Logarithmic Normalization — log-ratio column normalisation for multiplicative aggregation contexts
LOGARITHMIC-NORMALIZATION (Logarithmic Normalization — log-ratio column normalisation for multiplicative aggregation contexts) is a normalization multi-criteria decision-making (MCDM) method introduced by Zavadskas, E. K., Turskis, Z. in 2008. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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When to use it
Logarithmic normalisation is suitable when performance values span several orders of magnitude (multiplicative structure). Each benefit column sums to 1. Requires all x_ij > 0.
Strengths & limitations
- Follows a transparent, reproducible computational procedure that can be audited step by step.
- Handles multiple criteria of differing scales and units within a single decision matrix.
- Results depend on the chosen normalisation, weights, and parameter settings.
Sources
- Zavadskas, E. K., Turskis, Z. (2008). A new logarithmic normalization method in games theory. Informatica DOI: 10.15388/informatica.2008.215 ↗
How to cite this page
ScholarGate. (2026, June 2). Logarithmic Normalization — log-ratio column normalisation for multiplicative aggregation contexts. ScholarGate. https://scholargate.app/en/decision-making/logarithmic-normalization
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
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