Robust Solutions to Least-Squares Problems with Uncertain Data
SIAM Journal on Matrix Analysis and Applications
Mathematics of Operations Research
Fuzzy efficiency measures in data envelopment analysis
Fuzzy Sets and Systems
Fuzzy DEA: a perceptual evalution method
Fuzzy Sets and Systems
Data Envelopment Analysis: A Comprehensive Text with Models, Applications References, and DEA-Solver Software with Cdrom
Robust Solutions to Uncertain Semidefinite Programs
SIAM Journal on Optimization
Benchmarking Mechanical Ventilation Services in Teaching Hospitals
Journal of Medical Systems
Idea and Ar-Idea: Models for Dealing with Imprecise Data in Dea
Management Science
An Assurance Interval for the Non-Archimedean Epsilon in DEA Models
Operations Research
A polynomial-time algorithm for finding ɛ in DEA models
Computers and Operations Research
Operations Research
Finding the most efficient DMUs in DEA: An improved integrated model
Computers and Industrial Engineering
A fuzzy DEA/AR approach to the selection of flexible manufacturing systems
Computers and Industrial Engineering
Fuzzy efficiency measures in fuzzy DEA/AR with application to university libraries
Expert Systems with Applications: An International Journal
Fuzzy data envelopment analysis and its application to location problems
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Computers and Industrial Engineering
Interval efficiency assessment using data envelopment analysis
Fuzzy Sets and Systems
Robust solutions of uncertain linear programs
Operations Research Letters
Robust linear optimization under general norms
Operations Research Letters
Computers and Industrial Engineering
Duality and efficiency computations in the cost efficiency model with price uncertainty
Computers and Operations Research
Computers and Industrial Engineering
Piecewise Linear Virtual Inputs/Outputs in Interval DEA
International Journal of Operations Research and Information Systems
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Crisp input and output data are fundamentally indispensable in traditional data envelopment analysis (DEA). However, the input and output data in real-world problems are often imprecise or ambiguous. Some researchers have proposed interval DEA (IDEA) and fuzzy DEA (FDEA) to deal with imprecise and ambiguous data in DEA. Nevertheless, many real-life problems use linguistic data that cannot be used as interval data and a large number of input variables in fuzzy logic could result in a significant number of rules that are needed to specify a dynamic model. In this paper, we propose an adaptation of the standard DEA under conditions of uncertainty. The proposed approach is based on a robust optimization model in which the input and output parameters are constrained to be within an uncertainty set with additional constraints based on the worst case solution with respect to the uncertainty set. Our robust DEA (RDEA) model seeks to maximize efficiency (similar to standard DEA) but under the assumption of a worst case efficiency defied by the uncertainty set and it's supporting constraint. A Monte-Carlo simulation is used to compute the conformity of the rankings in the RDEA model. The contribution of this paper is fourfold: (1) we consider ambiguous, uncertain and imprecise input and output data in DEA; (2) we address the gap in the imprecise DEA literature for problems not suitable or difficult to model with interval or fuzzy representations; (3) we propose a robust optimization model in which the input and output parameters are constrained to be within an uncertainty set with additional constraints based on the worst case solution with respect to the uncertainty set; and (4) we use Monte-Carlo simulation to specify a range of Gamma in which the rankings of the DMUs occur with high probability.