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最小-最大归一化×衡量备选方案并根据折衷解进行排序×
领域决策决策
方法族MCDMMCDM
起源年份19812020
提出者Hwang, C. L., Yoon, K.Stević, Ž., Pamučar, D., Puška, A., Chatterjee, P.
类型Normalization (linear, range-scaling)Utility function (ideal + anti-ideal reference)
开创性文献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 ↗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 ↗
别名
相关88
摘要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.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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ScholarGate方法对比: MIN-MAX-NORMALIZATION · MARCOS. 于 2026-06-17 检索自 https://scholargate.app/zh/compare