Porównaj metody

	CRITIC-M	MEREC-G	SWARA II
Dziedzina	Podejmowanie decyzji	Podejmowanie decyzji	Podejmowanie decyzji
Rodzina	MCDM	MCDM	MCDM
Rok powstania	1995	2021	2010
Twórca	Based on Diakoulaki et al.'s CRITIC; modified variants developed later	Keshavarz Ghorabaee, Hosseinzadeh Lotfi et al.	Keršuliene, Zavadskas, and Turskis; extended by Zolfani et al.
Typ	Objective weight derivation via correlation and variance	Objective weight derivation via removal impact assessment	Expert-based stepwise weight derivation with ratio refinement
Źródło pierwotne	Diakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: The CRITIC method. Computers & Operations Research, 22(7), 763-770.	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.	Keršuliene, V., Zavadskas, E. K., & Turskis, Z. (2010). Selection of rational dispute resolution method by evaluating opposing parties' interest in civil litigation. Journal of Civil Engineering and Management, 16(3), 412-422.
Inne nazwy	CRITIC-M, Modified CRITIC	MEREC-G, Generalized MEREC	SWARA II, SWARA 2
Pokrewne	3	3	4
Podsumowanie	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.	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.	SWARA II (Step-wise Weight Assessment Ratio Analysis - Improved) is an enhanced variant of the SWARA method for deriving criterion weights from expert assessments. Instead of requiring pairwise comparisons or absolute weight assignments, SWARA II asks experts to rank criteria, then assess the relative importance of each criterion compared to the next-ranked one. Improved variants enhance robustness and interpretability of weight derivation.