Data Envelopment Analysis with Fuzzy Parameters: An Interactive Approach

Adel Hatami-Marbini, Saber Saati, Madjid Tavana

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

4 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationOptimizing, Innovating, and Capitalizing on Information Systems for Operations
EditorsJohn Wang
PublisherIGI Global
Number of pages15
ISBN (Electronic)9781466629264
ISBN (Print)1466629258, 9781466629257
Publication statusPublished - 28 Feb 2013
Externally publishedYes


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