Enhanced Russell measure in fuzzy DEA

Enhanced Russell measure in fuzzy DEA
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模糊 DEA 中的增强罗素测度

DOI:
10.1504/ijdats.2010.032454
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发表时间:
2010-04
影响因子:
--
通讯作者:
Li Yongjun
Li Yongjun
中科院分区:
--
文献类型:
--
作者:
Wang Meiqiang;Li Yongjun

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经典的DEA模型(CCR、BCC)的径向测度是不完全的,它们只是投入和产出效率的单独测度,其效率指标忽略了非零的投入和产出松弛。改进的Russell图测度(ERM)消除了这些缺陷。现有的模糊DEA模型都是CCR或BCC模型的推广,决策单元的有效性最终是CCR或BCC模型的解。在ERM模型的基础上,提出了一种模糊DEA模型,用于处理给定模糊输入和输出数据的效率评价问题,并采用基于α-截数比较的排序方法.通过柔性制造系统的性能评估的应用程序和比较结果说明了所提出的框架。与基于CCR或BCC模型的模糊DEA模型相比,该方法的效率测度相对更合理,更能反映实际过程。
The radial measures of classical DEA models (CCR, BCC) are incomplete, they are only separate measures of input and output efficiency and their efficiency index omit the non-zero input and output slacks. Enhanced Russell graph measure (ERM) eliminates these deficiencies. All of the existing fuzzy DEA models are extension of CCR or BCC model, efficiencies of DMUs, ultimately, are solution of CCR or BCC model. Based on ERM model, a fuzzy DEA model is proposed to deal with the efficiency evaluation problem with the given fuzzy input and output data, by using a ranking method based on the comparison of α-cuts. The proposed framework is illustrated through an application to performance assessment of flexible manufacturing system and comparative results are presented. The efficiency measure of the proposed approach is relatively more reasonable than those of fuzzy DEA models based on CCR or BCC model and represents some real-life processes more appropriately.
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