方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 多目标微观模拟× | 随机微观模拟× | |
|---|---|---|
| 领域 | 仿真 | 仿真 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1957 (microsimulation); 2000s (multi-objective extension) | 1957 |
| 提出者≠ | Orcutt, G. H. (microsimulation); multi-objective extension developed by policy modeling community | Guy H. Orcutt |
| 类型≠ | Simulation-based policy evaluation | Stochastic individual-level simulation |
| 开创性文献≠ | Orcutt, G. H. (1957). A new type of socio-economic system. The Review of Economics and Statistics, 39(2), 116-123. DOI ↗ | Orcutt, G. H. (1957). A new type of socio-economic system. The Review of Economics and Statistics, 39(2), 116–123. DOI ↗ |
| 别名 | MO-Microsim, Multi-criteria microsimulation, Multi-objective policy microsimulation, MOMS | Probabilistic Microsimulation, Monte Carlo Microsimulation, Stochastic Micro-simulation, SMSM |
| 相关≠ | 5 | 6 |
| 摘要≠ | 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. | 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. |
| ScholarGate数据集 ↗ |
|
|