A discriminative multi-objective programming method for solving network dea

被引：0

作者：

Kao, Han-Ying ^{[1
]}

Chan, Chieh-Yu ^{[1
]}

机构：

[1] Department of Computer Science and Information Engineering, National Dong Hwa University, Hualien

来源：

Kao, H.-Y. (teresak@mail.ndhu.edu.tw) | 1600年 / Springer Science and Business Media Deutschland GmbH卷 / 20期

关键词：

Bcc models; Information entropy; Multi-objective programming; Network dea;

D O I：

10.1007/978-3-642-35452-6_34

中图分类号：

学科分类号：

摘要：

This study proposes the multi-objective programming (MOP) method for solving network DEA models. In the proposed method, the efficiency of each division (within a DMU) and the overall efficiency of the DMU are formulated as different objective functions. By the fuzzy approach, the overall as well as the divisional efficiencies can be computed in a cohesive framework. We adopt information entropy to estimate the discriminating power of various DEA models. The results show that this study obtains satisfactory and discriminating efficiency scores compared with related studies. © Springer-Verlag Berlin Heidelberg 2013.

引用

页码：327 / 335

页数：8

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