Võrdle meetodeid

	CRITIC-M	Kriteeriumide tähtsus interkriteeriumite korrelatsiooni kaudu	MEREC-G
Valdkond	Otsustamine	Otsustamine	Otsustamine
Perekond	MCDM	MCDM	MCDM
Tekkeaasta	1995	1995	2021
Looja	Based on Diakoulaki et al.'s CRITIC; modified variants developed later	Diakoulaki, D., Mavrotas, G., Papayannakis, L.	Keshavarz Ghorabaee, Hosseinzadeh Lotfi et al.
Tüüp	Objective weight derivation via correlation and variance	Statistical contrast intensity + correlation-based objective weighting	Objective weight derivation via removal impact assessment
Algallikas	Diakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: The CRITIC method. Computers & Operations Research, 22(7), 763-770.	Diakoulaki, D., Mavrotas, G., Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: The CRITIC method. Computers & Operations Research	Keshavarz Ghorabaee, M., Hosseinzadeh Lotfi, F., Behzadi, M., & Sałabun, W. (2021). MEREC: A new multi-criteria model to evaluate wind farm locations. Sustainability, 12(15), 6136.
Rööpnimetused	CRITIC-M, Modified CRITIC	—	MEREC-G, Generalized MEREC
Seotud	3	8	3
Kokkuvõte	CRITIC-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.	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.	MEREC-G (Method Based on Removal Effects of Criteria - Generalized) is an objective weight derivation method that assigns weights based on the impact of removing each criterion from the decision analysis. The core idea is that important criteria, when removed, cause large changes in the final ranking. Generalized variants extend the original MEREC to various aggregation logic and decision contexts.