Methoden vergelijken

	Rough-VIKOR	Analytic Hierarchy Process	ANP	Bayesiaanse BWM
Vakgebied	Besluitvorming	Besluitvorming	Besluitvorming	Besluitvorming
Familie	MCDM	MCDM	MCDM	MCDM
Jaar van ontstaan	2015	1980	1996	2020
Grondlegger	Zhu, G. Hu, J. Qi, J. Gu, C. Peng, Y.	Saaty, T. L.	Saaty, T. L.	Mohammadi, M., Rezaei, J.
Type	Rough outranking/ranking — Rough number (lower approximation L, upper approximation U)	Pairwise comparison (eigenvalue)	Weight_Subjective (pairwise comparison, supermatrix, network structure)	Hierarchical Dirichlet posterior over weights via MCMC (JAGS) — group decision
Oorspronkelijke bron	Zhu, G., Hu, J., Qi, J., Gu, C., Peng, Y. (2015). An integrated AHP and VIKOR for design concept evaluation based on rough number. Advanced Engineering Informatics	Saaty, T. L. (1980). The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation. McGraw-Hill, New York ISBN: 978-0070543713	Saaty, T. L. (1996). Decision Making with Dependence and Feedback: The Analytic Network Process. RWS Publications, Pittsburgh ISBN: 0-9620317-9-8	Mohammadi, M., Rezaei, J. (2020). Bayesian best-worst method: A probabilistic group decision making model. Omega
Aliassen	—	—	—	—
Verwant	8	8	8	8
Samenvatting	ROUGH-VIKOR (Rough-VIKOR — Rough extension of VIKOR) is a ranking multi-criteria decision-making (MCDM) method introduced by Zhu, G. Hu, J. Qi, J. Gu, C. Peng, Y. in 2015. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.	AHP (Analytic Hierarchy Process) is a weight subjective multi-criteria decision-making (MCDM) method introduced by Saaty, T. L. in 1980. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.	ANP (Analytic Network Process (AHP with feedback and interdependences)) is a weight subjective multi-criteria decision-making (MCDM) method introduced by Saaty, T. L. in 1996. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.	BWM-BAYESIAN (Bayesian BWM — Probabilistic Group Best-Worst Method) is a weight subjective multi-criteria decision-making (MCDM) method introduced by Mohammadi, M., Rezaei, J. in 2020. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.