Sammenlign metoder

	Rough-VIKOR	Analytisk Hierarkiproces	Best-Worst-metoden	Bayesian BWM
Fagområde	Beslutningstagning	Beslutningstagning	Beslutningstagning	Beslutningstagning
Familie	MCDM	MCDM	MCDM	MCDM
Oprindelsesår	2015	1980	2015	2020
Ophavsperson	Zhu, G. Hu, J. Qi, J. Gu, C. Peng, Y.	Saaty, T. L.	Rezaei, J.	Mohammadi, M., Rezaei, J.
Type	Rough outranking/ranking — Rough number (lower approximation L, upper approximation U)	Pairwise comparison (eigenvalue)	Pairwise comparison (best-to-others + others-to-worst vectors), LP	Hierarchical Dirichlet posterior over weights via MCMC (JAGS) — group decision
Oprindelig kilde	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	Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega	Mohammadi, M., Rezaei, J. (2020). Bayesian best-worst method: A probabilistic group decision making model. Omega
Aliasser	—	—	—	—
Relaterede	8	8	8	8
Resumé	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.	BWM (Best-Worst Method) is a weight subjective multi-criteria decision-making (MCDM) method introduced by Rezaei, J. in 2015. 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.