Reproduce “A VIKOR and TOPSIS focused reanalysis of the MADM methods based on logarithmic normalization” on OpenResearch
Turn your favorite coding agents into research agents that review literature, develop hypotheses, and run experiments.
Universal app for Apple silicon and Intel. Requires macOS 11 or later.
About this paper
Sarfaraz Zolfani, Morteza Yazdani, Dragan Pamucar, Pascale Zaraté
An international research team systematically analyzed the effect of logarithmic normalization on VIKOR and TOPSIS Multi-Attribute Decision Making methods, finding that this approach enhances ranking stability, especially for VIKOR, under changing criteria weights and dynamic decision matrices.
Key insights
- Logarithmic normalization can alter the rankings produced by VIKOR and TOPSIS, with the extent of influence varying based on the specific problem and MADM method used.
- LN-based methods, particularly VIKOR, exhibit superior ranking stability when criteria weights are modified or when the set of alternatives in the decision matrix changes.
- The choice of normalization technique is critical and should be a deliberate decision based on the characteristics of the decision problem, rather than a default application of conventional methods.
Summary by alphaXiv.
Tip: change arxiv.org to autoarxiv.org in any arXiv abstract link to open the paper here.