MCDMDecision-makingRankingMath steps
Multi-Attributive Border Approximation area Comparison
MABAC (Multi-Attributive Border Approximation area Comparison) is a ranking multi-criteria decision-making (MCDM) method introduced by Pamučar, D., Ćirović, G. in 2015. 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
S_i can be any real number. S_i > 0 means the alternative lies above the Border Approximation Area (BAA) — it is a good alternative for that criterion. S_i < 0 means below BAA — poor performance. Alternatives above BAA across all criteria are clearly best.
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.
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
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Cite this page
ScholarGate. (2026, June 2). MABAC. ScholarGate. https://scholargate.app/decision-making/mabac