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Linguïstische extensie van L2T-SAW×Bayesiaanse BWM×
VakgebiedBesluitvormingBesluitvorming
FamilieMCDMMCDM
Jaar van ontstaan20182020
GrondleggerCid-López, A., Hornos, M. J., Carrasco, R. A., Herrera-Viedma, E.Mohammadi, M., Rezaei, J.
TypeLinguistic outranking/ranking — 2-Tuple Linguistic Variable (2TL: (s_i, α))Hierarchical Dirichlet posterior over weights via MCMC (JAGS) — group decision
Oorspronkelijke bronCid-López, A., Hornos, M. J., Carrasco, R. A., Herrera-Viedma, E. (2018). Prioritization of the launch of ICT products and services through linguistic multi-criteria decision-making (2-tuple SAW). Technological and Economic Development of Economy DOI ↗Mohammadi, M., Rezaei, J. (2020). Bayesian best-worst method: A probabilistic group decision making model. Omega DOI ↗
Aliassen
Verwant88
SamenvattingL2T-SAW (Linguistic extension of L2T-SAW) is a ranking multi-criteria decision-making (MCDM) method introduced by Cid-López, A., Hornos, M. J., Carrasco, R. A., Herrera-Viedma, E. in 2018. 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.
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ScholarGateMethoden vergelijken: L2T-SAW · BWM-BAYESIAN. Geraadpleegd op 2026-06-18 via https://scholargate.app/nl/compare