Sammenlign metoder

	Evaluering basert på avstand fra gjennomsnittsløsning	Logaritmetisk metode for additive vekter	Sammenligning av areal for grenseapproksimasjon med flere attributter
Fagfelt	Beslutningstaking	Beslutningstaking	Beslutningstaking
Familie	MCDM	MCDM	MCDM
Opprinnelsesår	2015	2021	2015
Opphavsperson	Keshavarz Ghorabaee, M., Zavadskas, E. K., Olfat, L., Turskis, Z.	Pamučar, D., Žižović, M., Biswas, S., Božanić, D.	Pamučar, D., Ćirović, G.
Type	Distance from average solution	Logarithm-based additive weighting	Border approximation area (distance from BAA)
Opprinnelig kilde	Keshavarz Ghorabaee, M., Zavadskas, E. K., Olfat, L., Turskis, Z. (2015). Multi-criteria inventory classification using a new method of evaluation based on distance from average solution (EDAS). Informatica	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	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
Alias	—	—	—
Relaterte	8	8	8
Sammendrag	EDAS (Evaluation Based on Distance from Average Solution) is a ranking multi-criteria decision-making (MCDM) method introduced by Keshavarz Ghorabaee, M., Zavadskas, E. K., Olfat, L., Turskis, Z. in 2015. 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.	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.