Influence of Allocating One New Fuzzy Source on DMUs Efficiency

Many studies have been conducted on sensitivity analysis in DEA which focus on changing the value of data or reallocation of inputs. In this article, some models have been presented which can be used for allocating one or more new inputs between the DMUs in a way that some of the inefficient units have been modified to efficient units. These models have been offered for both crisp inputs and fuzzy inputs. The presented model allocates the new inputs between the DMUs in a way that the distance of new inputs from the fair allocation is minimized by applying the Chebyshev's norm. The mentioned models are utilized in four numerical examples and the related results are reported. To the present, the related studies have been focused on changing the value of the old inputs, however, this article paid particular attention to allocating the new input(s) between the DMUs.