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Vektorska normalizacija×Procjena utemeljena na udaljenosti od prosječnog rješenja×
PodručjeDonošenje odlukaDonošenje odluka
ObiteljMCDMMCDM
Godina nastanka19812015
TvoracHwang, C. L., Yoon, K.Keshavarz Ghorabaee, M., Zavadskas, E. K., Olfat, L., Turskis, Z.
VrstaNormalization (L2, unit-sphere projection)Distance from average solution
Temeljni izvorHwang, 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 ↗
Drugi nazivi
Srodne48
SažetakNORM-VECTOR (Vector Normalization — Euclidean column-norm scaling (L2 normalisation)) 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.
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ScholarGateUsporedite metode: NORM-VECTOR · EDAS. Preuzeto 2026-06-15 s https://scholargate.app/hr/compare