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Min-Max Normalization — lineær skalering af hver kriteriekolonne til [0, 1]

MIN-MAX-NORMALIZATION (Min-Max Normalization — lineær skalering af hver kriteriekolonne til [0, 1]) er en normaliseringsmetode inden for multi-kriterie beslutningstagning (MCDM - multi-criteria decision-making), introduceret af Hwang, C. L., Yoon, K. i 1981. Den omdanner en beslutningsmatrix af alternativer, vurderet på tværs af flere kriterier, til et struktureret, reproducerbart resultat.

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Kilder

  1. 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: 10.1007/978-3-642-48318-9

Sådan citerer du denne side

ScholarGate. (2026, June 2). Min-Max Normalization — linear rescaling of each criterion column to [0, 1]. ScholarGate. https://scholargate.app/da/decision-making/min-max-normalization

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ScholarGateMIN-MAX-NORMALIZATION (Min-Max Normalization — linear rescaling of each criterion column to [0, 1]). Hentet 2026-06-15 fra https://scholargate.app/da/decision-making/min-max-normalization · Datasæt: https://doi.org/10.5281/zenodo.20539026