BRAUERS-DOMINANCE - Brauers & Zavadskas (2014) Dominance Theory - used in MultiMOORA aggregation

Overview

Input: rank matrix (rows=alts, cols=rankings, cell=rank 1..m). Source: Orakçı 2024 §1.8.10.

Output

rank position, lower is better

Data

Crisp, complete rank

Size

2+ alternatives, 3-12 criteria works best

Used for

Rank aggregation, social choice, preference fusion

How it works

1. 1

   Pairwise Pareto dominance check across rankings. Score = times this alt strictly dominates − times strictly dominated.

   i dominates k iff r_ij ≤ r_kj ∀j AND r_ij < r_kj ∃j; score = #dominates − #dominated_by

   Orakçı 2024 §1.8.10

Fits when / Look elsewhere when

Assumptions to verify

• Input is a rank matrix (1=best, m=worst per voter)
• Each voter ranks all alternatives

Edge cases and pitfalls

• Applying BRAUERS-DOMINANCE without verifying this assumption.

  Requirement: Input is a rank matrix (1=best, m=worst per voter)

• Applying BRAUERS-DOMINANCE without verifying this assumption.

  Requirement: Each voter ranks all alternatives

• Using BRAUERS-DOMINANCE when: Cardinal preferences important → use a MAUT method.

  An alternative method is recommended in this situation.

How to cite