Efficiency measurement in fuzzy additive data envelopment analysis

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 D-level 2 A. Hatami-Marbini et al. 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. (2012) 'Efficiency measurement in fuzzy additive data envelopment analysis', Int. Louvain (UCL) in Belgium. He received his MSc and BSc in Industrial Engineering from Islamic Azad University in Iran. His research interests are in operations research, data envelopment analysis, multicriteria decision-making and fuzzy sets theory. Ali Emrouznejad is a Senior Lecturer in Operations and Information Management Group at the Aston Business School in Birmingham, UK. His area of research interests include performance measurement and management, efficiency and productivity analysis and data mining. He serves on the Editorial Board of several scientific journals.