A VIKOR and TOPSIS focused reanalysis of the MADM methods based on
  logarithmic normalization
  Decision and policy-makers in multi-criteria decision-making analysis take
into account some strategies in order to analyze outcomes and to finally make
an effective and more precise decision. Among those strategies, the
modification of the normalization process in the multiple-criteria
decision-making algorithm is still a question due to the confrontation of many
normalization tools. Normalization is the basic action in defining and solving
a MADM problem and a MADM model. Normalization is the first, also necessary,
step in solving, i.e. the application of a MADM method. It is a fact that the
selection of normalization methods has a direct effect on the results. One of
the latest normalization methods introduced is the Logarithmic Normalization
(LN) method. This new method has a distinguished advantage, reflecting in that
a sum of the normalized values of criteria always equals 1. This normalization
method had never been applied in any MADM methods before. This research study
is focused on the analysis of the classical MADM methods based on logarithmic
normalization. VIKOR and TOPSIS, as the two famous MADM methods, were selected
for this reanalysis research study. Two numerical examples were checked in both
methods, based on both the classical and the novel ways based on the LN. The
results indicate that there are differences between the two approaches.
Eventually, a sensitivity analysis is also designed to illustrate the
reliability of the final results.
