Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Агентно-событийное дискретно-событийное моделирование× | Имитационное моделирование дискретных событий (DES)× | |
|---|---|---|
| Область | Имитационное моделирование | Имитационное моделирование |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 2000s | 1960s (formalized); modern computational form from 1970s onward |
| Автор метода≠ | Hybridization formalized by multiple authors; Siebers & Aickelin, Lagergren & Buckley among key contributors | Banks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s) |
| Тип≠ | Hybrid simulation paradigm | Stochastic process simulation |
| Основополагающий источник≠ | Lagergren, J. H., & Buckley, E. (2010). A hybrid approach to simulation: Combining agent-based and discrete event simulation. Proceedings of the 2010 Winter Simulation Conference, pp. 170–181. IEEE. link ↗ | Banks, J., Carson, J.S., Nelson, B.L. & Nicol, D.M. (2010). Discrete-Event System Simulation (5th ed.). Pearson. ISBN: 978-0136062127 |
| Другие названия≠ | AB-DES, Hybrid ABM-DES, Agent-DES, Hybrid Agent-Based Discrete-Event Simulation | DES, event-driven simulation, Ayrık Olay Simülasyonu (DES) |
| Связанные | 4 | 4 |
| Сводка≠ | Agent-based discrete-event simulation (AB-DES) is a hybrid modeling paradigm that couples autonomous agent behavior with an event-driven execution engine. It captures the decision-making heterogeneity of individual entities while maintaining the precise, time-stamped flow control of discrete-event simulation, making it suitable for complex systems where both individual agency and process sequencing matter. | 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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