MABAC
Updated 2026-08-11
INTRODUCTION
English translation pending.
CORE DEFINITION
Multi-Attributive Border Approximation Area Comparison (MABAC) evaluates alternatives by their distance from a border approximation area. The procedure normalizes the decision matrix, defines the border approximation area for each criterion, typically from the geometric mean of the alternatives' values on that criterion, and computes each alternative's weighted distance from that border. Distances above the border indicate an alternative better than the benchmark on that criterion, and distances below indicate worse. The distances are summed into a final score and the alternatives ranked. The border is computed from the alternatives being compared, so the ranking is relative.
SCAFFOLDING EFFECT
Reduce cognitive load
- Use border construction: compute the border approximation area from the criteria values before scoring anything. - Use signed distance: record whether each alternative sits above or below the border on each criterion. - Use weighted total: sum the weighted distances and rank, rather than comparing criteria one at a time.
Anchor fast decisions
Comparing alternatives criterion by criterion produces no overall ordering, and aggregating without a reference point makes scores hard to interpret. Defining a border from the criteria values supplies that reference, and the signed distance from it has a direct reading: above the border means better than the group on that criterion. Weighting the distances before summation lets the criteria that matter more influence the ranking more, and the total accumulates each alternative's advantages and disadvantages. The border moves when the alternative set changes, so results are relative.
MINIMUM ACTION
In progress 0/1Practice this model in one real situation:
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Source support: Explicit
- doi.orghttps://doi.org/10.1016/j.eswa.2014.11.057verified
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