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邻域自适应有序加权平均法×准则重要性通过准则间相关性 (CRITIC)×
领域决策决策
方法族MCDMMCDM
起源年份20141995
提出者Malczewski, J.; Liu, X.Diakoulaki, D., Mavrotas, G., Papayannakis, L.
类型Range-sensitive neighbourhood-local OWA — criterion weights w^q_k scale with local criterion variance within each spatial neighbourhood; order weights λ_k remain global, encoding a single risk attitude applied everywhereStatistical contrast intensity + correlation-based objective weighting
开创性文献Malczewski, J., Liu, X. (2014). Local ordered weighted averaging in GIS-based multicriteria analysis. Annals of GIS DOI ↗Diakoulaki, D., Mavrotas, G., Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: The CRITIC method. Computers & Operations Research DOI ↗
别名
相关88
摘要LOCAL-OWA (neighbourhood-adaptive Ordered Weighted Averaging) is a ranking multi-criteria decision-making (MCDM) method introduced by Malczewski, J.; Liu, X. in 2014. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.CRITIC (CRiteria Importance Through Intercriteria Correlation) is a weight objective multi-criteria decision-making (MCDM) method introduced by Diakoulaki, D., Mavrotas, G., Papayannakis, L. in 1995. 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: LOCAL-OWA · CRITIC. 于 2026-06-18 检索自 https://scholargate.app/zh/compare