Sammenlign metoder

	PiF-ARAS	Analytisk Hierarkiproces	Analytic Network Process (ANP med feedback og indbyrdes afhængigheder)	Bayesian BWM
Fagområde	Beslutningstagning	Beslutningstagning	Beslutningstagning	Beslutningstagning
Familie	MCDM	MCDM	MCDM	MCDM
Oprindelsesår	2013	1980	1996	2020
Ophavsperson	Cuong, B. C., Kreinovich, V.	Saaty, T. L.	Saaty, T. L.	Mohammadi, M., Rezaei, J.
Type	Picture utility-degree ranking — Picture Fuzzy Number (PiFN: μ, η, ν; μ+η+ν ≤ 1)	Pairwise comparison (eigenvalue)	Weight_Subjective (pairwise comparison, supermatrix, network structure)	Hierarchical Dirichlet posterior over weights via MCMC (JAGS) — group decision
Oprindelig kilde	Cuong, B. C., Kreinovich, V. (2013). Picture fuzzy sets — A new concept for computational intelligence problems. 2013 Third World Congress on Information and Communication Technologies (WICT 2013)	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
Aliasser	—	—	—	—
Relaterede	8	8	8	8
Resumé	PIF-ARAS (PiF-ARAS — Picture Fuzzy extension of ARAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Cuong, B. C., Kreinovich, V. in 2013. 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.