Multi-Attribute Utility Theory
MAUT (Multi-Attribute Utility Theory) is a ranking multi-criteria decision-making (MCDM) method introduced by Keeney, R. L., Raiffa, H. in 1976. 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
U(A_i) ∈ [0,1] with linear utility functions. Higher U means greater overall utility. MAUT requires that criteria satisfy preferential independence (stronger: additive independence) for the additive form to be valid. In practice, this is often assumed without formal verification. Non-linear utility functions (exponential, etc.) can be specified per criterion if the decision-maker's risk attitude warrants it.
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.Keeney, R. L., Raiffa, H. (1976). Decisions with Multiple Objectives: Preferences and Value Trade-offs. WileyISBN 978-0-521-43883-4
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Cite this page
ScholarGate. (2026, June 2). MAUT. ScholarGate. https://scholargate.app/decision-making/maut