Journal
COMPUTATIONAL & APPLIED MATHEMATICS
Volume 41, Issue 2, Pages -Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s40314-022-01780-y
Keywords
Efficiency; Fuzzy data; Fuzzy production possibility set; Fuzzy enhanced Russell graph measure; Fuzzy efficient targets
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Funding
- MINECO, Spain [MTM2017-89577-P]
- Spanish Ministry of Economy and Competitiveness [AYA2016-75931-C2-1-P]
- Consejeria de Educacion y Ciencia (Junta de Andalucia) [TIC-101]
- Spanish Ministry of Science, Innovation and Universities [PGC2018-095786-B-I00]
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This paper studies the efficiency assessment of Decision Making Units (DMUs) with fuzzy sets as inputs and outputs. It proposes a fuzzy enhanced Russell graph measure using polygonal fuzzy sets and LU-fuzzy partial orders. Compared with other fuzzy DEA approaches, the proposed method shows greater discriminant power and flexibility in modeling the input and output data.
This paper studies the efficiency assessment of Decision Making Units (DMUs) when their inputs and outputs are fuzzy sets. An axiomatic derivation of the fuzzy production possibility set is presented and a fuzzy enhanced Russell graph measure is formulated using a fuzzy arithmetic approach. The proposed approach uses polygonal fuzzy sets and LU-fuzzy partial orders, and provides crisp efficiency measures (and associated efficiency ranking) as well as fuzzy efficient targets. The proposed approach has been compared with other fuzzy DEA approaches on different datasets from the literature, and the results show that it has more discriminant power and more flexibility in modelling the input and output data.
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