one of the important issues in data envelopment analysis (dea) is sensitivity analysis. heretofore the existent studies have considered the data modification of inputs and outputs in one or multiple dmus. in this paper the number of dmus is increased and a stability region is obtained in  by applying defining hyperplanes in which if the added dmu (only one dmu) is in this region then all of the...

Anchor DMUs are a new class in the general classification of Decision Making Units (DMUs) in Data Envelopment Analysis (DEA). An anchor DMU in DEA is an extreme-efficient DMU that defines the transition from the efficient frontier to the free-disposability part of the boundary of the Production Possibility Set (PPS). In this paper, the anchor points of the PPS of the CCR model are investigated....

One of the important issues in data envelopment analysis (DEA) is sensitivity analysis. Heretofore the existent studies have considered the data modification of inputs and outputs in one or multiple DMUs. In this paper the number of DMUs is increased and a stability region is obtained in  by applying defining hyperplanes in which if the added DMU (only one DMU) is in this region then all of the...

The production possibility set (PPS) is defined as the set of all inputs and outputs of a system in which inputs can produce outputs. In data envelopment analysis (DEA), identification of the strong defining hyperplanes of the empirical production possibility set (PPS) is important, because they can be used for determining rates of change of outputs with change in inputs. Also, efficient hyperp...

This paper presents an algorithm to compute the value of the inverse Laplace transforms of rational functions with poles on arrangements of hyperplanes. As an application, we present an efficient computation of the partition function for classical root systems.

This paper explores the use of thresholded hyperplanes as the building blocks of a classifier for face detection. We are motivated by the work of Viola and Jones [10] who used Haar-like wavelet features as their weak classifiers in the AdaBoost learning algorithm. These weak classifiers were chosen for their speed. We explore how much may be gained by using more powerful but less computationall...

This paper addresses issue of sensitivity of efficiency classification of variable returns to scale (VRS) technology for enhancing the credibility of data envelopment analysis (DEA) results in practical applications when an additional decision making unit (DMU) needs to be added to the set being considered. It also develops a structured approach to assisting practitioners in making an appropria...

The production possibility set (PPS) is defined as the set of all inputs and outputs of a system in which inputs can produce outputs. In data envelopment analysis (DEA), identification of the strong defining hyperplanes of the empirical production possibility set (PPS) is important, because they can be used for determining rates of change of outputs with change in inputs. Also, efficient hyperp...