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Modeling Fuzzy Data Envelopment Analysis with Expectation Criterion

机译:模糊数据包络分析与期望标准

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This paper presents a new class of fuzzy expectation data envelopment analysis (FEDEA) models with credibility constraints. Since the proposed model contains the credibility of fuzzy events in the constraints and the expected value of a fuzzy variable in the objective, the solution process is very complex. Thus, in the case when the inputs and outputs are mutually independent trapezoidal fuzzy variables, we discuss the equivalent nonlinear forms of the programming model, which can be solved by standard optimization software. At the end of this paper, one numerical example is also provided to illustrate the efficiency of decision-making unites (DMUs) in the proposed model.
机译:本文介绍了具有可信度约束的新型模糊期望数据包络分析(FEDEA)模型。由于所提出的模型包含限制中的模糊事件的可信度和目标中的模糊变量的预期值,因此解决方案过程非常复杂。因此,在输入和输出是相互独立的梯形模糊变量的情况下,我们讨论了编程模型的等效非线性形式,其可以通过标准优化软件解决。在本文的末尾,还提供了一个数值示例以说明所提出的模型中的决策单元(DMUS)的效率。

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