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首页> 外文期刊>International journal of productivity and quality management >Data envelopment analysis: an efficient duo linear programming approach
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Data envelopment analysis: an efficient duo linear programming approach

机译:数据包络分析:高效的线性规划方法

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Data envelopment analysis (DEA) is a powerful mathematical method that utilises linear programming (LP) to determine the relative efficiencies of a set of functionally similar decision-making units (DMUs). Evaluating the efficiency of DMUs continues to be a difficult problem to solve, especially when the multiplicity of inputs and outputs associated with these units is considered. Problems related to computational complexities arise when there are a relatively large number of redundant variables and constraints in the problem. In this paper, we propose a three-step algorithm to reduce the computational complexities and costs in the multiplier DEA problems. In the first step, we identify some of the inefficient DMUs through input-output comparisons. In the second step, we specify the efficient DMUs by solving a LP model. In the third step, we use the results derived from the second step and another LP model to obtain the efficiency of the inefficient DMUs. We also present a numerical example to demonstrate the applicability of the proposed framework and exhibit the efficacy of the procedures and algorithms.
机译:数据包络分析(DEA)是一种强大的数学方法,它利用线性规划(LP)来确定一组功能相似的决策单元(DMU)的相对效率。评估DMU的效率仍然是一个难以解决的问题,尤其是在考虑与这些单元相关的输入和输出的多样性时。当问题中存在大量冗余变量和约束时,就会出现与计算复杂性有关的问题。在本文中,我们提出了一种三步算法来减少乘法器DEA问题中的计算复杂性和成本。第一步,我们通过输入输出比较来识别一些效率低下的DMU。在第二步中,我们通过求解LP模型来指定有效的DMU。在第三步中,我们使用从第二步中获得的结果和另一个LP模型来获得低效率DMU的效率。我们还提供了一个数值示例,以证明所提出框架的适用性,并展示了程序和算法的有效性。

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