Additive Ratio Assessment
ARAS (Additive Ratio Assessment) is a ranking multi-criteria decision-making (MCDM) method introduced by Zavadskas, E. K., Turskis, Z. in 2010. 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
K_i ∈ [0,1]. The optimal alternative receives K_0=1 (by definition S_0/S_0=1). All real alternatives have K_i ≤ 1 because S_0 ≥ S_i. Higher K_i means the alternative is proportionally closer to the optimal benchmark. Unlike COPRAS, ARAS uses a single additive score without splitting benefit/cost — it handles cost by inverting before normalisation.
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.Zavadskas, E. K., Turskis, Z. (2010). A new additive ratio assessment (ARAS) method in multicriteria decision-making. Technological and Economic Development of Economy
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ScholarGate. (2026, June 2). ARAS. ScholarGate. https://scholargate.app/decision-making/aras