  Applications of data envelopment analysis (DEA) show that many inefficient
units are projected onto the weakly efficient parts of the frontier when
efficiency scores are computed. However this fact disagrees with the main
concept of the DEA approach, because the efficiency score of an inefficient
unit has to be measured relative to an efficient unit. As a consequence
inaccurate efficiency scores may be obtained. This happens because a
non-countable (continuous) production possibility set is determined on a basis
of a finite number of production units. It has been proposed in the literature
to use artificial production units in the primal space of inputs and outputs as
a starting point in order to improve the frontier of the DEA models. Farrell
was the first who introduced artificial units in the primal space of inputs and
outputs in order to secure convex isoquants. In previous papers we introduced
the notion of terminal units. Moreover, some relationships were established
between terminal units and other sets of units that were proposed for improving
envelopment. In this paper we develop an algorithm for improving the frontier.
The construction of algorithm is based on the notion of terminal units. Our
theoretical results are verified by computational experiments using real-life
data sets and also confirmed by graphical examples.
