Fuzzy efficiency measures in data envelopment analysis
Fuzzy Sets and Systems
A fuzzy DEA/AR approach to the selection of flexible manufacturing systems
Computers and Industrial Engineering
Fuzzy data envelopment analysis (DEA): Model and ranking method
Journal of Computational and Applied Mathematics
Fuzzy data envelopment analysis and its application to location problems
Information Sciences: an International Journal
Efficiency measurement for network systems: IT impact on firm performance
Decision Support Systems
Efficiencies of two-stage systems with fuzzy data
Fuzzy Sets and Systems
Self-organizing fuzzy aggregation models to rank the objects with multiple attributes
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Efficiency measures for multiplant firms
Operations Research Letters
Computing fuzzy process efficiency in parallel systems
Fuzzy Optimization and Decision Making
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This paper investigates the problem of efficiency measurement for parallel production systems where a number of processes are operating independently within the system, and some input/output data are fuzzy numbers. When all observations have precise values, previous studies found that the system efficiency measured from a relational data envelopment analysis model is a weighted average of the process efficiencies. Based on the extension principle of fuzzy theory, this paper constructs a pair of two-level programming models to calculate the lower and upper bounds of the @a-cuts of the fuzzy system and process efficiencies. It is shown that the fuzzy system efficiency is still a weighted average of the fuzzy process efficiencies. However, the weights need not be the same at different @a levels. The case of measuring the teaching and research efficiencies of chemistry departments in UK universities with a qualitative factor of research quality discussed in the literature is used as an example to explain the idea of this paper. Fuzzy measures obtained from fuzzy observations are more informative than crisp measures obtained from assuming the fuzzy observations to be precise.