Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Dinamica Sistemelor Bazată pe Agenți× | Simularea cu Evenimente Discrete (SED)× | |
|---|---|---|
| Domeniu | Simulare | Simulare |
| Familie | Process / pipeline | Process / pipeline |
| Anul apariției≠ | 2000s | 1960s (formalized); modern computational form from 1970s onward |
| Autorul original≠ | Borshchev, A. & Filippov, A. (hybrid formalization); Sterman, J. D. (system dynamics foundation) | Banks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s) |
| Tip≠ | Hybrid simulation model | Stochastic process simulation |
| Sursa seminală≠ | 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 |
| Denumiri alternative≠ | AB-SD, Hybrid ABM-SD, Agent-based SD, Multi-level hybrid simulation | DES, event-driven simulation, Ayrık Olay Simülasyonu (DES) |
| Înrudite≠ | 5 | 4 |
| Rezumat≠ | 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. |
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