Traditional DEA models deal with measurements of relative efficiency of DMUs regarding multiple-inputs vs. multiple-outputs. One of the drawbacks of these models is the neglect of intermediate products or linking activities. After pointing out needs for inclusion of them in DEA models, we propose a slacks-based network DEA model that can deal with intermediate products. Using this model we can ...

Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. In the conventional DEA, all the data assume the form of specific numerical values. However, the observed values of the input and output data in real-life problems are sometimes imprecise or vague. Previous method...

This paper defines and describes the classification of heterogeneous and otherwise abstract multi-user virtual environments. Furthermore, the aim of the paper is to compare the most critical features of the worlds, and thus, to establish solid foundation for the development of ideal multi-user virtual world. Total of 15 virtual worlds have been selected for qualitative survey, which includes me...

the ways of placing decision making units (dmus) in certain clusters are found as a subject in statistics, these ways usually are heuristic. the proposed clustering approach in this article considers preferences of dmus. this study applies data envelopment analysis (dea) dmus are clustered by solving multi-objective linear problem (molp) and by considering preferences of each dmu at production ...

The Malmquist index (MI) has demonstrated its usefulness in comparing the performances of Decision Making Units (DMUs) performances. global MI (GMI) been suggested as a means to overcome three drawbacks MI: non-circularity, disparate measurements, and infeasibility. Recently, it appeared that can also be used compare groups DMUs. While this new function increased usefulness, presents same MI. I...

In many applications, ranking of decision making units (DMUs) is a problematic technical task procedure to decision makers in data envelopment analysis (DEA), especially when there are extremely efficient DMUs. In such cases, many DEA models may usually get the same efficiency score for different DMUs. Hence, there is a growing interest in ranking techniques yet. The purpose of this paper is ra...