Efficiency Assessment and Target Setting Using a Fully Fuzzy DEA Approach

Abstract

Data envelopment analysis (DEA) is a non-parametric methodology for efficiency assessment. This paper proposes a new radial, input-oriented and fully fuzzy DEA approach, based on an LU-fuzzy partial order (L for lower, U for upper), for assessing the relative efficiency of a set of Decision-Making Units (DMUs). The proposed approach involves a radial input contraction, Phase I, and an additive slacks maximization, Phase II. Each phase is first formulated as a fully fuzzy linear programming (FFLP), and then it is transformed into a multiobjective optimization problem. The latter is solved using the lexicographic weighted Tchebycheff method. The proposed fully fuzzy DEA approach provides, for each unit, a fuzzy efficiency measure and a fuzzy target operating point. A classification of the efficiency status of the units is also presented. Computational experiences and comparison with other fuzzy DEA approaches are reported.