@article{(International Science Index):http://waset.org/publications/10009165,
  title    = {Classifying and Predicting Efficiencies Using Interval DEA Grid Setting},
  author    = {Yiannis G. Smirlis },
  country   = {Greece},
  institution={University of Piraeus},
  abstract  = {The classification and the prediction of efficiencies in Data Envelopment Analysis (DEA) is an important issue, especially in large scale problems or when new units frequently enter the under-assessment set. In this paper, we contribute to the subject by proposing a grid structure based on interval segmentations of the range of values for the inputs and outputs. Such intervals combined, define hyper-rectangles that partition the space of the problem. This structure, exploited by Interval DEA models and a dominance relation, acts as a DEA pre-processor, enabling the classification and prediction of efficiency scores, without applying any DEA models.},
    journal   = {International Journal of Mathematical, Computational, Physical, Electrical and Computer Engineering},  volume    = {12},
  number    = {6},
  year      = {2018},
  pages     = {119 - 123},
  ee        = {http://waset.org/publications/10009165},
  url       = {http://waset.org/Publications?p=138},
  bibsource = {http://waset.org/Publications},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 138, 2018},
}