Krahasoni metodat
Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.
| Modelimi hibrid i simulimit me bazë agjentë dhe ngjarje diskrete× | Simulimi me Evente Diskret (DES)× | |
|---|---|---|
| Fusha | Simulimi | Simulimi |
| Familja | Process / pipeline | Process / pipeline |
| Viti i origjinës≠ | 2000s | 1960s (formalized); modern computational form from 1970s onward |
| Krijuesi≠ | Hybridization formalized by multiple authors; Siebers & Aickelin, Lagergren & Buckley among key contributors | Banks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s) |
| Lloji≠ | Hybrid simulation paradigm | Stochastic process simulation |
| Burimi themelues≠ | 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 |
| Emërtime të tjera≠ | AB-DES, Hybrid ABM-DES, Agent-DES, Hybrid Agent-Based Discrete-Event Simulation | DES, event-driven simulation, Ayrık Olay Simülasyonu (DES) |
| Të lidhura | 4 | 4 |
| Përmbledhja≠ | 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. |
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