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线性最大值归一化×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19672020
提出者Fishburn, P. C.Stević, Ž., Pamučar, D., Puška, A., Chatterjee, P.
类型Normalization (linear-max, ratio-based)Utility function (ideal + anti-ideal reference)
开创性文献Fishburn, P. C. (1967). Additive Utilities with Incomplete Product Sets: Application to Priorities and Assignments. Operations Research 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48
摘要LINEAR-MAX-NORMALIZATION (Linear Max Normalization — division by column maximum (benefit) or column minimum over value (cost)) is a normalization multi-criteria decision-making (MCDM) method introduced by Fishburn, P. C. in 1967. 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: LINEAR-MAX-NORMALIZATION · MARCOS. 于 2026-06-15 检索自 https://scholargate.app/zh/compare