SMAA-2 — Stochastic extension of SMAA2
SMAA2 (SMAA-2 — Stochastic extension of SMAA2) is a ranking multi-criteria decision-making (MCDM) method introduced by Lahdelma, R. & Salminen, P. in 2001. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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When to use it
SMAA-2 (Lahdelma & Salminen 2001) extends base SMAA by computing the full rank acceptability index matrix b_i^r for all ranks r=1..m (not only rank 1) and aggregating into a holistic acceptability a_i^h = Σ_r α^r b_i^r (Eq.18) via monotone metaweights α^1 ≥ ... ≥ α^m ≥ 0, α^1=1. Monte Carlo samples (x^{(k)}, w^{(k)}) drawn from f_X and uniform W; per-sample additive utility (Eq.11) → rankings → b_i^r → a_i^h. Final ranking by a_i^h descending. No defuzzification — SMAA-2 is probabilistic, not fuzzy.
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.
Sources
- Lahdelma & Salminen (2001). Stochastic Multicriteria Acceptability Analysis 2. Operations Research link ↗
How to cite this page
ScholarGate. (2026, June 2). SMAA-2 — Stochastic extension of SMAA2. ScholarGate. https://scholargate.app/en/decision-making/smaa2