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| Méthode Z-Number Best-Worst× | Extension de TOPSIS aux Z-Nombres× | |
|---|---|---|
| Domaine | Prise de décision | Prise de décision |
| Famille | MCDM | MCDM |
| Année d'origine | 2018 | 2018 |
| Auteur d'origine≠ | Aboutorab, Saberi, Asadabadi, Hussain, Chang (UTS Sydney, Australia) | Gardashova, L. A. |
| Type≠ | Pairwise comparison weighting under Z-number uncertainty | Z-Number outranking/ranking — Z-Number (Z = (A, B): restriction A, reliability B; both fuzzy) |
| Source fondatrice≠ | Aboutorab, H., Saberi, M., Asadabadi, M.R., Hussain, O., Chang, E. (2018). ZBWM: The Z-number extension of Best Worst Method and its application for supplier development. Expert Systems with Applications DOI ↗ | Gardashova, L. A. (2018). Z-Number Based TOPSIS Method in Multi-Criteria Decision Making. Advances in Intelligent Systems and Computing DOI ↗ |
| Alias | — | — |
| Apparentées | 8 | 8 |
| Résumé≠ | Z-BWM (Z-Number Best-Worst Method) is a weighting multi-criteria decision-making (MCDM) method introduced by Aboutorab, Saberi, Asadabadi, Hussain, Chang (UTS Sydney, Australia) in 2018. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. | Z-TOPSIS (Z-Number extension of TOPSIS) is a ranking multi-criteria decision-making (MCDM) method introduced by Gardashova, L. A. in 2018. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. |
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