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Enhanced Russell measure in fuzzy DEA

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  • Meiqiang Wang
  • Yongjun Li

Abstract

The radial measures of classical DEA models (CCR, BCC) are incomplete, they are only separate measures of input and output efficiency and their efficiency index omit the non-zero input and output slacks. Enhanced Russell graph measure (ERM) eliminates these deficiencies. All of the existing fuzzy DEA models are extension of CCR or BCC model, efficiencies of DMUs, ultimately, are solution of CCR or BCC model. Based on ERM model, a fuzzy DEA model is proposed to deal with the efficiency evaluation problem with the given fuzzy input and output data, by using a ranking method based on the comparison of α-cuts. The proposed framework is illustrated through an application to performance assessment of flexible manufacturing system and comparative results are presented. The efficiency measure of the proposed approach is relatively more reasonable than those of fuzzy DEA models based on CCR or BCC model and represents some real-life processes more appropriately.

Suggested Citation

  • Meiqiang Wang & Yongjun Li, 2010. "Enhanced Russell measure in fuzzy DEA," International Journal of Data Analysis Techniques and Strategies, Inderscience Enterprises Ltd, vol. 2(2), pages 140-154.
    • Handle: RePEc:ids:injdan:v:2:y:2010:i:2:p:140-154
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    Cited by:

    1. K. Smimou, 2013. "On the significance testing of fuzzy regression applied to the CAPM: Canadian commodity futures evidence," International Journal of Applied Management Science, Inderscience Enterprises Ltd, vol. 5(2), pages 144-171.

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