MCDMDecision-makingAggregationMath steps
Heronian Mean (HM)
HERONIAN-MEAN (Heronian Mean (HM)) is a aggregation multi-criteria decision-making (MCDM) method introduced by Yu, D. in 2012. 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
Higher HM score indicates better aggregated performance. Geometrically averages pairwise interactions between criteria.
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
- Results depend on the chosen normalisation, weights, and parameter settings.
Sources
- 1.Yu, D. (2012). Intuitionistic fuzzy geometric Heronian mean aggregation operators. Applied Soft Computing
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Cite this page
ScholarGate. (2026, June 2). HERONIAN-MEAN. ScholarGate. https://scholargate.app/decision-making/heronian-mean