Fuzzy Data Envelopment Analysis: An Adjustable Approach

P. Peykani, E. Mohammadi, Ali Emrouznejad, M.S. Pishvaee, M. Rostamy-Malkhalifeh

Research output: Contribution to journalArticlepeer-review


Possibilistic Data Envelopment Analysis (PDEA) is one of the most applicable and popular approaches in the literature to deal with imprecise and ambiguous data in DEA models. In this approach, with respect to tendency of decision maker (DM) in taking optimistic, pessimistic and compromise attitude, three measures including possibility, necessity and credibility measures are used to form the Fuzzy DEA (FDEA) models, respectively. However, decision makers may have different preference and so it is necessary to customize fuzzy DEA models according to properties of DMUs. This paper proposes a novel fuzzy DEA model based on general fuzzy measure in which the attitude of DMUs could be determined by the optimistic-pessimistic parameters. As a result, the proposed FDEA model is general, applicable, flexible, and adjustable based on each DMUs. A numerical example is used to explain the proposed approach while usefulness and applicability of this approach have been illustrated using a real data set to measure efficiency of 38 hospital in United States.
Original languageEnglish
Pages (from-to)439-452
Number of pages14
JournalExpert Systems with Applications
Early online date19 Jun 2019
Publication statusPublished - 1 Dec 2019

Bibliographical note

© 2019, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/


  • Fuzzy data envelopment analysis
  • General fuzzy measure
  • Hospital efficiency
  • Possibility theory
  • Uncertainty


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