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| Z-Number Preference Ranking Organization Method (II)× | Z-Number Best-Worst Method× | |
|---|---|---|
| Fachgebiet | Entscheidungsfindung | Entscheidungsfindung |
| Familie | MCDM | MCDM |
| Entstehungsjahr≠ | 2020 | 2018 |
| Urheber≠ | Mahammad Nuriyev (Khazar University, Baku, Azerbaijan); builds on Brans-Vincke 1985 PROMETHEE | Aboutorab, Saberi, Asadabadi, Hussain, Chang (UTS Sydney, Australia) |
| Typ≠ | Outranking method with Z-number uncertainty (PROMETHEE II — full ranking) | Pairwise comparison weighting under Z-number uncertainty |
| Wegweisende Quelle≠ | Nuriyev, M. (2020). Z-numbers Based Hybrid MCDM Approach for Energy Resources Ranking and Selection. International Journal of Energy Economics and Policy DOI ↗ | 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 ↗ |
| Aliasnamen | — | — |
| Verwandt | 8 | 8 |
| Zusammenfassung≠ | Z-PROMETHEE (Z-Number Preference Ranking Organization Method (II)) is a ranking multi-criteria decision-making (MCDM) method introduced by Mahammad Nuriyev (Khazar University, Baku, Azerbaijan); builds on Brans-Vincke 1985 PROMETHEE in 2020. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. | 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. |
| ScholarGateDatensatz ↗ |
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