Comparer des méthodes

	Extension linguistique probabiliste de MARCOS	Processus d'analyse hiérarchique	ANP	BWM bayésien
Domaine	Prise de décision	Prise de décision	Prise de décision	Prise de décision
Famille	MCDM	MCDM	MCDM	MCDM
Année d'origine	2023	1980	1996	2020
Auteur d'origine	Wang, J., Wei, G., Wei, C., Wei, Y.	Saaty, T. L.	Saaty, T. L.	Mohammadi, M., Rezaei, J.
Type	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
Source fondatrice	(). UNCONFIRMED — PL-MARCOS specific seminal not confirmed via systematic literature search. PENDING	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
Alias	—	—	—	—
Apparentées	8	8	8	8
Résumé	PL-MARCOS (Probabilistic Linguistic extension of MARCOS) is a ranking multi-criteria decision-making (MCDM) method introduced by Wang, J., Wei, G., Wei, C., Wei, Y. in 2023. 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.