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Pesos objectius per correlació de criteris i desviació estàndard×Classificació Integral Basada en Distàncies×
CampPresa de decisionsPresa de decisions
FamíliaMCDMMCDM
Any d'origen20102022
Autor originalWang, Y. M., Luo, Y.Krstić, M., Agnusdei, G. P., Tadić, S., Kovač, M., Miglietta, P. P.
TipusCorrelation-penalised standard-deviation weightingDistance from PIS/NIS/AS (Euclidean × Taxicab combined)
Font seminalWang, 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 ↗Krstić, M., Agnusdei, G. P., Tadić, S., Kovač, M., Miglietta, P. P. (2022). A Novel Axiomatic DEA-COBRA Framework for Evaluating the Sustainable Performance of Agri-Food Systems. Sustainability link ↗
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ResumCCSD (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.COBRA (COmprehensive distance Based RAnking) is a ranking multi-criteria decision-making (MCDM) method introduced by Krstić, M., Agnusdei, G. P., Tadić, S., Kovač, M., Miglietta, P. P. in 2022. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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ScholarGateCompara mètodes: CCSD · COBRA. Recuperat el 2026-06-15 de https://scholargate.app/ca/compare