Decision Making Based on Fuzzy Data Envelopment Analysis

  • Peijun Guo
  • Hideo Tanaka
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 117)

DEA (data envelopment analysis) is a non-parametric technique for measuring and evaluating the relative efficiencies of a set of entities with common crisp inputs and outputs. In fact, in a real evaluation problem input and output data of entities evaluated often fluctuate. These fluctuating data can be represented as linguistic variables characterized by fuzzy numbers for reflecting a kind of general feeling or experience of experts. Based on the fundamental CCR model, a fuzzy DEA model is proposed to deal with the efficiency evaluation problem with the given fuzzy input and output data. Furthermore, a fuzzy aggregation model for integrating multiple attribute fuzzy values of objects is proposed based on the fuzzy DEA model. Using the proposed fuzzy DEA models, the crisp efficiency in CCR model is generalized to be a fuzzy efficiency to reflect the inherent uncertainty in real evaluation problems. Using the proposed fuzzy aggregation models, the objects can be ranked objectively.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Peijun Guo
    • 1
  • Hideo Tanaka
    • 2
  1. 1.Faculty of Business AdministrationYokohama National UniversityYokohamaJapan
  2. 2.Faculty of Psychological ScienceHiroshima International UniversityHigashi-HiroshimaJapan

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