Interval-Valued Intuitionistic Fuzzy MABAC (Xue, You, Lai, Liu 2016)
IVIF-MABAC (Interval-Valued Intuitionistic Fuzzy MABAC (Xue, You, Lai, Liu 2016)) is a ranking multi-criteria decision-making (MCDM) method introduced by Atanassov, K. T., Gargov, G. in 1989. 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
IVIF-MABAC extends MABAC to handle Interval-Valued Intuitionistic Fuzzy uncertainty (Atanassov-Gargov 1989). All operations use IVIFN arithmetic (Xue 2016 Defs 1-8). Each alternative is compared to the Border Approximation Area (BAA, geometric mean across alternatives) per criterion via signed IVIF Euclidean distance — positive if above BAA (upper area G⁺, near ideal), negative if below (lower area G⁻, near anti-ideal). The closeness coefficient CC_i sums these signed distances; higher CC_i = better. Supports incomplete weight information via optimization model M-1 (Eq. 19) or M-2/Eq. 21 close
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.
- May exhibit rank reversal when alternatives are added to or removed from the set.
- Assumes full compensation — a strong score on one criterion can offset a weak score on another.
Common pitfalls
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Sources
- 1.Atanassov, K. T., Gargov, G. (1989). Interval valued intuitionistic fuzzy sets. Fuzzy Sets and Systems
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ScholarGate. (2026, June 2). IVIF-MABAC. ScholarGate. https://scholargate.app/decision-making/ivif-mabac