MCDMDecision-makingRankingMath steps
Simple Additive Weighting
SAW (Simple Additive Weighting) is a ranking multi-criteria decision-making (MCDM) method introduced by Fishburn, P. C. in 1967. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
Key highlights
- 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.
Intuition
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How it works
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When to use it
S_i ∈ [0,1] after linear-max normalisation (assuming all positive values). Higher S_i means better overall performance. SAW is fully compensatory — a very high value on one criterion can offset a low value on another.
Strengths & limitations
Strengths
- 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.
Limitations
- Assumes full compensation — a strong score on one criterion can offset a weak score on another.
Common pitfalls
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Sources
- 1.Fishburn, P. C. (1967). Additive utilities with incomplete product sets: Application to priorities and assignments. Operations Research
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Cite this page
ScholarGate. (2026, June 2). SAW. ScholarGate. https://scholargate.app/decision-making/saw