Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Агентно-орієнтована системна динаміка× | Дискретно-подієве моделювання (DES)× | |
|---|---|---|
| Галузь | Імітаційне моделювання | Імітаційне моделювання |
| Родина | Process / pipeline | Process / pipeline |
| Рік появи≠ | 2000s | 1960s (formalized); modern computational form from 1970s onward |
| Автор методу≠ | Borshchev, A. & Filippov, A. (hybrid formalization); Sterman, J. D. (system dynamics foundation) | Banks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s) |
| Тип≠ | Hybrid simulation model | Stochastic process simulation |
| Основоположне джерело≠ | Borshchev, A., & Filippov, A. (2004). From system dynamics and discrete event to practical agent based modeling: Reasons, techniques, tools. In Proceedings of the 22nd International Conference of the System Dynamics Society. Oxford, UK. link ↗ | Banks, J., Carson, J.S., Nelson, B.L. & Nicol, D.M. (2010). Discrete-Event System Simulation (5th ed.). Pearson. ISBN: 978-0136062127 |
| Інші назви≠ | AB-SD, Hybrid ABM-SD, Agent-based SD, Multi-level hybrid simulation | DES, event-driven simulation, Ayrık Olay Simülasyonu (DES) |
| Пов'язані≠ | 5 | 4 |
| Підсумок≠ | Agent-based system dynamics (AB-SD) is a hybrid simulation paradigm that couples agent-based modeling (ABM) at the micro level with system dynamics (SD) stock-and-flow structures at the macro level. This allows researchers to capture emergent individual behavior and feedback-driven aggregate dynamics within a single coherent model, making it especially valuable for complex socio-economic and epidemiological systems. | 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. |
| ScholarGateНабір даних ↗ |
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