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Abstract
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In conventional cost efficiency models, input
and output data and their corresponding input prices are
fundamentally known for each decision-making unit.
However, the observed values of the input and output data
in real problems are sometimes imprecise. This study
shows that the cost efficiency evaluation method can be
improved to account for situations where input–output data
and their corresponding input prices are fuzzy numbers. A
new fuzzy cost-minimizing model known as a possibilistic
linear programming problem is proposed to evaluate the
cost efficiency. In this model data information is considered
as triangular fuzzy numbers. Using the a-level-based
approach, the model is transformed into an interval programming
problem which is solved as a crisp parametric
linear programming model. In addition, new definitions of
the fuzzy cost efficiency and cost efficient unit are suggested.
Finally, a numerical example is presented to illustrate
the proposed method.
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