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Metodologia Rozmytego Logarytmu Wag Addytywnych (TFN)×MABAC×
DziedzinaPodejmowanie decyzjiPodejmowanie decyzji
RodzinaMCDMMCDM
Rok powstania2021 crisp; 2022 variant applicator2015
TwórcaBožanić, D., Pamučar, D., Milić, A., Marinković, D., Komazec, N.Pamučar, D., Ćirović, G.
TypTriangular-fuzzy linguistic expert weighting with Bonferroni aggregation; logarithmic transform around an absolute anti-ideal pointBorder approximation area (distance from BAA)
Źródło pierwotneBožanić, D., Pamučar, D., Milić, A., Marinković, D., Komazec, N. (2022). Modification of the Logarithm Methodology of Additive Weights (LMAW) by a Triangular Fuzzy Number and Its Application in Multi-Criteria Decision Making. Axioms DOI ↗Pamučar, D., Ćirović, G. (2015). The selection of transport and handling resources in logistics centers using Multi-Attributive Border Approximation area Comparison (MABAC). Expert Systems with Applications DOI ↗
Inne nazwy
Pokrewne88
PodsumowanieF-LMAW (Fuzzy Logarithm Methodology of Additive Weights (TFN)) is a weight subjective multi-criteria decision-making (MCDM) method introduced by Božanić, D., Pamučar, D., Milić, A., Marinković, D., Komazec, N. in 2021 crisp; 2022 variant applicator. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.MABAC (Multi-Attributive Border Approximation area Comparison) is a ranking multi-criteria decision-making (MCDM) method introduced by Pamučar, D., Ćirović, G. in 2015. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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ScholarGatePorównaj metody: F-LMAW · MABAC. Pobrano 2026-06-17 z https://scholargate.app/pl/compare