Comparar métodos

	Extensión Lingüística Probabilística de MARCOS	Proceso Analítico Jerárquico	Proceso Analítico en Red (AHP con retroalimentación e interdependencias)	BWM-BAYESIAN (Método Bayesiano de Mejor-Peor para Grupos
Campo	Toma de decisiones	Toma de decisiones	Toma de decisiones	Toma de decisiones
Familia	MCDM	MCDM	MCDM	MCDM
Año de origen	2023	1980	1996	2020
Autor original	Wang, J., Wei, G., Wei, C., Wei, Y.	Saaty, T. L.	Saaty, T. L.	Mohammadi, M., Rezaei, J.
Tipo	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
Fuente seminal	(). 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
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Relacionados	8	8	8	8
Resumen	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.