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Min-Max-Normalisierung×Messung von Alternativen und Rangfolge gemäß Kompromisslösung×
FachgebietEntscheidungsfindungEntscheidungsfindung
FamilieMCDMMCDM
Entstehungsjahr19812020
UrheberHwang, C. L., Yoon, K.Stević, Ž., Pamučar, D., Puška, A., Chatterjee, P.
TypNormalization (linear, range-scaling)Utility function (ideal + anti-ideal reference)
Wegweisende QuelleHwang, C. L., Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications. Lecture Notes in Economics and Mathematical Systems, Vol. 186, Springer-Verlag DOI ↗Stević, Ž., Pamučar, D., Puška, A., Chatterjee, P. (2020). Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS). Computers & Industrial Engineering DOI ↗
Aliasnamen
Verwandt88
ZusammenfassungMIN-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.MARCOS (Measurement of Alternatives and Ranking according to Compromise Solution) is a ranking multi-criteria decision-making (MCDM) method introduced by Stević, Ž., Pamučar, D., Puška, A., Chatterjee, P. in 2020. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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ScholarGateMethoden vergleichen: MIN-MAX-NORMALIZATION · MARCOS. Abgerufen am 2026-06-15 von https://scholargate.app/de/compare