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

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

0.00 Avg rating0 Votes
Article ID: iaor20117313
Volume: 214
Issue: 3
Start Page Number: 457
End Page Number: 472
Publication Date: Nov 2011
Journal: European Journal of Operational Research
Authors: , ,
Keywords: fuzzy sets
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 a‐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.

Reviews

Required fields are marked *. Your email address will not be published.