Alternative Ranking Order Method Accounting for Two-Step Normalisation
AROMAN (Alternative Ranking Order Method Accounting for Two-Step Normalisation) is a ranking multi-criteria decision-making (MCDM) method introduced by Zdravković, M., Hamid, M., Radovanović, M. in 2022. 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
Q_i > 0. Higher Q means better. AROMAN applies two-step normalisation (linear-max then vector) to reduce normalisation-method sensitivity, then aggregates with a power function. α=0.5 is the default; α→1 approaches weighted sum; α→0 approaches weighted product (geometric mean behaviour).
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.
- Assumes full compensation — a strong score on one criterion can offset a weak score on another.
Common pitfalls
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Sources
- 1.Zdravković, M., Hamid, M., Radovanović, M. (2022). AROMAN — Alternative Ranking Order Method Accounting for Two-Step Normalisation. Journal of Computational Design and Engineering
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Cite this page
ScholarGate. (2026, June 2). AROMAN. ScholarGate. https://scholargate.app/decision-making/aroman