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Proximity-Adjusted WLC×Metode, kas balstīta uz kritēriju noņemšanas efektiem×
NozareLēmumu pieņemšanaLēmumu pieņemšana
SaimeMCDMMCDM
Izcelsmes gads20062021
AutorsRinner, C.; Heppleston, A.Keshavarz Ghorabaee, M., Amiri, M., Zavadskas, E. K., Antucheviciene, J., Turskis, Z.
TipsSpatially heterogeneous additive utility — criterion weights vary per alternative as a function of proximity to a reference locationRemoval-effect objective weighting (logarithmic utility)
PirmavotsRinner, C., Heppleston, A. (2006). The spatial dimensions of multi-criteria evaluation — case study of a home buyer's spatial decision support system. Lecture Notes in Computer Science (GIScience 2006) 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
KopsavilkumsPROXIMITY-WLC (Proximity-Adjusted WLC — spatially explicit weighted linear combination) is a ranking multi-criteria decision-making (MCDM) method introduced by Rinner, C.; Heppleston, A. in 2006. 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: PROXIMITY-WLC · MEREC. Izgūts 2026-06-17 no https://scholargate.app/lv/compare