Bandingkan kaedah

	Pengaturcaraan Matlamat	Proses Hierarki Analitik	Proses Rangkaian Analitik (AHP dengan maklum balas dan kebergantungan)	Bayesian BWM
Bidang	Pembuatan Keputusan	Pembuatan Keputusan	Pembuatan Keputusan	Pembuatan Keputusan
Keluarga	MCDM	MCDM	MCDM	MCDM
Tahun asal	1955	1980	1996	2020
Pengasas	Charnes, A., Cooper, W. W.	Saaty, T. L.	Saaty, T. L.	Mohammadi, M., Rezaei, J.
Jenis	Multi-objective optimisation — weighted/lexicographic goal deviation minimisation	Pairwise comparison (eigenvalue)	Weight_Subjective (pairwise comparison, supermatrix, network structure)	Hierarchical Dirichlet posterior over weights via MCMC (JAGS) — group decision
Sumber perintis	Charnes, A., Cooper, W. W. (1955). Optimal estimation of executive compensation by linear programming. Management Science	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
Alias	—	—	—	—
Berkaitan	8	8	8	8
Ringkasan	GOAL-PROGRAMMING (Goal Programming — Minimise deviations from multiple aspiration levels) is a ranking multi-criteria decision-making (MCDM) method introduced by Charnes, A., Cooper, W. W. in 1955. 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.