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Parabolic Intuitionistic Fuzzy based Data Envelopment Analysis

机译:抛物线直觉模糊基于数据包络分析

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A Fuzzy Data Envelopment Analysis (FDEA) is a popular technique to measure the relative efficiency of a Decision Making Unit (DMU) with respect to other DMUs under uncertain/imprecise information represented in form of fuzzy input and fuzzy output. However, in a real life application, due to higher order of uncertainty, the fuzzy set may not be a suitable choice, as the membership value alone cannot represent the input/output information precisely. Therefore in the paper, we extend the FDEA model to Intuitionistic Fuzzy Data Envelopment Analysis (IFDEA) model, namely, Parabolic Intuitionistic Fuzzy based Data Envelopment Analysis, where the input and output are demonstrated by Parabolic Intuitionistic Fuzzy Numbers (PIFNs). Further the α-cut and ß-cut approach are used to convert the parabolic intuitionistic fuzzy inputs and outputs into their corresponding intervals and to compute the parametric efficiencies of the given DMUs. Additionally, we have used the section formula to defuzzify the parabolic intuitionistic fuzzy numbers into their crisp form to execute the optimization problem. Finally, the cross-efficiency technique is used to rank the DMUs.
机译:模糊数据包络分析(FDEA)是一种流行的技术,用于在模糊输入和模糊输出的形式表示的不确定/不精确的信息下测量决策单元(DMU)的相对效率。然而,在实际应用中,由于更高的不确定性,模糊组可能不是合适的选择,因为单独的成员值不能精确地表示输入/输出信息。因此,我们将FDEA模型扩展到直觉模糊数据包络分析(IFDEA)模型,即抛物线直觉基于模糊的数据包络分析,其中抛物线直觉模糊数(PIFN)证明了输入和输出。此外,α-Cut和β-Cut方法用于将抛物线直觉模糊输入和输出转换为它们的相应间隔,并计算给定DMU的参数效率。此外,我们使用该章节公式将抛物线直觉模糊数字Defuzzzzzzify Defulative Intuation的模糊数字放入其清晰的表单中以执行优化问题。最后,使用交叉效率技术对DMU进行排名。

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