MDS is a dimensionality reduction technique. It can be divided into Metric multidimensional scaling, Generalized multidimensional scaling and Classical multidimensional scaling.
Generalized multidimensional scaling is an extension of metric multidimensional scaling, in which the target space is an arbitrary smooth non-Euclidean space. In cases where the dissimilarities are distances on a surface and the target space is another surface, GMDS allows finding the minimum-distortion embedding of one surface into another.
Classical multidimensional scaling is also known as Principal Coordinates Analysis, Torgerson Scaling or Torgerson Gower scaling. It takes an input matrix giving dissimilarities between pairs of items and outputs a coordinate matrix whose configuration minimizes a loss function called strain.