Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Pondération par ACP× | Évaluation combinatoire basée sur la distance× | |
|---|---|---|
| Domaine | Prise de décision | Prise de décision |
| Famille | MCDM | MCDM |
| Année d'origine≠ | 1901 | 2016 |
| Auteur d'origine≠ | Pearson, K. | Keshavarz Ghorabaee, M., Zavadskas, E. K., Turskis, Z., Antucheviciene, J. |
| Type≠ | Weight_Objective (PCA variance explained, eigenvector-based) | Distance from anti-ideal (Euclidean + Taxicab) |
| Source fondatrice≠ | Pearson, K. (1901). On lines and planes of closest fit to systems of points in space. Philosophical Magazine DOI ↗ | Keshavarz Ghorabaee, M., Zavadskas, E. K., Turskis, Z., Antucheviciene, J. (2016). A new combinative distance-based assessment (CODAS) method for multi-criteria decision-making. Economic Computation and Economic Cybernetics Studies and Research link ↗ |
| Alias | — | — |
| Apparentées | 8 | 8 |
| Résumé≠ | PCA-WEIGHT (PCA Weighting — Principal Component Analysis based objective weighting) is a weight objective multi-criteria decision-making (MCDM) method introduced by Pearson, K. in 1901. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. | CODAS (Combinative Distance-Based Assessment) is a ranking multi-criteria decision-making (MCDM) method introduced by Keshavarz Ghorabaee, M., Zavadskas, E. K., Turskis, Z., Antucheviciene, J. in 2016. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. |
| ScholarGateJeu de données ↗ |
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