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Home›Decision-making›Kemeny-Young — Optimal rank aggregation minimising Kendall τ disagreement
MCDMAggregationOperatorcrisp

Kemeny-Young — Optimal rank aggregation minimising Kendall τ disagreement

KEMENY-YOUNG (Kemeny-Young — Optimal rank aggregation minimising Kendall τ disagreement) is a aggregationoperator multi-criteria decision-making (MCDM) method introduced by Kemeny, J. G. in 1959. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

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  3. 1 Sources
  4. PUBLISHED
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When to use it

Kemeny-Young finds the ranking σ* minimising total Kendall τ distance from all individual rankings (equivalently maximising the Kemeny score). It always elects the Condorcet winner if one exists. Computing the exact solution is NP-hard for large m — use branch-and-bound or genetic algorithm heuristics for m > 8.

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
  • Results depend on the chosen normalisation, weights, and parameter settings.

Sources

  1. Kemeny, J. G. (1959). Mathematics without numbers. Daedalus link ↗

How to cite this page

ScholarGate. (2026, June 2). Kemeny-Young — Optimal rank aggregation minimising Kendall τ disagreement. ScholarGate. https://scholargate.app/en/decision-making/kemeny-young

Similar methods

CONDORCETWEIGHTED-VOTINGBORDACOPELANDKEMIRASCHULZEDODGSONCOMPROMISE-PROGRAMMING

Related reference concepts

Multidimensional ScalingDecision MakingK-Means ClusteringDecision Support SystemsAnalysis of Collective Decision-MakingApproximation Algorithms

Spotted an issue on this page? Report or suggest a fix →

ScholarGate — KEMENY-YOUNG (Kemeny-Young — Optimal rank aggregation minimising Kendall τ disagreement). Retrieved 2026-07-21 from https://scholargate.app/en/decision-making/kemeny-young · Dataset: https://doi.org/10.5281/zenodo.20539026
Quick facts
Originator
Kemeny, J. G.
Subfamily
AggregationOperator
Year
1959
Type
Rank aggregation (Kemeny consensus, NP-hard optimisation)
Value Space
crisp
Uncertainty
None
Compensation
N/A
Rank Reversal
No
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