Comparer des méthodes

	Microsimulation stochastique	Simulation de Monte-Carlo
Domaine	Simulation	Prise de décision
Famille	Process / pipeline	MCDM
Année d'origine	1957	1949
Auteur d'origine	Guy H. Orcutt	Metropolis, N., Ulam, S.
Type	Stochastic individual-level simulation	Robustness wrapper — Monte Carlo uncertainty propagation
Source fondatrice	Orcutt, G. H. (1957). A new type of socio-economic system. The Review of Economics and Statistics, 39(2), 116–123.	Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association
Alias	Probabilistic Microsimulation, Monte Carlo Microsimulation, Stochastic Micro-simulation, SMSM	—
Apparentées	6	0
Résumé	Stochastic Microsimulation tracks a large population of individual units — people, households, or firms — through time by applying random draws from empirically estimated probability distributions at each transition event. Unlike deterministic counterparts, every state change is decided by chance, preserving realistic heterogeneity and allowing rigorous uncertainty quantification across multiple simulation runs.	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.