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Z-skaitļu fuzzy kompromisa rangs pēc attāluma līdz ideālajai risinājumam×Metode, kas balstīta uz kritēriju noņemšanas efektiem×
NozareLēmumu pieņemšanaLēmumu pieņemšana
SaimeMCDMMCDM
Izcelsmes gads20222021
AutorsPuška, A. Božanić, D. Nedeljković, M. Janošević, M.Keshavarz Ghorabaee, M., Amiri, M., Zavadskas, E. K., Antucheviciene, J., Turskis, Z.
TipsCompromise ranking via distance to ideal/anti-ideal under Z-number uncertaintyRemoval-effect objective weighting (logarithmic utility)
PirmavotsPuška, A., Božanić, D., Nedeljković, M., Janošević, M. (2022). Green Supplier Selection in an Uncertain Environment in Agriculture Using a Hybrid MCDM Model: Z-Numbers–Fuzzy LMAW–Fuzzy CRADIS Model. Axioms DOI ↗Keshavarz Ghorabaee, M., Amiri, M., Zavadskas, E. K., Antucheviciene, J., Turskis, Z. (2021). Determination of objective weights using a new method based on the removal effects of criteria (MEREC). Informatica DOI ↗
Citi nosaukumi
Saistītās88
KopsavilkumsZF-CRADIS (Z-Number Fuzzy Compromise Ranking from Distance to Ideal Solution) is a ranking multi-criteria decision-making (MCDM) method introduced by Puška, A. Božanić, D. Nedeljković, M. Janošević, M. in 2022. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.MEREC (MEthod based on the Removal Effects of Criteria) is a weight objective multi-criteria decision-making (MCDM) method introduced by Keshavarz Ghorabaee, M., Amiri, M., Zavadskas, E. K., Antucheviciene, J., Turskis, Z. in 2021. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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ScholarGateSalīdzināt metodes: ZF-CRADIS · MEREC. Izgūts 2026-06-15 no https://scholargate.app/lv/compare