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Solving generalized fuzzy data envelopment analysis model: a parametric approach

Author

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  • Ali Asghar Foroughi

    (University of Qom)

  • Roohollah Abbasi Shureshjani

    (University of Qom)

Abstract

Data envelopment analysis (DEA) is a non-parametric technique to assess the performance of a set of homogeneous decision making units (DMUs) with common crisp inputs and outputs. Regarding the problems that are modelled out of the real world, the data cannot constantly be precise and sometimes they are vague or fluctuating. So in the modelling of such data, one of the best approaches is using the fuzzy numbers. Substituting the fuzzy numbers for the crisp numbers in DEA, the traditional DEA problem transforms into a fuzzy data envelopment analysis (FDEA) problem. Different methods have been suggested to compute the efficiency of DMUs in FDEA models so far but the most of them have limitations such as complexity in calculation, non-contribution of decision maker in decision making process, utilizable for a specific model of FDEA and using specific group of fuzzy numbers. In the present paper, to overcome the mentioned limitations, a new approach is proposed. In this approach, the generalized FDEA problem is transformed into a parametric programming, in which, parameter selection depends on the decision maker’s ideas. Two numerical examples are used to illustrate the approach and to compare it with some other approaches.

Suggested Citation

  • Ali Asghar Foroughi & Roohollah Abbasi Shureshjani, 2017. "Solving generalized fuzzy data envelopment analysis model: a parametric approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(4), pages 889-905, December.
    • Handle: RePEc:spr:cejnor:v:25:y:2017:i:4:d:10.1007_s10100-016-0448-5
    DOI: 10.1007/s10100-016-0448-5
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    Cited by:

    1. Nafiseh Javaherian & Ali Hamzehee & Hossein Sayyadi Tooranloo, 2021. "A compositional approach to two-stage Data Envelopment Analysis in intuitionistic fuzzy environment," Operations Research and Decisions, Wroclaw University of Science Technology, Faculty of Management, vol. 31, pages 21-39.
    2. Josef Jablonský & Ali Emrouznejad & Mehdi Toloo, 2018. "Editorial: Special issue on data envelopment analysis," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(4), pages 809-812, December.
    3. Nafiseh Javaherian & Ali Hamzehee & Hossein Sayyadi Tooranloo, 2021. "A compositional approach to two-stage Data Envelopment Analysis in intuitionistic fuzzy environment," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 31(1), pages 21-39.
    4. Tibor Csendes & Csanád Imreh & József Temesi, 2017. "Editorial," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(4), pages 739-741, December.

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