A novel best worst method robust data envelopment analysis: Incorporating decision makers’ preferences in an uncertain environment

Hashem Omrani, Mahsa Valipour, Ali Emrouznejad

Research output: Contribution to journalArticlepeer-review

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.
Original languageEnglish
Article number100184
JournalOperations Research Perspectives
Volume8
Early online date15 Apr 2021
DOIs
Publication statusPublished - 2021

Bibliographical note

© 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license.

Keywords

  • Airline Efficiency
  • Best Worst Method (BWM)
  • Data Envelopment Analysis (DEA)
  • Robust Optimization

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