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Normalisation Min-Max×Technique pour le classement par similarité à la solution idéale×
DomainePrise de décisionPrise de décision
FamilleMCDMMCDM
Année d'origine19811981
Auteur d'origineHwang, C. L., Yoon, K.Hwang, C. L., Yoon, K.
TypeNormalization (linear, range-scaling)Distance-based (compromise)
Source fondatriceHwang, C. L., Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications. Lecture Notes in Economics and Mathematical Systems, Vol. 186, Springer-Verlag DOI ↗Hwang, C. L., Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications — A State-of-the-Art Survey. Lecture Notes in Economics and Mathematical Systems, Vol. 186, Springer-Verlag DOI ↗
Alias
Apparentées88
RésuméMIN-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.TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) is a ranking 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.
ScholarGateJeu de données
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  2. 1 Sources
  3. PUBLISHED
  1. v1
  2. 1 Sources
  3. PUBLISHED

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ScholarGateComparer des méthodes: MIN-MAX-NORMALIZATION · TOPSIS. Consulté le 2026-06-17 sur https://scholargate.app/fr/compare