विधियों की तुलना करें

	स्तरीकृत बेस्ट वर्स्ट विधि	AHP-BOCR	फजी बीडब्ल्यूएम
क्षेत्र	निर्णयन	निर्णयन	निर्णयन
परिवार	MCDM	MCDM	MCDM
उद्भव वर्ष	2015	2008	2015 crisp; 2017 variant applicator
प्रवर्तक	Jafar Rezaei and collaborators	Thomas L. Saaty (AHP); BOCR framework development extended AHP	Guo, S., Zhao, H.
प्रकार	Hierarchical pairwise comparison with layer-wise best-worst	Hierarchical pairwise comparison with strategic perspective	Triangular-fuzzy Best-to-Others and Others-to-Worst pairwise comparison with nonlinearly-constrained programming
मौलिक स्रोत	Rezaei, J. (2015). Best-worst multi-criteria decision-making method: Some properties and a linear model. Journal of Cleaner Production, 229, 976-985.	Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1(1), 83-98.	Guo, S., Zhao, H. (2017). Fuzzy best-worst multi-criteria decision-making method and its applications. Knowledge-Based Systems
उपनाम	Stratified BWM	AHP-BOCR, Strategic Criteria AHP	—
संबंधित	4	5	8
सारांश	Stratified BWM is an extension of the Best Worst Method that applies the BWM logic recursively across multiple hierarchical layers. Instead of weighting criteria at a single level, it identifies the best and worst criterion within each level of a hierarchy, then aggregates weights across levels. This enables more realistic modeling of complex decision problems with natural hierarchical structures.	AHP-BOCR is an extension of the Analytic Hierarchy Process that incorporates strategic perspectives through the BOCR framework: Benefits, Opportunities, Costs, and Risks. Instead of optimizing a single objective, AHP-BOCR decomposes decisions into four strategic dimensions and uses a formula (Benefits × Opportunities) / (Costs × Risks) to synthesize a strategic priority. This approach is particularly suited to long-term, complex decisions with multiple stakeholder perspectives.	FUZZY-BWM (Fuzzy BWM — Triangular Fuzzy Best-Worst Method) is a weight subjective multi-criteria decision-making (MCDM) method introduced by Guo, S., Zhao, H. in 2015 crisp; 2017 variant applicator. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.