Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Имитационное моделирование дискретно-событийных сценариев политики× | Имитационное моделирование дискретных событий (DES)× | |
|---|---|---|
| Область | Имитационное моделирование | Имитационное моделирование |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1960s–1990s | 1960s (formalized); modern computational form from 1970s onward |
| Автор метода≠ | Tocher, K. D. and Gordon, G. (early DES); policy scenario extension emerged through operations research and health policy modeling communities | Banks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s) |
| Тип≠ | Simulation-based policy evaluation | Stochastic process simulation |
| Основополагающий источник≠ | Law, A. M. (2015). Simulation Modeling and Analysis (5th ed.). McGraw-Hill Education. ISBN: 9780073401324 | Banks, J., Carson, J.S., Nelson, B.L. & Nicol, D.M. (2010). Discrete-Event System Simulation (5th ed.). Pearson. ISBN: 978-0136062127 |
| Другие названия≠ | Policy DES, Scenario-based DES, Policy simulation DES, DES policy analysis | DES, event-driven simulation, Ayrık Olay Simülasyonu (DES) |
| Связанные≠ | 5 | 4 |
| Сводка≠ | 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. | Discrete-Event Simulation (DES) is a computational modeling paradigm in which the state of a system changes only at a countable sequence of points in time — the events. Between events nothing changes, so the simulation clock jumps directly from one event to the next. Formalized through the foundational textbooks of Banks, Carson, Nelson and Nicol and of Law in the 1960s–2000s, DES has become the standard tool for analyzing queuing systems, healthcare patient flows, manufacturing lines, and logistics networks where entities move through resources over time. |
| ScholarGateНабор данных ↗ |
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