Fuzzy context-dependent data envelopment analysis
Fuzzy context-dependent data envelopment analysis
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DOI：
10.1504/ijdats.2009.024293
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发表时间：
2009-03
期刊：
影响因子：
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通讯作者：
Meiqiang Wang;L. Liang
中科院分区：
文献类型：
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作者：
Meiqiang Wang;L. Liang
原始的上下文相关数据包络分析(DEA)是基于给定的评估上下文来衡量决策单元(DMU)的吸引力和进度，并且使用不同层次的有效前沿而不是传统的第一级有效前沿作为评估上下文。它仅限于清晰的数据。为了处理不精确的数据，引入了模糊性的概念，提出了一种基于α-Cuts比较的排序方法，在原始的上下文相关数据包络分析的基础上，给出了一种基于模糊观测值的决策单元更好的评价结果。该方法是对原始上下文相关DEA的模糊环境的扩展，它更好地描述了一些真实的过程。用一个数值算例说明了该方法的有效性。
The original context-dependent Data Envelopment Analysis (DEA) is developed to measure the attractiveness and progress of Decision-Making Units (DMUs) based on a given evaluation context and different strata of efficient frontiers, rather than the traditional first-level efficient frontier, are used as evaluation contexts. It is limited to crisp data. To deal with imprecise data, this paper introduces the notion of fuzziness and develops a procedure to provide finer evaluation results of DMUs with fuzzy observations based on the original context- dependent DEA by using a ranking method based on the comparison of α-cuts. The proposed approach is an extension to the fuzzy environment of the original context-dependent DEA; it represents some real-life processes more appropriately. A numerical example is used to illustrate the approach.