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Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.

Cubic-EDAS×Ponderação objetiva por correlação de critérios e desvio padrão (CCSD)×
ÁreaTomada de decisãoTomada de decisão
FamíliaMCDMMCDM
Ano de origem20232010
Autor originalPaul, T.K., Jana, C., Pal, M.Wang, Y. M., Luo, Y.
TipoCubic Pythagorean Fuzzy ranking — CuPyFN = ⟨IvPyFN, PyFN⟩ = (⟨[Y⁻,Y⁺],[F⁻,F⁺]⟩,⟨Y,F⟩); Pythagorean constraint (Y⁺)²+(F⁺)² ≤ 1; average-solution EDAS with score-function PDA/NDACorrelation-penalised standard-deviation weighting
Fonte seminalPaul, T.K., Jana, C., Pal, M. (2023). Multi-criteria group decision-making method in disposal of municipal solid waste based on cubic Pythagorean fuzzy EDAS approach with incomplete weight information. Applied Soft Computing 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 ↗
Outros nomes
Relacionados88
ResumoCUBIC-EDAS (Cubic-EDAS — Cubic Pythagorean Fuzzy EDAS (CuP-EDAS)) is a ranking multi-criteria decision-making (MCDM) method introduced by Paul, T.K., Jana, C., Pal, M. in 2023. 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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ScholarGateComparar métodos: CUBIC-EDAS · CCSD. Recuperado em 2026-06-17 de https://scholargate.app/pt/compare