Usporedite metode

	SWARA II	Metoda Best-Worst	MEREC-G
Područje	Donošenje odluka	Donošenje odluka	Donošenje odluka
Obitelj	MCDM	MCDM	MCDM
Godina nastanka	2010	2015	2021
Tvorac	Keršuliene, Zavadskas, and Turskis; extended by Zolfani et al.	Rezaei, J.	Keshavarz Ghorabaee, Hosseinzadeh Lotfi et al.
Vrsta	Expert-based stepwise weight derivation with ratio refinement	Pairwise comparison (best-to-others + others-to-worst vectors), LP	Objective weight derivation via removal impact assessment
Temeljni izvor	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	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.
Drugi nazivi	SWARA II, SWARA 2	—	MEREC-G, Generalized MEREC
Srodne	4	8	3
Sažetak	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.	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.