Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Min-Max Normalization× | Novērtēšana, balstoties uz atšķirību no vidējā risinājuma× | |
|---|---|---|
| Nozare | Lēmumu pieņemšana | Lēmumu pieņemšana |
| Saime | MCDM | MCDM |
| Izcelsmes gads≠ | 1981 | 2015 |
| Autors≠ | Hwang, C. L., Yoon, K. | Keshavarz Ghorabaee, M., Zavadskas, E. K., Olfat, L., Turskis, Z. |
| Tips≠ | Normalization (linear, range-scaling) | Distance from average solution |
| Pirmavots≠ | Hwang, C. L., Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications. Lecture Notes in Economics and Mathematical Systems, Vol. 186, Springer-Verlag DOI ↗ | Keshavarz Ghorabaee, M., Zavadskas, E. K., Olfat, L., Turskis, Z. (2015). Multi-criteria inventory classification using a new method of evaluation based on distance from average solution (EDAS). Informatica DOI ↗ |
| Citi nosaukumi | — | — |
| Saistītās | 8 | 8 |
| Kopsavilkums≠ | MIN-MAX-NORMALIZATION (Min-Max Normalization — linear rescaling of each criterion column to [0, 1]) is a normalization multi-criteria decision-making (MCDM) method introduced by Hwang, C. L., Yoon, K. in 1981. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. | EDAS (Evaluation Based on Distance from Average Solution) is a ranking multi-criteria decision-making (MCDM) method introduced by Keshavarz Ghorabaee, M., Zavadskas, E. K., Olfat, L., Turskis, Z. in 2015. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. |
| ScholarGateDatu kopa ↗ |
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