方法对比

	SWARA II	最佳-最差法 (Best-Worst Method)	CRITIC-M
领域	决策	决策	决策
方法族	MCDM	MCDM	MCDM
起源年份	2010	2015	1995
提出者	Keršuliene, Zavadskas, and Turskis; extended by Zolfani et al.	Rezaei, J.	Based on Diakoulaki et al.'s CRITIC; modified variants developed later
类型	Expert-based stepwise weight derivation with ratio refinement	Pairwise comparison (best-to-others + others-to-worst vectors), LP	Objective weight derivation via correlation and variance
开创性文献	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.	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.
别名	SWARA II, SWARA 2	—	CRITIC-M, Modified CRITIC
相关	4	8	3
摘要	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.	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.