The purpose of this study is to utilize a new method for ranking extreme efficient decision making units (DMUs) based upon the omission of these efficient DMUs from reference set of inefficient and non-extreme efficient DMUs in data envelopment analysis (DEA) models with constant and variable returns to scale. In this method, an L2norm is used and it is believed that it doesn't have any existin...

Tracking subset relations between the contents containers on the heap is fundamental to modeling the semantics of many common programing idioms such as applying a function to a subset of objects and maintaining multiple views of the same set of objects. We introduce a relation, must reference sets, which subsumes the concept of must-aliasing and enables existing shape analysis techniques to eff...

Precise modeling of the structure of the heap and how objects are shared between various arrays or data structures is fundamental to understanding the behavior of a program. This paper introduces a novel higher order relation, reference set dominance, which subsumes the concept of aliasing and enables existing shape analysis techniques to, efficiently and accurately, model many types of contain...

Several metrics and indicators have been suggested in the past to evaluate multi-objective evolutionary and non-evolutionary algorithms. However, these metrics are known to have many problems that make their application sometimes unsound, and sometimes infeasible. This paper proposes a new approach, in which metrics are parameterized with respect to a reference set, on which depend the properti...