UTilités Additives (Additive Utility Assessment)
UTA (UTilités Additives (Additive Utility Assessment)) is a ranking multi-criteria decision-making (MCDM) method introduced by Jacquet-Lagrèze, E., Siskos, J. in 1982. 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
UTA infers an additive utility function u(g) = Σ_i u_i(g_i) from the decision-maker's holistic weak order on a reference set A′, by minimising the sum of single errors F = Σ_{a∈A′} σ(a) (Eq.(15)). u_i are piecewise-linear on α_i breakpoints (paper p.154). Post-optimality (Eqs.(16)–(19)) explores the polyhedron F ≤ F* + k(F*) via 2n LPs (min/max u_i(g_i^*)) to give a mean utility ū(g) and implicit-weight intervals. If F* > 0 the reference ranking is inconsistent with additive utility; if persistent infeasibility arises in monotonicity, consider UTASTAR (Siskos & Yannacopoulos 1985, double-error
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.Jacquet-Lagrèze, E., Siskos, J. (1982). Assessing a set of additive utility functions for multicriteria decision-making, the UTA method. European Journal of Operational Research
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ScholarGate. (2026, June 2). UTA. ScholarGate. https://scholargate.app/decision-making/uta