方法对比
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| 多目标系统动力学× | 随机系统动力学× | |
|---|---|---|
| 领域 | 仿真 | 仿真 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1961 (SD); multi-objective extensions from 1990s onward | 1980s–2000s |
| 提出者≠ | Forrester, J. W. (System Dynamics); multi-objective extension by various authors | Jay W. Forrester (base SD); stochastic extensions developed through 1980s–2000s by multiple researchers |
| 类型≠ | Simulation / optimization hybrid | Continuous stochastic simulation |
| 开创性文献≠ | Sterman, J. D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. McGraw-Hill. ISBN: 978-0-07-231135-8 | Sterman, J.D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. Irwin McGraw-Hill. ISBN: 978-0072389159 |
| 别名 | MOSD, Multi-criteria SD, Multi-objective SD modeling, System dynamics with multiple objectives | SSD, stochastic stock-flow modelling, probabilistic system dynamics, random system dynamics |
| 相关≠ | 4 | 5 |
| 摘要≠ | Multi-Objective System Dynamics (MOSD) couples the feedback-loop simulation power of System Dynamics with explicit multi-criteria optimization, enabling analysts to explore how a dynamic system can simultaneously satisfy competing policy goals — such as cost minimization, environmental sustainability, and social equity — over time. | Stochastic System Dynamics (SSD) extends conventional system dynamics by replacing fixed parameter values and deterministic flow equations with probability distributions and random draws. Running many replications of the stock-flow model yields probabilistic trajectories — confidence bands rather than single lines — enabling rigorous uncertainty quantification and risk analysis in complex feedback systems such as epidemic models, supply chains, and energy policy scenarios. |
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