Grey relational analysis

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Grey relational analysis (GRA), also called Deng's Grey Incidence Analysis model, was developed by a Chinese Professor Julong Deng of Huazhong University of Science and Technology. It is one of the most widely used models of Grey system theory. GRA uses a specific concept of information. It defines situations with no information as black, and those with perfect information as white. However, neither of these idealized situations ever occurs in real world problems. In fact, situations between these extremes are described as being grey, hazy or fuzzy. Therefore, a grey system means that a system in which part of information is known and part of information is unknown. With this definition, information quantity and quality form a continuum from a total lack of information to complete information – from black through grey to white. Since uncertainty always exists, one is always somewhere in the middle, somewhere between the extremes, somewhere in the grey area.

Grey analysis then comes to a clear set of statements about system solutions. At one extreme, no solution can be defined for a system with no information. At the other extreme, a system with perfect information has a unique solution. In the middle, grey systems will give a variety of available solutions. Grey analysis does not attempt to find the best solution, but does provide techniques for determining a good solution, an appropriate solution for real world problems.

Dr. Sifeng Liu, the pupil of Deng, renamed the concept of GRA to "Deng's Degree of Grey Incidence Analysis Model" and building upon it proposed his own "Absolute Degree of Grey Incidence Model" (Liu et al., 2017).

References[edit]

  • Chan WK and Tong TKL, (2007), Multi-criteria material selections and end-of-life product strategy: Grey relational analysis approach, Materials & Design, Volume 28, Issue 5, Pages 1539-1546
  • Free Multi-criteria Decision Aiding (MCDA) Tools for Research Students http://sites.google.com/site/mcdafreeware/
  • Liu, SF., Yang, Y., and Forrest, J. (2017). Grey Data Analysis. Springer.