Ranking
Rank Reversal Analysis: Detection of ranking instability when alternatives are added/removed
Triantaphyllou, E. · 2000
Overview
Robustness diagnostic: rank reversal detection and quantification. Output typically robustness_score (higher value = preferred).
Strengths
- •Method-specific: Robustness diagnostic: rank reversal detection and quantification
Limitations
- •Assumes: A base ranking method is selected
- •Assumes: Computational budget for repeated runs
Method assistant
Grounded explanations: it explains the method, it does not compute.
Assumptions to verify
- •A base ranking method is selected
- •Computational budget for repeated runs
When not to use
- •Quick analysis needed → defer robustness check
Edge cases
- •See F.steps and D.parameters for RANK-REVERSAL-specific edge handling. recommendation_metadata.assumptions_to_verify also lists boundary conditions.
Common pitfalls
- •Hatalı: 'RANK-REVERSAL bu varsayımı kontrol etmeden uygulamak'. Doğrusu: A base ranking method is selected
- •Hatalı: 'RANK-REVERSAL bu varsayımı kontrol etmeden uygulamak'. Doğrusu: Computational budget for repeated runs
- •Hatalı: RANK-REVERSAL'yi 'Quick analysis needed → defer robustness check' durumunda kullanmak: recommendation_metadata.not_recommended_when alternatif öneriyor.
Worked example
- 1.Adım 1 (F1): Validate inputs for rank-reversal. Formül: \text{RR ratio}=\frac{\text{# reversals across perturbations}}{\text{# perturbations}\cdot\binom{m}{2}} Anchor: Triantaphyllou 2000, (pending PDF page verification)
How to cite
Triantaphyllou, E. (2000). Multi-Criteria Decision Making Methods: A Comparative Study. Kluwer Academic Publishers, Dordrecht. https://doi.org/10.1007/978-1-4757-3157-6_2