Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Divkārtējās normalizācijas balstīta daudzkārtējā agregācija× | Kritēriju korelācijas un standartnovirzes objektīvā svēršana× | |
|---|---|---|
| Nozare | Lēmumu pieņemšana | Lēmumu pieņemšana |
| Saime | MCDM | MCDM |
| Izcelsmes gads≠ | 2020 | 2010 |
| Autors≠ | Liao, H., Wu, X. | Wang, Y. M., Luo, Y. |
| Tips≠ | Dual-normalisation aggregation (linear + vector) | Correlation-penalised standard-deviation weighting |
| Pirmavots≠ | Liao, H., Wu, X. (2020). DNMA: A double normalization-based multiple aggregation method for multi-expert multi-criteria decision making. Omega DOI ↗ | Wang, Y. M., Luo, Y. (2010). Integration of correlations with standard deviations for determining attribute weights in multiple attribute decision making. Mathematical and Computer Modelling DOI ↗ |
| Citi nosaukumi | — | — |
| Saistītās | 8 | 8 |
| Kopsavilkums≠ | DNMA (Double Normalization-Based Multiple Aggregation) is a ranking multi-criteria decision-making (MCDM) method introduced by Liao, H., Wu, X. in 2020. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. | CCSD (Criteria Correlation and Standard Deviation objective weighting) is a weight objective multi-criteria decision-making (MCDM) method introduced by Wang, Y. M., Luo, Y. in 2010. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. |
| ScholarGateDatu kopa ↗ |
|
|