MCDMNormalizationcrisp

Min-Max Normalization — linear rescaling of each criterion column to [0, 1]

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.

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Sources

  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

Related methods

ScholarGateMIN-MAX-NORMALIZATION (Min-Max Normalization — linear rescaling of each criterion column to [0, 1]). Retrieved 2026-06-04 from https://scholargate.app/tr/decision-making/min-max-normalization