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A new Data Envelopment Analysis under uncertain environment with respect to fuzziness and an estimation of reliability

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Abstract

Data envelopment analysis (DEA) is an effective technique for measuring the efficiency of decision-making units (DMUs) with several inputs and various outputs. Traditional DEA requires crisp data. However, the data in real applications are often imprecise. In order to dominate this restriction, the fuzzy sets may be utilized with the classical DEA to permit expert to integrate ambiguous data into the model. However, fuzzy sets encounter the limitation of not considering the estimation of reliability of information. In view of this, Z-number has been extended to model fuzzy numbers with a degree of confidence. In this paper, we introduce a new DEA (abbreviated as Z-DEA) for working out CCR in which the input and/or output are Z-number variables. We do this task by converting the Z-DEA to classical fuzzy model on the base of a fuzzy expectation of the fuzzy sets. In our study, the expert utilizes the linguistic terms for expressing judgment and an estimation of reliability. To the best of our knowledge, compared with the traditional DEA frameworks, The DEA with Z-data can more practically handle real-world problems.

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Authors and Affiliations

  1. Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

    Soheil Sadi-Nezhad & Alireza Sotoudeh-Anvari

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  1. Soheil Sadi-Nezhad
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  2. Alireza Sotoudeh-Anvari
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Correspondence to Alireza Sotoudeh-Anvari.

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Sadi-Nezhad, S., Sotoudeh-Anvari, A. A new Data Envelopment Analysis under uncertain environment with respect to fuzziness and an estimation of reliability. OPSEARCH 53, 103–115 (2016). https://doi.org/10.1007/s12597-015-0217-6

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