So sánh phương pháp

	Phân tích độ nhạy quyết định	Mô phỏng Monte Carlo
Lĩnh vực	Mô phỏng	Ra quyết định
Họ	Process / pipeline	MCDM
Năm ra đời	1950s–1970s (formalized)	1949
Người khởi xướng	Saltelli, A. et al.; widely formalized across operations research and health economics	Metropolis, N., Ulam, S.
Loại	Parameter variation / robustness testing	Robustness wrapper — Monte Carlo uncertainty propagation
Công trình gốc	Saltelli, A., Tarantola, S., Campolongo, F., & Ratto, M. (2004). Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models. John Wiley & Sons, Chichester. ISBN: 9780470870938	Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association
Tên gọi khác	DSA, One-Way Sensitivity Analysis, Tornado Diagram Analysis, Parametric Sensitivity Analysis	—
Liên quan	2	0
Tóm tắt	Deterministic Sensitivity Analysis (DSA) tests how model outputs change when individual or combined input parameters are varied across plausible ranges, one at a time or in structured combinations, without invoking probabilistic sampling. It is the standard approach in economic modeling, decision trees, and mathematical programming to identify which parameters drive conclusions and to demonstrate model robustness to regulators, reviewers, and stakeholders.	MONTE-CARLO-SIMULATION (Monte Carlo Simulation — Stochastic uncertainty propagation through MCDM model) is a ranking multi-criteria decision-making (MCDM) method introduced by Metropolis, N., Ulam, S. in 1949. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.