Efficiency measure in a fully fuzzy DEA
M. Arana Jiménez, A. Younesi, M. C. Sánchez Gil, S. Lozano Segura
In this work, we study a Data Envelopment Analysis (DEA) whose inputs and outputs data present uncertainty, modeled by means of fuzzy numbers. In this context, a new radial, input-oriented and fully fuzzy DEA approach is proposed, based on an LU-fuzzy partial order. We get a model to assess the relative efficiency of a set of Decision Making Units (DMUs), and then classify each DMUs as efficient, weakly efficient, partially efficient, or inefficient. To do that, the proposed method requires two phases. In each phase a fully fuzzy linear programming is formulated, which is transformed into a multiobjective optimization problem, and solved using the lexicographic weighted Tchebycheff method. The proposed method for a fully fuzzy DEA approach provides, for each unit, a fuzzy efficiency measure and a fuzzy target operating point. To illustrate the power of the present approach, a comparison with other recent method is offered.
Keywords: DEA, fuzzy data, fully fuzzy linear programming, multiobjective optimization
Scheduled
Data Envelopment Analysis II
June 10, 2022 4:00 PM
Conference hall
Other papers in the same session
M. D. Guillén, J. Aparicio Baeza, M. Esteve Campello
F. Fernández Palacín, M. A. López Sánchez, M. Muñoz Márquez
V. J. España Roch, J. Aparicio Baeza, X. Barber Vallés, M. Esteve Campello
R. Moragues, J. Aparicio, M. Esteve
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