Methoden vergelijken

	Monte Carlo Simulatie	Stochastische Gevoeligheidsanalyse
Vakgebied	Besluitvorming	Simulatie
Familie	MCDM	Process / pipeline
Jaar van ontstaan	1949	1990s–2000s
Grondlegger	Metropolis, N., Ulam, S.	Saltelli, A. et al.; Claxton, K. et al. (health economics stream)
Type	Robustness wrapper — Monte Carlo uncertainty propagation	Probabilistic uncertainty quantification technique
Oorspronkelijke bron	Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association	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
Aliassen	—	PSA, Probabilistic Sensitivity Analysis, Stochastic SA, Monte Carlo Sensitivity Analysis
Verwant	0	5
Samenvatting	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.	Stochastic Sensitivity Analysis (PSA) extends classical one-at-a-time sensitivity testing by representing uncertain model inputs as probability distributions and propagating them through the model via Monte Carlo sampling. The result is a full distribution of possible outputs, together with rankings of which inputs drive output variance the most — enabling robust, evidence-grounded conclusions under uncertainty.