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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Ayandegan Institute of Higher Education,
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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 |
_version_ |
1717779920830070784 |