Modeling Fuzzy DEA with Type-2 Fuzzy Variable Coefficients

  • Authors:

  • Rui Qin;Yankui Liu;Zhiqiang Liu;Guoli Wang

  • Affiliations:

  • College of Mathematics & Computer Science, Hebei University Baoding, Hebei, China 071002;College of Mathematics & Computer Science, Hebei University Baoding, Hebei, China 071002;School of Creative Media, City University of Hong Kong, Hong Kong, China;College of Mathematics & Computer Science, Hebei University Baoding, Hebei, China 071002

  • Venue:
  • ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
  • Year:
  • 2009

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Abstract

Data envelopment analysis (DEA) is an effective method for measuring the relative efficiency of a set of homogeneous decision-making units (DMUs). However, the data in traditional DEA model are limited to crisp inputs and outputs, which cannot be precisely obtained in many production processes or social activities. This paper attempts to extend the traditional DEA model and establishes a DEA model with type-2 (T2) fuzzy inputs and outputs. To establish this model, we first propose a reduction method for T2 fuzzy variables based on the expected value of fuzzy variable. After that, we establish a DEA model with the obtained fuzzy variables. In some special cases such as the inputs and outputs are independent T2 triangular fuzzy variables, we provide a method to turn the original DEA model to its equivalent one. At last, we provide a numerical example to illustrate the efficiency of the proposed DEA model.