A Novel Two-Stage DEA Model in Fuzzy Environment: Application to Industrial Workshops Performance Measurement

被引：17
|
作者：
Soltani, M. R. [1 ]
Edalatpanah, S. A. [2 ]
Sobhani, F. Movahhedi [1 ]
Najafi, S. E. [1 ]
机构：
[1] Islamic Azad Univ, Dept Ind Engn, Sci & Res Branch, Tehran, Iran
[2] Ayandegan Inst Higher Educ, Dept Ind Engn, Mazandaran, Iran
来源：
INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS | 2020年 / 13卷 / 01期
关键词：
Effidency; Fuzzy data envelopment analysis; Two-stage DEA model; Industrial-workshops; DATA ENVELOPMENT ANALYSIS; EFFICIENCY DECOMPOSITION; PROGRAMMING PROBLEMS; NETWORK DEA; WEIGHTS;
D O I：
10.2991/ijcis.d.200731.002
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
One of the paramount mathematical methods to compute the general performance of organizations is data envelopment analysis (DEA). Nevertheless, in some cases, the decision-making units (DMUs) have middle values. Furthermore, the conventional DEA models have been originally formulated solely for crisp data and cannot handle the problems with uncertain information. To tackle the above issues, this paper presents a two-stage DEA model with fuzzy data. The recommended technique is based on the fuzzy arithmetic and has a simple construction. Furthermore, to illustrate the new model, we investigate the efficiency of some industrial workshops in Iran. The results show the effectiveness and robustness of the new model. (C) 2020 The Authors. Published by Atlantis Press B.V
引用
收藏
页码：1134 / 1152
页数：19
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