MCDMDecision-makingRankingMath steps
Intuitionistic extension of MABAC
IF-MABAC (Intuitionistic extension of MABAC) is a ranking multi-criteria decision-making (MCDM) method introduced by Li, Y. in 2021. 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
if-mabac extends MABAC to handle Intuitionistic uncertainty. All arithmetic operations (normalisation, weighting, distance computation) are performed using Intuitionistic Fuzzy Number (IFN: μ, ν; μ+ν ≤ 1) algebra. The final scores are defuzzified via score function S = μ − ν before ranking.
Strengths & limitations
Strengths
- 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.
Limitations
- 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.Pamučar, D., & Ćirović, G. (2015). The selection of transport and handling resources in logistics centers using Multi-Attributive Border Approximation area Comparison (MABAC). Expert Systems with Applications, 42(6), 3016-3028. [Canonical MABAC source; cited in place of the retracted Li (2021) intuitionistic-fuzzy MABAC paper, doi:10.1155/2021/5536751.]
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Cite this page
ScholarGate. (2026, June 2). IF-MABAC. ScholarGate. https://scholargate.app/decision-making/if-mabac