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Logaritme Methodologie van Additieve Gewichten×Bayesiaanse BWM×
VakgebiedBesluitvormingBesluitvorming
FamilieMCDMMCDM
Jaar van ontstaan20212020
GrondleggerPamučar, D., Žižović, M., Biswas, S., Božanić, D.Mohammadi, M., Rezaei, J.
TypeLogarithm-based additive weightingHierarchical Dirichlet posterior over weights via MCMC (JAGS) — group decision
Oorspronkelijke bronPamučar, D., Žižović, M., Biswas, S., Božanić, D. (2021). A new logarithm methodology of additive weights (LMAW) for multi-criteria decision-making: Application in logistics. Facta Universitatis, Series: Mechanical Engineering DOI ↗Mohammadi, M., Rezaei, J. (2020). Bayesian best-worst method: A probabilistic group decision making model. Omega DOI ↗
Aliassen
Verwant88
SamenvattingLMAW (Logarithm Methodology of Additive Weights) is a ranking multi-criteria decision-making (MCDM) method introduced by Pamučar, D., Žižović, M., Biswas, S., Božanić, D. in 2021. 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: LMAW · BWM-BAYESIAN. Geraadpleegd op 2026-06-17 via https://scholargate.app/nl/compare