Volume 52, Number 2, April–June 2018
Fuzzy Data Envelopment Analysis: Recent Developments and Applications
|Page(s)||619 - 643|
|Published online||20 July 2018|
Modeling fuzzy data envelopment analysis under robust input and output data
College of Science, Hebei Agricultural University,
2 College of Mathematics and Information Science, Hebei University, Baoding 071002, Hebei, China
3 Key Lab. of Machine Learning and Computational Intelligence, College of Mathematics and Information Science, Hebei University, Baoding, 071002, China
* Corresponding author: firstname.lastname@example.org
Accepted: 6 May 2017
This paper offers a fuzzy optimization framework for data envelopment analysis (DEA) to evaluate the relative efficiency of decision making units (DMUs) with parametric interval-valued fuzzy variable-based inputs and outputs. The parametric interval-valued fuzzy variable-based inputs and outputs is employed to capture the uncertainty of data on the basis of professional judgements or empirical estimations. The DEA problem is formulated as fuzzy expectation model with credibility constraints. When the inputs and outputs are mutually independent parametric interval-valued triangular fuzzy variables, we investigate the parametric equivalent representations of expectation objective function and chance constraints. In order to find the optimal solution of our DEA model, a domain decomposition method is proposed. Finally, the numerical example on the sustainable supplier evaluation and selection problem is provided to demonstrate the efficiency of the proposed DEA model and domain decomposition method.
Mathematics Subject Classification: 90C70 / 91B16 / 90C90
Key words: Data envelopment analysis / fuzzy programming / parametric interval-valued fuzzy variable / lambda selection variable / domain decomposition method
© EDP Sciences, ROADEF, SMAI 2018
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