Author/Authors :
abbari, A Department of Mathematics - Science and Research Branch Islamic Azad University, Tehran, Iran
Abstract :
Data envelopment analysis (DEA) helps the managers to separate and classify the ecient and
inefficient units in a homogenous group. DEA is a set of methods inferred from mathematics and other
sciences in which the branch of unit ranking can be significantly effective in improving managerial
decisions. Although this branch in DEA is considered still young, it has proved its ability in solving
some problems like production planning, resource allocation, inventory control, etc. The managers
who care about their results quality cannot be indifferent to units ranking. In this article, to rank
the units which are under-evaluated, rstly the decision-making unit (DMU) is removed from the
production possibility set (PPS), and then the new PPS is produced. The unit under evaluation
is inside or outside of the new PPS. Therefore, to benchmark the under-evaluation DMU to new
frontiers, two models are solved. If the removed unit is outside of the new PPS, the first model is
feasible, and the second model is infeasible. If the removed unit is inside or on the frontier of the new
PPS, both models are feasible. The method presented in this article for ranking the under-evaluation
units has these characteristics: 1- this model can distinguish extreme and non-extreme efficient units
and inefficient units. 2- Also, the presented models for ranking DMUs can be changed into a linear
model. 3- This method shows stability in changing small or near-zero data. 4- It does not assign a
false ranking. The presented methods in this article are able to distinguish the set of extreme and
non-extreme efficient and inefficient units as well as being able to overcome the common problems
in ranking. In this article, suggested models are introduced in 3.1 which are able to rank all under
evaluation units except non-extreme ecient units, this problem is solved in 3.2, in other words in
3.2 all DMUs are ranked