Krahasoni metodat

	Metoda Miri-Maksi (Best-Worst Method)	CRITIC-M	MEREC-G
Fusha	Vendimmarrja	Vendimmarrja	Vendimmarrja
Familja	MCDM	MCDM	MCDM
Viti i origjinës	2015	1995	2021
Krijuesi	Rezaei, J.	Based on Diakoulaki et al.'s CRITIC; modified variants developed later	Keshavarz Ghorabaee, Hosseinzadeh Lotfi et al.
Lloji	Pairwise comparison (best-to-others + others-to-worst vectors), LP	Objective weight derivation via correlation and variance	Objective weight derivation via removal impact assessment
Burimi themelues	Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega	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.
Emërtime të tjera	—	CRITIC-M, Modified CRITIC	MEREC-G, Generalized MEREC
Të lidhura	8	3	3
Përmbledhja	BWM (Best-Worst Method) is a weight subjective multi-criteria decision-making (MCDM) method introduced by Rezaei, J. in 2015. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.	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.