Vertaile menetelmiä

	Modified TOPSIS based on D-Numbers (Deng Evidence Theory)	Analytic Hierarchy Process	ANP	Bayesian BWM
Tieteenala	Päätöksenteko	Päätöksenteko	Päätöksenteko	Päätöksenteko
Menetelmäperhe	MCDM	MCDM	MCDM	MCDM
Syntyvuosi	2016	1980	1996	2020
Kehittäjä	Fei, L., Hu, Y., Xiao, F., Chen, L., Deng, Y.	Saaty, T. L.	Saaty, T. L.	Mohammadi, M., Rezaei, J.
Tyyppi	D-Number ranking — D:Ω→[0,1] with Σ_{B⊆Ω} D(B) ≤ 1; incomplete evidence allowed (Deng 2012)	Pairwise comparison (eigenvalue)	Weight_Subjective (pairwise comparison, supermatrix, network structure)	Hierarchical Dirichlet posterior over weights via MCMC (JAGS) — group decision
Alkuperäislähde	Fei, L., Hu, Y., Xiao, F., Chen, L., Deng, Y. (2016). A Modified TOPSIS Method Based on D Numbers and Its Applications in Human Resources Selection. Mathematical Problems in Engineering	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
Rinnakkaisnimet	—	—	—	—
Liittyvät	8	8	8	8
Tiivistelmä	D-TOPSIS (Modified TOPSIS based on D-Numbers (Deng Evidence Theory)) is a ranking multi-criteria decision-making (MCDM) method introduced by Fei, L., Hu, Y., Xiao, F., Chen, L., Deng, Y. in 2016. 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.