The state of the art in fuzzy data envelopment analysis

Ali Emrouznejad*, Madjid Tavana, Adel Hatami-Marbini

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)

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. This chapter provides a taxonomy and review of the fuzzy DEA (FDEA) methods. We present a classification scheme with six categories, namely, the tolerance approach, the α-level based approach, the fuzzy ranking approach, the possibility approach, the fuzzy arithmetic, and the fuzzy random/type-2 fuzzy set. We discuss each classification scheme and group the FDEA papers published in the literature over the past 30 years.
Original languageEnglish
Title of host publicationPerformance measurement with fuzzy data envelopment analysis
EditorsAli Emrouznejad, Madjid Tavana
Place of PublicationBerlin (DE)
PublisherSpringer
Pages1-45
Number of pages45
Volume309
ISBN (Electronic)978-3-642-41372-8
ISBN (Print)978-3-642-41371-1
DOIs
Publication statusPublished - 31 Dec 2014

Publication series

NameStudies in fuzziness and soft computing
PublisherSpringer-Verlag
Volume309
ISSN (Print)1434-9922
ISSN (Electronic)1860-0808

Fingerprint

Fuzzy Data
Data envelopment analysis
Data Envelopment Analysis
Output
Fuzzy Arithmetic
Type-2 Fuzzy Sets
Relative Efficiency
Taxonomies
Ambiguous
Fuzzy sets
Taxonomy
Tolerance
Ranking
Decision making
Decision Making
Unit
Methodology

Keywords

  • data envelopment analysis
  • fuzzy sets
  • tolerance approach
  • alpha-level based approach
  • fuzzy ranking approach
  • possibility approach
  • fuzzy arithmetic
  • fuzzy random
  • type-2 fuzzy set

Cite this

Emrouznejad, A., Tavana, M., & Hatami-Marbini, A. (2014). The state of the art in fuzzy data envelopment analysis. In A. Emrouznejad, & M. Tavana (Eds.), Performance measurement with fuzzy data envelopment analysis (Vol. 309, pp. 1-45). (Studies in fuzziness and soft computing; Vol. 309). Berlin (DE): Springer. https://doi.org/10.1007/978-3-642-41372-8-1
Emrouznejad, Ali ; Tavana, Madjid ; Hatami-Marbini, Adel. / The state of the art in fuzzy data envelopment analysis. Performance measurement with fuzzy data envelopment analysis. editor / Ali Emrouznejad ; Madjid Tavana. Vol. 309 Berlin (DE) : Springer, 2014. pp. 1-45 (Studies in fuzziness and soft computing).
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Emrouznejad, A, Tavana, M & Hatami-Marbini, A 2014, The state of the art in fuzzy data envelopment analysis. in A Emrouznejad & M Tavana (eds), Performance measurement with fuzzy data envelopment analysis. vol. 309, Studies in fuzziness and soft computing, vol. 309, Springer, Berlin (DE), pp. 1-45. https://doi.org/10.1007/978-3-642-41372-8-1

The state of the art in fuzzy data envelopment analysis. / Emrouznejad, Ali; Tavana, Madjid; Hatami-Marbini, Adel.

Performance measurement with fuzzy data envelopment analysis. ed. / Ali Emrouznejad; Madjid Tavana. Vol. 309 Berlin (DE) : Springer, 2014. p. 1-45 (Studies in fuzziness and soft computing; Vol. 309).

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)

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KW - fuzzy sets

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Emrouznejad A, Tavana M, Hatami-Marbini A. The state of the art in fuzzy data envelopment analysis. In Emrouznejad A, Tavana M, editors, Performance measurement with fuzzy data envelopment analysis. Vol. 309. Berlin (DE): Springer. 2014. p. 1-45. (Studies in fuzziness and soft computing). https://doi.org/10.1007/978-3-642-41372-8-1