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삼각 퍼지 수(TFN)를 이용한 퍼지 로그 가중치 방법론×가산 가중치 방법론의 로그×
분야의사결정의사결정
계열MCDMMCDM
기원 연도2021 crisp; 2022 variant applicator2021
창시자Božanić, D., Pamučar, D., Milić, A., Marinković, D., Komazec, N.Pamučar, D., Žižović, M., Biswas, S., Božanić, D.
유형Triangular-fuzzy linguistic expert weighting with Bonferroni aggregation; logarithmic transform around an absolute anti-ideal pointLogarithm-based additive weighting
원전Božanić, 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., 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 ↗
별칭
관련88
요약F-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.LMAW (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.
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ScholarGate방법 비교: F-LMAW · LMAW. 2026-06-18에 다음에서 검색함: https://scholargate.app/ko/compare