Võrdle meetodeid

	Rough-EDAS	Analytic Hierarchy Process	Parim-Halvim Meetod	Bayesi BWM
Valdkond	Otsustamine	Otsustamine	Otsustamine	Otsustamine
Perekond	MCDM	MCDM	MCDM	MCDM
Tekkeaasta	2022	1980	2015	2020
Looja	Paul, V.K. Chakraborty, S. Chakraborty, S.	Saaty, T. L.	Rezaei, J.	Mohammadi, M., Rezaei, J.
Tüüp	Rough outranking/ranking — Rough number (lower approximation L, upper approximation U)	Pairwise comparison (eigenvalue)	Pairwise comparison (best-to-others + others-to-worst vectors), LP	Hierarchical Dirichlet posterior over weights via MCMC (JAGS) — group decision
Algallikas	Paul, V.K., Chakraborty, S., Chakraborty, S. (2022). An Integrated IRN-BWM-EDAS Method for Supplier Selection in a Textile Industry. Decision Making: Applications in Management and Engineering	Saaty, T. L. (1980). The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation. McGraw-Hill, New York ISBN: 978-0070543713	Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega	Mohammadi, M., Rezaei, J. (2020). Bayesian best-worst method: A probabilistic group decision making model. Omega
Rööpnimetused	—	—	—	—
Seotud	8	8	8	8
Kokkuvõte	ROUGH-EDAS (Rough-EDAS — Rough extension of EDAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Paul, V.K. Chakraborty, S. Chakraborty, S. in 2022. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.	AHP (Analytic Hierarchy Process) is a weight subjective multi-criteria decision-making (MCDM) method introduced by Saaty, T. L. in 1980. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.	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.	BWM-BAYESIAN (Bayesian BWM — Probabilistic Group Best-Worst Method) is a weight subjective multi-criteria decision-making (MCDM) method introduced by Mohammadi, M., Rezaei, J. in 2020. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.