Ranking
EVAMIX: EVAluation of MIXed data
Voogd, H. · 1983
Overview
Mixed ordinal+cardinal pairwise dominance aggregation. Output typically utility (higher value = preferred).
Strengths
- •Method-specific: Mixed ordinal+cardinal pairwise dominance aggregation
Limitations
- •Assumes: Criteria preferences are independent (no synergistic interactions)
- •Assumes: Compensation is acceptable: high score on one criterion can offset low on another
- •Assumes: Decision matrix is complete (no missing values)
Method assistant
Grounded explanations: it explains the method, it does not compute.
Assumptions to verify
- •Criteria preferences are independent (no synergistic interactions)
- •Compensation is acceptable: high score on one criterion can offset low on another
- •Decision matrix is complete (no missing values)
When not to use
- •Criteria strongly correlated → consider DEMATEL/ANP for interdependence
- •Non-compensatory preferences → consider outranking (ELECTRE/PROMETHEE)
Edge cases
- •See F.steps and D.parameters for EVAMIX-specific edge handling. recommendation_metadata.assumptions_to_verify also lists boundary conditions.
Common pitfalls
- •Hatalı: 'EVAMIX bu varsayımı kontrol etmeden uygulamak'. Doğrusu: Criteria preferences are independent (no synergistic interactions)
- •Hatalı: 'EVAMIX bu varsayımı kontrol etmeden uygulamak'. Doğrusu: Compensation is acceptable: high score on one criterion can offset low on another
- •Hatalı: 'EVAMIX bu varsayımı kontrol etmeden uygulamak'. Doğrusu: Decision matrix is complete (no missing values)
- •Hatalı: EVAMIX'yi 'Criteria strongly correlated → consider DEMATEL/ANP for interdependence' durumunda kullanmak: recommendation_metadata.not_recommended_when alternatif öneriyor.
- •Hatalı: EVAMIX'yi 'Non-compensatory preferences → consider outranking (ELECTRE/PROMETHEE)' durumunda kullanmak: recommendation_metadata.not_recommended_when alternatif öneriyor.
Worked example
- 1.Adım 1 (F1): Step 1: For each ordered pair (A_i, A_k): compute ordinal dominance score OD_ik = Σ_{j∈ordinal} w_j · sign(x_ij − x_kj)·d_j and cardinal dominance score CD_ik = Σ_{j∈cardinal} w_j · (n_ij − n_kj) where n_ij is min-max normalised. Formül: OD_{ik} = \sum_{j \in \text{ordinal}}w_{j}\cdot\text{sign}((x_{ij}-x_{kj})\cdot d_{j});\quad CD_{ik} = \sum_{j \in \text{cardinal}}w_{j}\cdot(n_{ij}-n_{kj}) Anchor: Voogd 1983, p.222-225
- 2.Adım 2 (F2): Step 2: Compute overall dominance score D_ik = w_ord · OD_ik + w_card · CD_ik where w_ord = Σ_{j∈ordinal} w_j, w_card = Σ_{j∈cardinal} w_j. Net score S_i = Σ_k D_ik. Rank descending. Formül: D_{ik} = w_{\text{ord}}\cdot OD_{ik} + w_{\text{card}}\cdot CD_{ik};\quad S_{i} = \sum_{k \neq i}D_{ik} Anchor: Voogd 1983, p.225
Commonly paired with
- •AHP + EVAMIX (high)
- •BWM + EVAMIX (high)
- •ENTROPY + EVAMIX (high)
- •CRITIC + EVAMIX (high)
- •SWARA + EVAMIX (high)
How to cite
Voogd, H. (1983). Multicriteria Evaluation for Urban and Regional Planning. Pion, London. https://doi.org/10.1111/j.1435-5597.1984.tb00827.x