Omrani, Hashem, Valipour, Mahsa and Emrouznejad, Ali (2021). A novel best worst method robust data envelopment analysis:Incorporating decision makers’ preferences in an uncertain environment. Operations Research Perspectives, 8 ,
Abstract
Data Envelopment Analysis (DEA) has been widely applied in measuring the efficiency of Decision-Making Units (DMUs). The conventional DEA has three major drawbacks: a) it does not consider Decision Makers’ (DMs) preferences in the evaluation process, b) DMUs in this model are flexible in weighting the criteria to reach the maximum possible efficiency, and c) it ignores the uncertainty in data. However, in many real-world applications, data are uncertain as well as imprecise and managers want to impose their opinions in decision-making procedure. To address these problems, this paper develops a novel multi-objective Best Worst Method (BWM)-Robust DEA (RDEA) for incorporating DMs’ preferences into DEA model in an uncertain environment. The proposed model tries to provide a new efficiency score which is more reliable and compatible with real problems by taking the advantages of the BWM to apply experts’ opinions and RDEA to model the uncertainty This bi-objective BWM-RDEA model is solved utilizing amin-max technique and so as to illustrate its usefulness, this model is implemented for assessing Iranian airlines.
Publication DOI: | https://doi.org/10.1016/j.orp.2021.100184 |
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Divisions: | College of Business and Social Sciences > Aston Business School > Operations & Information Management College of Business and Social Sciences > Aston Business School |
Additional Information: | © 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license. |
Uncontrolled Keywords: | Airline Efficiency,Best Worst Method (BWM),Data Envelopment Analysis (DEA),Robust Optimization,Statistics and Probability,Strategy and Management,Management Science and Operations Research,Control and Optimization |
Publication ISSN: | 2214-7160 |
Last Modified: | 16 Aug 2024 07:11 |
Date Deposited: | 28 May 2021 12:02 |
Full Text Link: | |
Related URLs: |
https://www.sci ... 0075?via%3Dihub
(Publisher URL) http://www.scop ... tnerID=8YFLogxK (Scopus URL) |
PURE Output Type: | Article |
Published Date: | 2021 |
Published Online Date: | 2021-04-15 |
Accepted Date: | 2021-03-30 |
Authors: |
Omrani, Hashem
Valipour, Mahsa Emrouznejad, Ali ( ![]() |
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