Intuitionistic Fuzzy Multi-Attribute Utility Theory (IFWA-based additive utility)
IF-MAUT (Intuitionistic Fuzzy Multi-Attribute Utility Theory (IFWA-based additive utility)) is a ranking multi-criteria decision-making (MCDM) method introduced by Atanassov, K. T. in 1986. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
Read the full method
Sign in with a free account to read this section.
Method map
The neighbourhood of related methods — select a node to explore.
When to use it
IF-MAUT extends additive utility theory to the IF setting via the Xu 2007 IFWA aggregation operator. Each alternative's row of IFN ratings is aggregated into a single utility IFN U_i, then defuzzified by the Chen-Tan score S(U_i) = μ − ν for ranking. Cost criteria are complemented at Step F2 via (μ, ν) → (ν, μ). On ties, Hong-Choi accuracy H = μ + ν breaks them.
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
- Atanassov, K. T. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems DOI: 10.1016/S0165-0114(86)80034-3 ↗
How to cite this page
ScholarGate. (2026, June 2). Intuitionistic Fuzzy Multi-Attribute Utility Theory (IFWA-based additive utility). ScholarGate. https://scholargate.app/en/decision-making/if-maut
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- AHPDecision-making↔ compare
- ANPDecision-making↔ compare
- BWMDecision-making↔ compare
- BWM-BAYESIANDecision-making↔ compare
- CCSDDecision-making↔ compare
- CILOSDecision-making↔ compare
- CIMASDecision-making↔ compare
- CRITICDecision-making↔ compare