Võrdle meetodeid

	Grey-EDAS	Analytic Hierarchy Process	ANP	Bayesi BWM
Valdkond	Otsustamine	Otsustamine	Otsustamine	Otsustamine
Perekond	MCDM	MCDM	MCDM	MCDM
Tekkeaasta	2017	1980	1996	2020
Looja	Stanujkic, D., Zavadskas, E. K., Keshavarz Ghorabaee, M., Turskis, Z.	Saaty, T. L.	Saaty, T. L.	Mohammadi, M., Rezaei, J.
Tüüp	Grey outranking/ranking — Grey Interval Number (GIN: [x̲, x̄])	Pairwise comparison (eigenvalue)	Weight_Subjective (pairwise comparison, supermatrix, network structure)	Hierarchical Dirichlet posterior over weights via MCMC (JAGS) — group decision
Algallikas	Stanujkic, D., Zavadskas, E. K., Keshavarz Ghorabaee, M., Turskis, Z. (2017). An Extension of the EDAS Method Based on the Use of Interval Grey Numbers. Studies in Informatics and Control	Saaty, T. L. (1980). The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation. McGraw-Hill, New York ISBN: 978-0070543713	Saaty, T. L. (1996). Decision Making with Dependence and Feedback: The Analytic Network Process. RWS Publications, Pittsburgh ISBN: 0-9620317-9-8	Mohammadi, M., Rezaei, J. (2020). Bayesian best-worst method: A probabilistic group decision making model. Omega
Rööpnimetused	—	—	—	—
Seotud	8	8	8	8
Kokkuvõte	GREY-EDAS (Grey-EDAS — Grey extension of EDAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Stanujkic, D., Zavadskas, E. K., Keshavarz Ghorabaee, M., Turskis, Z. in 2017. 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.	ANP (Analytic Network Process (AHP with feedback and interdependences)) is a weight subjective multi-criteria decision-making (MCDM) method introduced by Saaty, T. L. in 1996. 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.