Efficiency measurement in fuzzy additive data envelopment analysis

Adel Hatami-Marbini, Madjid Tavana, Ali Emrouznejad, Saber Saati

Research output: Contribution to journalArticlepeer-review


Performance evaluation in conventional data envelopment analysis (DEA) requires crisp numerical values. However, the observed values of the input and output data in real-world problems are often imprecise or vague. These imprecise and vague data can be represented by linguistic terms characterised by fuzzy numbers in DEA to reflect the decision-makers' intuition and subjective judgements. This paper extends the conventional DEA models to a fuzzy framework by proposing a new fuzzy additive DEA model for evaluating the efficiency of a set of decision-making units (DMUs) with fuzzy inputs and outputs. The contribution of this paper is threefold: (1) we consider ambiguous, uncertain and imprecise input and output data in DEA, (2) we propose a new fuzzy additive DEA model derived from the a-level approach and (3) we demonstrate the practical aspects of our model with two numerical examples and show its comparability with five different fuzzy DEA methods in the literature. Copyright © 2011 Inderscience Enterprises Ltd.
Original languageEnglish
Pages (from-to)1-20
Number of pages20
JournalInternational Journal of Industrial Systems Engineering
Issue number1
Publication statusPublished - 2012


  • DEA
  • data envelopment analysis
  • fuzzy sets theory
  • DMUs
  • decision-making units
  • fuzzy additive model


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