مقایسهٔ روش‌ها

	تحلیل حساسیت مقاوم	شبیه‌سازی مونت کارلو
حوزه	شبیه‌سازی	تصمیم‌گیری
خانواده	Process / pipeline	MCDM
سال پیدایش	1990s–2000s	1949
پدیدآور	Saltelli, A. and colleagues	Metropolis, N., Ulam, S.
نوع	Simulation-based robustness assessment pipeline	Robustness wrapper — Monte Carlo uncertainty propagation
منبع بنیادین	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
نام‌های دیگر	RSA, Robust SA, Sensitivity Analysis under Uncertainty, Uncertainty-robust sensitivity analysis	—
مرتبط	3	0
خلاصه	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.