Data Envelopment Analysis with Fuzzy Parameters: An Interactive Approach

Adel Hatami-Marbini, Saber Saati and Madjid Tavana
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Adel Hatami-Marbini: Universite Catholique de Louvain, Belgium
Saber Saati: Islamic Azad University, Iran
Madjid Tavana: La Salle University, USA

International Journal of Operations Research and Information Systems (IJORIS), 2011, vol. 2, issue 3, 39-53

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. In the conventional DEA, all the data assume the form of specific numerical values. However, the observed values of the input and output data in real-life problems are sometimes imprecise or vague. Previous methods have not considered the preferences of the decision makers (DMs) in the evaluation process. This paper proposes an interactive evaluation process for measuring the relative efficiencies of a set of DMUs in fuzzy DEA with consideration of the DMs’ preferences. The authors construct a linear programming (LP) model with fuzzy parameters and calculate the fuzzy efficiency of the DMUs for different a levels. Then, the DM identifies his or her most preferred fuzzy goal for each DMU under consideration. A modified Yager index is used to develop a ranking order of the DMUs. This study allows the DMs to use their preferences or value judgments when evaluating the performance of the DMUs.

Date: 2011
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