Title

A taxonomy and review of the fuzzy data envelopment analysis literature: Two decades in the making

Document Type

Article

Publication Date

2-8-2011

DOI

https://doi.org/10.1016/j.ejor.2011.02.001

Abstract

Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. Crisp input and output data are fundamentally indispensable in conventional DEA. However, the observed values of the input and output data in real-world problems are sometimes imprecise or vague. Many researchers have proposed various fuzzy methods for dealing with the imprecise and ambiguous data in DEA. In this study, we provide a taxonomy and review of the fuzzy DEA methods. We present a classification scheme with four primary categories, namely, the tolerance approach, the α-level based approach, the fuzzy ranking approach and the possibility approach. We discuss each classification scheme and group the fuzzy DEA papers published in the literature over the past 20 years. To the best of our knowledge, this paper appears to be the only review and complete source of references on fuzzy DEA.

Language

English

Comments

Hatami-Marbini, A., Emrouznejad, A. and Tavana, M. (2011) ‘A Taxonomy and Review of the Fuzzy Data Envelopment Analysis Literature: Two Decades in the Making,’ European Journal of Operational Research, Vol. 214, No. 3, pp. 457–472.

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