MCDMDecision-makingDistanceMath steps
Mahalanobis Distance — covariance-adjusted distance accounting for inter-criterion correlations
MAHALANOBIS-DISTANCE (Mahalanobis Distance — covariance-adjusted distance accounting for inter-criterion correlations) is a distance multi-criteria decision-making (MCDM) method introduced by Mahalanobis, P. C. in 1936. 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
d ≥ 0; d=0 iff a=b. Mahalanobis Distance is symmetric.
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.
Common pitfalls
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Sources
- 1.Mahalanobis, P. C. (1936). Mahalanobis Distance. Proceedings of the National Institute of Sciences of India
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Cite this page
ScholarGate. (2026, June 2). MAHALANOBIS-DISTANCE. ScholarGate. https://scholargate.app/decision-making/mahalanobis-distance