate 2019-06-01
description In many real applications, the data of production processes cannot be precisely measured. Hence the input and output of Decision Making Units (DMUs) in Data Envelopment Analysis (DEA) may be imprecise or fuzzy-numbered. In original DEA models, inputs and outputs are measured by exact values on a ratio scale, therefore conventional DEA can't easily measure the performance of DMUs and rank them. The researchers have introduced mane deferent model for ranking DMUs by fuzzy number. In this paper, we proposed a new method by using the Tchebycheff norm for ranking DMUs with fuzzy data. We explain our method by numerical example with the triangular fuzzy number.
topic data envelopment analysis
ranking
tchebycheff norm
fuzzy system
url http://www.riejournal.com/article_88475_9188efbe5ce5fb746a8b859816eeef1b.pdf
work_keys_str_mv AT shmirzaei rankingefficientdmususingthetchebycheffnormwithfuzzydataindea
AT asalehi rankingefficientdmususingthetchebycheffnormwithfuzzydataindea
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