Compară metode

	Extensia lingvistică probabilistică a metodei EDAS	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	2016	1980	1996	2020
Autorul original	Pang, Q. Wang, H. Xu, Z.	Saaty, T. L.	Saaty, T. L.	Mohammadi, M., Rezaei, J.
Tip	Probabilistic Linguistic outranking/ranking — Probabilistic Linguistic Term Set (PLTS: {L_k|p_k})	Pairwise comparison (eigenvalue)	Weight_Subjective (pairwise comparison, supermatrix, network structure)	Hierarchical Dirichlet posterior over weights via MCMC (JAGS) — group decision
Sursa seminală	Pang, Q., Wang, H., Xu, Z. (2016). Probabilistic linguistic term sets in multi-attribute group decision making. Information Sciences	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	PL-EDAS (Probabilistic Linguistic extension of EDAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Pang, Q. Wang, H. Xu, Z. in 2016. 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.