Stochastic UTilités Additives (preference-disaggregation under uncertainty)
STOCHASTIC-UTA (Stochastic UTilités Additives (preference-disaggregation under uncertainty)) is a ranking multi-criteria decision-making (MCDM) method introduced by Stavrou, D. I.; Ventikos, N. P.; Tsoukalas, V. D. (2018) — STOCHASTIC-UTA seminal chapter Jacquet-Lagrèze, E.; Siskos, J. (1982) — classical UTA foundation Siskos, Y. (1980) — preference disaggregation theory in 1982 — stochastic extension Stavrou-Ventikos-Tsoukalas 2018 Springer. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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When to use it
STOCHASTIC-UTA fits additive utility functions to a DM-supplied reference ranking via LP, then samples uncertain inputs N times (Monte Carlo) to derive acceptability indices. In deterministic mode (N=1), the score is the global utility u(A_i); in stochastic mode it is the holistic acceptability a_i.
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
- Stavrou, D. I., Ventikos, N. P., Tsoukalas, V. D. (2018). Robust Evaluation of Risks in Ship-to-Ship Transfer Operations: Application of the STOCHASTIC UTA Multicriteria Decision Support Method. In Lee, P. T. W. & Yang, Z. (Eds.), Multi-criteria Decision Making in Maritime Studies and Logistics (pp. 161–185). Springer. DOI: 10.1007/978-3-319-62338-2_8 ↗
How to cite this page
ScholarGate. (2026, June 2). Stochastic UTilités Additives (preference-disaggregation under uncertainty). ScholarGate. https://scholargate.app/en/decision-making/stochastic-uta
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