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DEA Cross-Efficiency Ranking Method Based on Grey Correlation Degree and Relative Entropy

机译:基于灰色相关度和相对熵的DEA交叉效率排名方法

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摘要

The ranking of decision-making units (DMUs) is one of the most significant issues in efficiency evaluation. However, the calculation results from the traditional Data envelopment analysis(DEA), method sometimes include multiple efficient DMUs or multiple DMUs with the same efficiency value, in which case the approach is weak in distinguishing among these DMUs. Therefore, this study proposes a DEA cross-efficiency ranking method based on the relative entropy evaluation method and the grey relational analysis method. First, the approach uses the cross-efficiency matrix as the decision matrix of multiple criteria decision-making (MCDM), and the relationship between DMU and the ideal solution is analyzed by the grey relational analysis method and the relative entropy evaluation method. Then, the degree of the criteria is determined by Shannon entropy, and the weighted grey correlation degree and the weighted relative entropy are obtained. Finally, with the comprehensive relative closeness degree between the DMU and the ideal solution, we can sort all the DMUs accordingly. In a comparative analysis, it shows that this method analyzes the similarity between DMUs and the ideal solution from the information distance and the similarity of the data sequence curve, and has certain advantages for analyzing the ranking of DMUs.
机译:决策单位(DMUS)的排名是效率评估中最重要的问题之一。然而,传统数据包络分析(DEA)的计算结果,方法有时包括具有相同效率值的多个高效DMU或多个DMU,在这种情况下,该方法在这些DMU中区分该方法是弱的。因此,本研究提出了基于相对熵评估方法和灰色关系分析方法的DEA交叉效率排名方法。首先,该方法使用跨效率矩阵作为多标准决策(MCDM)的判定矩阵,并通过灰色关系分析方法和相对熵评估方法分析DMU与理想解决方案之间的关系。然后,标准的程度由香农熵确定,获得加权灰色相关程度和加权相对熵。最后,随着DMU与理想解决方案之间的综合相对近立程度,我们可以相应地对所有DMU进行排序。在比较分析中,它表明该方法分析了DMU与来自信息距离的理想解决方案之间的相似性和数据序列曲线的相似性,并且具有分析DMUS排名的某些优点。

著录项

  • 期刊名称 Entropy
  • 作者

    Qin Si; Zhanxin Ma;

  • 作者单位
  • 年(卷),期 2019(21),10
  • 年度 2019
  • 页码 966
  • 总页数 14
  • 原文格式 PDF
  • 正文语种
  • 中图分类
  • 关键词

    机译:数据包络分析;交叉效率;灰色相关程度;相对熵;

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