Linear Sum Normalization — column-sum division (probability / stochastic normalisation)
LINEAR-SUM-NORMALIZATION (Linear Sum Normalization — column-sum division (probability / stochastic normalisation)) is a normalization multi-criteria decision-making (MCDM) method introduced by Zavadskas, E. K., Turskis, Z., Peldschus, F., Kaklauskas, A. in 1994. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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When to use it
Each column sums to 1 — r_ij can be interpreted as the fraction of total criterion performance captured by alternative i. Used in MOORA (ratio system) and ENTROPY weighting.
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., Peldschus, F., Kaklauskas, A. (1994). Competitive comparison of contractors' offers in construction. Technika, Vilnius link ↗
How to cite this page
ScholarGate. (2026, June 2). Linear Sum Normalization — column-sum division (probability / stochastic normalisation). ScholarGate. https://scholargate.app/en/decision-making/linear-sum-normalization
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