Comparar métodos

	Método Best-Worst	CRITIC-M	Análise da Razão de Avaliação de Pesos Passo a Passo
Área	Tomada de decisão	Tomada de decisão	Tomada de decisão
Família	MCDM	MCDM	MCDM
Ano de origem	2015	1995	2010
Autor original	Rezaei, J.	Based on Diakoulaki et al.'s CRITIC; modified variants developed later	Keršulienė, V., Zavadskas, E. K., Turskis, Z.
Tipo	Pairwise comparison (best-to-others + others-to-worst vectors), LP	Objective weight derivation via correlation and variance	Sequential step-ratio subjective weighting
Fonte seminal	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.	Keršulienė, V., Zavadskas, E. K., Turskis, Z. (2010). Selection of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (SWARA). Journal of Business Economics and Management
Outros nomes	—	CRITIC-M, Modified CRITIC	—
Relacionados	8	3	8
Resumo	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.	SWARA (Step-Wise Weight Assessment Ratio Analysis) is a weight subjective multi-criteria decision-making (MCDM) method introduced by Keršulienė, V., Zavadskas, E. K., Turskis, Z. in 2010. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.