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CLASSIFICATION AND RANK OF DMUS WITH INTERVAL INPUTS AND OUTPUTS IN DATA ENVELOPMENT ANALYSIS

机译:数据包络分析中间隔输入和输出的DMU分类和等级

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The original data envelopment analysis (DEA) model assumes that inputs and outputs data must be exact values. However, in the real word the data may be imprecise due to insufficient information or measure error and so on. For this reason, interval DEA is proposed. Andersen P and Petersen N C put forward a modified DEA (MDEA) in their paper called "A procedure for ranking efficient units in data envelopment analysis" in 1993 which can bring out more discriminative efficiency scores. This paper firstly extend the MDEA to an interval modified DEA (IMDEA) model. To get the upper bound of the efficiency score of the j_0 decision making unit (DMU_0), a DEA model with exact value is set up by adjusting the levels of interval inputs and outputs in favor of DMU_0 and aggressively against the other DMUs. On the contrary the model of getting lower bound of DMU_0 is also set up. As a result, efficiency score interval of each DMU is obtained. The efficiency score interval is more discriminative than the one got directly from general interval DEA. Based on this, all the DMUs are classified into three types: interval efficient, partly interval efficient and interval inefficient ones. The next, a new order relation between intervals which can express the DM's preference to the three types is brought forward. Consequently, a full and more convictive ranking is made on all the DMUs and more practical information is supplied for the decision maker. Finally an example is given.
机译:原始数据包络分析(DEA)模型假设输入和输出的数据必须是精确值。然而,在现实世界中的数据可能不精确由于信息不充分或测量误差等。出于这个原因,区间DEA建议。安德森P和彼得森N c个提出的改性DEA(MDEA)在1993年被称为“在数据包络分析排序高效单元A程序”他们的纸,它可以带出更有辨别效率得分。本文的MDEA首先延伸到改性DEA(IMDEA)模型的间隔。为了获得上界的效率得分的j_0决策单元(DMU_0)的,具有精确值的DEA模型是由有利于DMU_0的和积极对其他决策单元调整的间隔的输入和输出的电平设置。与此相反的越来越下界DMU_0的模式也成立。作为结果,获得每个DMU的效率得分间隔。效率得分间隔是更有辨别力比所述一个直接从一般间隔DEA得到。在此基础上,所有的DMU分为三种类型:区间有效,部分区间高效和低效间隔的人。接下来,间隔之间的新的顺序关系可以表达DM的偏好三类被提出。因此,一个完整的,更具有说服力的排名在所有的DMU,更实用的信息,为决策者提供做出。最后给出了一个例子。

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