Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Diskrētā notikumu simulācija (DES) politikas scenāriji× | Sistēmdinamika× | |
|---|---|---|
| Nozare | Simulācija | Simulācija |
| Saime | Process / pipeline | Process / pipeline |
| Izcelsmes gads≠ | 1960s–1990s | 1961 |
| Autors≠ | Tocher, K. D. and Gordon, G. (early DES); policy scenario extension emerged through operations research and health policy modeling communities | Jay W. Forrester |
| Tips≠ | Simulation-based policy evaluation | Continuous simulation / feedback modelling |
| Pirmavots≠ | Law, A. M. (2015). Simulation Modeling and Analysis (5th ed.). McGraw-Hill Education. ISBN: 9780073401324 | Sterman, J.D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. Irwin McGraw-Hill. ISBN: 978-0072389159 |
| Citi nosaukumi | Policy DES, Scenario-based DES, Policy simulation DES, DES policy analysis | stock-flow modelling, Sistem Dinamiği (Stock-Flow Modelleme), SD modelling, feedback simulation |
| Saistītās≠ | 5 | 3 |
| Kopsavilkums≠ | Policy Scenario Discrete-Event Simulation combines the event-by-event fidelity of Discrete-Event Simulation with systematic policy scenario analysis to evaluate how different interventions, regulations, or resource allocations change system performance. By running multiple well-defined policy scenarios through the same DES model, analysts can compare outcomes — throughput, waiting times, costs — across alternatives before real-world implementation. | System dynamics is a continuous simulation method, developed by Jay W. Forrester at MIT in 1961, that represents a complex system through stocks (accumulations), flows (rates of change), and feedback loops. By expressing these relationships as coupled ordinary differential equations, it reproduces how policies, delays, and nonlinear feedbacks drive system behaviour over time — making it a cornerstone tool in policy analysis, organisational modelling, and sustainability research. |
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