Issue |
RAIRO-Oper. Res.
Volume 55, Number 4, July-August 2021
|
|
---|---|---|
Page(s) | 2189 - 2202 | |
DOI | https://doi.org/10.1051/ro/2021097 | |
Published online | 14 July 2021 |
A novel fuzzy non-radial data envelopment analysis: An application in transportation
Birla Institute of Technology and Science, Pilani, India
* Corresponding author: p20170024@pilani.bits-pilani.ac.in, deepakmahlabits@gmail.com
Received:
13
March
2021
Accepted:
25
June
2021
The slack-based measure (SBM) DEA model is a non-radial model used to calculate the relative efficiency, input, and output targets of the different decision-making units (DMUs) based on their best peers or efficient frontier. The conventional SBM DEA model used crisp inputs and outputs. But, it can be observed in real-life problems that sometimes the available data is in linguistic forms such as “few”, “many”, “small”, or missing data. The DEA technique is frontier based, and therefore, imprecise data may lead to untenable results. Fuzzy theory, which is already established to handle uncertain data, can overcome this problem. Furthermore, the sensitivity and stability analysis have been checked the robustness of fuzzy DEA models. In this study, sensitivity and stability analysis of the fuzzy SBM DEA has been performed. The lower and upper sensitive bounds for inputs and outputs variables have been obtained for both the inefficient and efficient DMUs to calculate the input and output targets. Finally, a real-life transportation problem for the validity of the study is presented for its depiction.
Mathematics Subject Classification: 03B52 / 90C08 / 90C31 / 90C70 / 03E72
Key words: Data Envelopment Analysis / fuzzy slacks-based measure model / credibility measure / decision-making units / sensitivity analysis
© The authors. Published by EDP Sciences, ROADEF, SMAI 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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