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COMPOSITE NETWORK DATA ENVELOPMENT ANALYSIS MODEL

机译:组合网络数据包络分析模型

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摘要

This paper extends the DEA model to considering the decision-making unit (DMU) with the network structure. We define the network DMU and its network DEA efficiency based on the postulate system. On the series structure of the DMU, we further discuss a sequential optimization model originally proposed by Sexton and Lewis.1,2 Based on their work, we extend to the DMU with general network of k stages and propose a composite network DEA model which evaluate the network DEA efficiency by solving only one linear programming. We show that the network efficiency obtained from the composite model is equivalent to that obtained by the sequential optimization model. We show that a network DMU is network-efficient if and only if it is efficient at all stages. That is, the network-efficient DMU follows the "Bellman Optimal Principle." Our model shows that if a network DMU is not DEA-efficient, then it is not efficient at one stage at least.We also define the projection of the network DMU on the corresponding production possibility set of network DMUs. Finally, we discuss other basic structures of the network DMU and show that the overall network DEA model can be extended to the general network DMU.
机译:本文将DEA模型扩展为考虑具有网络结构的决策单元(DMU)。我们基于假设系统定义了网络DMU及其网络DEA效率。在DMU的序列结构上,我们进一步讨论了Sexton和Lewis最初提出的顺序优化模型。1,2,基于他们的工作,我们将其扩展到具有k个阶段的通用网络的DMU,并提出了一种用于评估通过仅解决一个线性规划来提高网络DEA效率。我们表明,从复合模型获得的网络效率与通过顺序优化模型获得的网络效率相当。我们证明,仅当在所有阶段都有效时,网络DMU才具有网络效率。即,具有网络效率的DMU遵循“贝尔曼最佳原理”。我们的模型表明,如果网络DMU效率不高,至少在一个阶段效率不高。我们还定义了网络DMU在相应的网络DMU生产可能性集上的投影。最后,我们讨论了网络DMU的其他基本结构,并表明可以将整个网络DEA模型扩展到通用网络DMU。

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