Compară metode

	Extensie plitogenică a P-CODAS	Proces Ierarhic Analitic	Procesul Analitic al Rețelei (AHP cu feedback și interdependențe)	BWM Bayesian
Domeniu	Luarea deciziilor	Luarea deciziilor	Luarea deciziilor	Luarea deciziilor
Familie	MCDM	MCDM	MCDM	MCDM
Anul apariției	2018	1980	1996	2020
Autorul original	Smarandache, F.	Saaty, T. L.	Saaty, T. L.	Mohammadi, M., Rezaei, J.
Tip	Plithogenic outranking/ranking — Plithogenic Set (PltS: attribute values with contradiction degrees)	Pairwise comparison (eigenvalue)	Weight_Subjective (pairwise comparison, supermatrix, network structure)	Hierarchical Dirichlet posterior over weights via MCMC (JAGS) — group decision
Sursa seminală	Smarandache, F. (2018). Plithogeny, Plithogenic Set, Logic, Probability, and Statistics. Pons Publishing, Brussels	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
Denumiri alternative	—	—	—	—
Înrudite	8	8	8	8
Rezumat	P-CODAS (Plithogenic extension of P-CODAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Smarandache, F. in 2018. 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.