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A novel hybrid approach based on fuzzy DEA-AHP

机译:一种基于模糊DEA-AHP的新型混合方法

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摘要

The data envelopment analysis (DEA) model is a non-parametric programming technique that helps to efficiency evaluating for every decision making units (DMUs) with multiple inputs and multiple outputs. In traditional DEA model, we need crisp data. But in the real world, most of the data are imprecise and uncertain. A major cause of uncertainty related to the non-quantifiable, incomplete and unachievable information. For this reason, fuzzy logic and fuzzy sets developed in different models of DEA. In this paper, a new hybrid model is developed for performance evaluation problems ranking of DMUs, with multiple inputs and fuzzy outputs. To achieve the best ranking of DMUs, fuzzy analytical hierarchy process (FAHP) is applied. Solving FAHP ends up in a full ranking of DMUs. Finally, to illustrate the proposed model an example is presented.
机译:数据包络分析(DEA)模型是一种非参数编程技术,有助于对具有多个输入和多个输出的每个决策单元(DMU)进行效率评估。在传统的DEA模型中,我们需要清晰的数据。但是在现实世界中,大多数数据都是不准确且不确定的。不确定性的主要原因与不可量化,不完整和无法实现的信息有关。因此,在DEA的不同模型中开发了模糊逻辑和模糊集。在本文中,针对具有多个输入和模糊输出的DMU的性能评估问题排名,开发了一种新的混合模型。为了获得DMU的最佳排名,应用了模糊层次分析法(FAHP)。解决FAHP最终将获得DMU的完整排名。最后,为了说明所提出的模型,给出了一个例子。

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