So sánh phương pháp

	Phân tích độ nhạy mạnh mẽ	Mô phỏng Monte Carlo
Lĩnh vực	Mô phỏng	Ra quyết định
Họ	Process / pipeline	MCDM
Năm ra đời	1990s–2000s	1949
Người khởi xướng	Saltelli, A. and colleagues	Metropolis, N., Ulam, S.
Loại	Simulation-based robustness assessment pipeline	Robustness wrapper — Monte Carlo uncertainty propagation
Công trình gốc	Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., Saisana, M., & Tarantola, S. (2008). Global Sensitivity Analysis: The Primer. Wiley. ISBN: 9780470059975	Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association
Tên gọi khác	RSA, Robust SA, Sensitivity Analysis under Uncertainty, Uncertainty-robust sensitivity analysis	—
Liên quan	3	0
Tóm tắt	Robust Sensitivity Analysis (RSA) systematically evaluates how much variation in model outputs can be attributed to uncertainty or variation in model inputs, with an explicit focus on conclusions that remain valid across a wide range of plausible input conditions. It goes beyond standard sensitivity analysis by asking not only which inputs matter most, but which findings are truly robust — stable regardless of assumptions made under uncertainty.	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.