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Uncertain random data envelopment analysis for technical efficiency
     
  
  
刊名:
Fuzzy Optimization and Decision Making: A Journal of Modeling and Computation Under Uncertainty
作者:
Jiang, Bao
(Ocean Univ China)
Feng, Wenxue
(Ocean Univ China)
Li, Jian
(Ocean Univ China)
刊号:
519LB020
ISSN:
1568-4539
出版年:
2022
年卷期:
2022, vol.21, no.1
页码:
1-20
总页数:
20
分类号:
O22
关键词:
Data envelopment analysis
;
Uncertainty theory
;
Chance theory
;
Uncertain random variable
;
Stability radii
;
DEA
;
MODELS
参考中译:
语种:
eng
文摘:
Data envelopment analysis (DEA) is a classical and prevailing tool for estimating relative efficiencies of multiple decision making units (DMUs). However, sometimes DMUs' inputs and outputs cannot be observed accurately in practical cases, and hence this paper attempts to propose an uncertain random DEA model to evaluate the efficiencies of DMUs with uncertain random inputs and outputs. The sensitivity and stability of this new model are further analyzed with the aim to figure out the stability radius of each DMU. Finally, a numerical example is presented for illustrating the proposed uncertain random DEA model.
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