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首页> 外文期刊>International Journal of Industrial Engineering & Production Research >Finding a Common Set of Weights by the Fuzzy Entropy Compared with Data Envelopment Analysis - A Case Study
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Finding a Common Set of Weights by the Fuzzy Entropy Compared with Data Envelopment Analysis - A Case Study

机译:与数据包络分析相比较,通过模糊熵寻找公共权重的案例研究

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A data envelopment analysis (DEA) method can be regarded as a useful management tool to evaluate decision making units (DMUs) using multiple inputs and outputs. In some cases, we face with imprecise inputs and outputs, such as fuzzy or interval data, so the efficiency of DMUs will not be exact. Most researchers have been interested in getting efficiency and ranking DMUs recently. Models of the traditional DEA cannot provide a completely ranking of efficient units; however, it can just distinguish between efficient and inefficient units. In this paper, the efficiency scores of DMUs are computed by a fuzzy CCR model and the fuzzy entropy of DMUs. Then these units are ranked and compared with two foregoing procedures. To do this, the fuzzy entropy based on common set of weights (CSW) is used. Furthermore, the fuzzy efficiency of DMUs considering the optimistic level is computed. Finally, a numerical example taken from a real-case study is considered and the related concept is analyzed.
机译:数据包络分析(DEA)方法可以看作是使用多个输入和输出评估决策单元(DMU)的有用管理工具。在某些情况下,我们面临着不精确的输入和输出,例如模糊数据或区间数据,因此DMU的效率将不够精确。大多数研究人员最近对提高效率和对DMU排名感兴趣。传统DEA的模型无法提供有效单位的完整排名。但是,它只能区分有效单位和无效单位。本文通过模糊CCR模型和DMU的模糊熵来计算DMU的效率得分。然后,对这些单位进行排名,并与上述两个步骤进行比较。为此,使用了基于公共权重集(CSW)的模糊熵。此外,计算了考虑乐观水平的DMU的模糊效率。最后,考虑了一个来自实际案例研究的数值示例,并分析了相关概念。

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