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Normalisasi Vektor×Penilaian Berdasarkan Jarak dari Penyelesaian Purata×
BidangPembuatan KeputusanPembuatan Keputusan
KeluargaMCDMMCDM
Tahun asal19812015
PengasasHwang, C. L., Yoon, K.Keshavarz Ghorabaee, M., Zavadskas, E. K., Olfat, L., Turskis, Z.
JenisNormalization (L2, unit-sphere projection)Distance from average solution
Sumber perintisHwang, 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 ↗
Alias
Berkaitan48
RingkasanNORM-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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ScholarGateBandingkan kaedah: NORM-VECTOR · EDAS. Dicapai 2026-06-15 daripada https://scholargate.app/ms/compare