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首页> 外文期刊>European Journal of Operational Research >Qualitative factors in data envelopment analysis: A fuzzy number approach
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Qualitative factors in data envelopment analysis: A fuzzy number approach

机译:数据包络分析中的定性因素:模糊数法

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摘要

Qualitative factors are difficult to mathematically manipulate when calculating the efficiency in data envelopment analysis (DEA). The existing methods of representing the qualitative data by ordinal variables and assigning values to obtain efficiency measures only superficially reflect the precedence relationship of the ordinal data. This paper treats the qualitative data as fuzzy numbers, and uses the DEA multipliers associated with the decision making units (DMUs) being evaluated to construct the membership functions. Based on Zadeh's extension principle, a pair of two-level mathematical programs is formulated to calculate the α-cuts of the fuzzy efficiencies. Fuzzy efficiencies contain more information for making better decisions. A performance evaluation of the chemistry departments of 52 UK universities is used for illustration. Since the membership functions are constructed from the opinion of the DMUs being evaluated, the results are more representative and persuasive.
机译:在计算数据包络分析(DEA)的效率时,很难用数学方法处理定性因素。现有的用序数变量表示定性数据并赋值以获取效率度量的方法只是表面上反映了序数数据的优先关系。本文将定性数据视为模糊数,并使用与要评估的决策单位(DMU)相关的DEA乘数来构造隶属函数。基于Zadeh的可拓原理,制定了两个两级数学程序来计算模糊效率的α-割线。模糊效率包含更多信息,可以做出更好的决策。以英国52所大学的化学系的绩效评估为例。由于隶属函数是根据要评估的DMU的意见构建的,因此结果更具代表性和说服力。

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