Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Rough-MARCOS× | Kritēriju korelācijas un standartnovirzes objektīvā svēršana× | |
|---|---|---|
| Nozare | Lēmumu pieņemšana | Lēmumu pieņemšana |
| Saime | MCDM | MCDM |
| Izcelsmes gads≠ | 2022 | 2010 |
| Autors≠ | Matić, B. Marinković, M. Jovanović, S. Sremac, S. Stević, Ž. | Wang, Y. M., Luo, Y. |
| Tips≠ | Rough outranking/ranking — Rough number (lower approximation L, upper approximation U) | Correlation-penalised standard-deviation weighting |
| Pirmavots≠ | Matić, B., Marinković, M., Jovanović, S., Sremac, S., Stević, Ž. (2022). Intelligent Novel IMF D-SWARA—Rough MARCOS Algorithm for Selection Construction Machinery for Sustainable Construction of Road Infrastructure. Buildings 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≠ | ROUGH-MARCOS (Rough-MARCOS — Rough extension of MARCOS) is a ranking multi-criteria decision-making (MCDM) method introduced by Matić, B. Marinković, M. Jovanović, S. Sremac, S. Stević, Ž. in 2022. 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. |
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