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HF-TOPSIS×Corrélation des critères et écart-type pour la pondération objective×
DomainePrise de décisionPrise de décision
FamilleMCDMMCDM
Année d'origine20132010
Auteur d'origineXu, Z., Zhang, X.Wang, Y. M., Luo, Y.
TypeDistance-to-ideal ranking (Hwang-Yoon 1981) extended to Hesitant Fuzzy Elements (HFE ⊂ [0,1]) via the hesitant normalised Euclidean distance d_1 (Xu-Xia 2011b); supports three weight-information modes: fully specified, completely unknown (Eq.(22) maximizing deviation closed-form), and partly known (Model M-2 linear programme).Correlation-penalised standard-deviation weighting
Source fondatriceXu, Z., Zhang, X. (2013). Hesitant fuzzy multi-attribute decision making based on TOPSIS with incomplete weight information. Knowledge-Based Systems DOI ↗Wang, Y. M., Luo, Y. (2010). Integration of correlations with standard deviations for determining attribute weights in multiple attribute decision making. Mathematical and Computer Modelling DOI ↗
Alias
Apparentées88
RésuméHF-TOPSIS (Hesitant Fuzzy TOPSIS with optional incomplete weight information (Xu-Zhang 2013 KBS)) is a ranking multi-criteria decision-making (MCDM) method introduced by Xu, Z., Zhang, X. in 2013. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.CCSD (Criteria Correlation and Standard Deviation objective weighting) is a weight objective multi-criteria decision-making (MCDM) method introduced by Wang, Y. M., Luo, Y. in 2010. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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ScholarGateComparer des méthodes: HF-TOPSIS · CCSD. Consulté le 2026-06-18 sur https://scholargate.app/fr/compare