Merging Decision-Making Units with Fuzzy Data

S. Ghobadi, Khosro Soleimani-Chamkhorami
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引用次数: 1

Abstract

This paper studies the problem of target setting for a generated entity from a merger among two or more decision making units. Identification of the inherited input/output levels from merging decision-making units is an important issue. In this study, a novel inverse data envelopment analysis model is introduced for target setting of a merger in the presence of fuzzy data. This model enables the merged unit to recognize the required input/output levels from merging units to achieve a predefined efficiency target. Moreover, a fuzzy linear programming model is presented for estimating the minimum attainable efficiency score through a given merging. Then, the performance of the proposed method is examined through a banking application.
用模糊数据合并决策单元
研究了两个或多个决策单元合并后生成实体的目标设置问题。确定合并决策单位继承的投入/产出水平是一个重要问题。本文提出了一种新的数据反包络分析模型,用于模糊数据存在下的并购目标设定。该模型使合并单元能够识别合并单元所需的输入/输出级别,以实现预定义的效率目标。在此基础上,提出了一种模糊线性规划模型,用于估计给定合并的最小可达效率分数。然后,通过一个银行应用程序检验了所提出方法的性能。
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