Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Multi-objective Microsimulation× | Monte Carlo simulācija× | |
|---|---|---|
| Nozare≠ | Simulācija | Lēmumu pieņemšana |
| Saime≠ | Process / pipeline | MCDM |
| Izcelsmes gads≠ | 1957 (microsimulation); 2000s (multi-objective extension) | 1949 |
| Autors≠ | Orcutt, G. H. (microsimulation); multi-objective extension developed by policy modeling community | Metropolis, N., Ulam, S. |
| Tips≠ | Simulation-based policy evaluation | Robustness wrapper — Monte Carlo uncertainty propagation |
| Pirmavots≠ | Orcutt, G. H. (1957). A new type of socio-economic system. The Review of Economics and Statistics, 39(2), 116-123. DOI ↗ | Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗ |
| Citi nosaukumi≠ | MO-Microsim, Multi-criteria microsimulation, Multi-objective policy microsimulation, MOMS | — |
| Saistītās≠ | 5 | 0 |
| Kopsavilkums≠ | Multi-objective microsimulation extends the classic microsimulation framework by simultaneously tracking and optimizing several competing policy objectives — such as efficiency, equity, fiscal cost, and social welfare — across a heterogeneous population of individual units. It produces a Pareto frontier of policy options rather than a single recommended solution, enabling transparent tradeoff analysis for complex policy decisions. | 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. |
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