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CRITIC-M×Méthode basée sur les effets de suppression des critères×
DomainePrise de décisionPrise de décision
FamilleMCDMMCDM
Année d'origine19952021
Auteur d'origineBased on Diakoulaki et al.'s CRITIC; modified variants developed laterKeshavarz Ghorabaee, M., Amiri, M., Zavadskas, E. K., Antucheviciene, J., Turskis, Z.
TypeObjective weight derivation via correlation and varianceRemoval-effect objective weighting (logarithmic utility)
Source fondatriceDiakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: The CRITIC method. Computers & Operations Research, 22(7), 763-770. DOI ↗Keshavarz Ghorabaee, M., Amiri, M., Zavadskas, E. K., Antucheviciene, J., Turskis, Z. (2021). Determination of objective weights using a new method based on the removal effects of criteria (MEREC). Informatica DOI ↗
AliasCRITIC-M, Modified CRITIC
Apparentées38
RésuméCRITIC-M (Criteria Importance Through Intercriteria Correlation - Modified) is an objective weight derivation method that extends the classical CRITIC approach. It assigns weights to criteria based on two intrinsic properties of the decision matrix: variance (how much a criterion differentiates alternatives) and correlation (how much a criterion conflicts with or supplements others). Modified variants adjust the formulation to improve robustness or interpretability.MEREC (MEthod based on the Removal Effects of Criteria) is a weight objective multi-criteria decision-making (MCDM) method introduced by Keshavarz Ghorabaee, M., Amiri, M., Zavadskas, E. K., Antucheviciene, J., Turskis, Z. in 2021. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
ScholarGateJeu de données
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  1. v1
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  3. PUBLISHED

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ScholarGateComparer des méthodes: CRITIC-M · MEREC. Consulté le 2026-06-18 sur https://scholargate.app/fr/compare