Võrdle meetodeid
Vaata valitud meetodeid kõrvuti; erinevad read on esile tõstetud.
| Min-Max Normalization× | Hindamismeetod keskmisest lahendusest lähtuvate kauguste põhjal× | |
|---|---|---|
| Valdkond | Otsustamine | Otsustamine |
| Perekond | MCDM | MCDM |
| Tekkeaasta≠ | 1981 | 2015 |
| Looja≠ | Hwang, C. L., Yoon, K. | Keshavarz Ghorabaee, M., Zavadskas, E. K., Olfat, L., Turskis, Z. |
| Tüüp≠ | Normalization (linear, range-scaling) | Distance from average solution |
| Algallikas≠ | 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 ↗ |
| Rööpnimetused | — | — |
| Seotud | 8 | 8 |
| Kokkuvõte≠ | 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. |
| ScholarGateAndmestik ↗ |
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