Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Simularea Cozilor× | Simularea cu Evenimente Discrete (SED)× | |
|---|---|---|
| Domeniu | Simulare | Simulare |
| Familie | Process / pipeline | Process / pipeline |
| Anul apariției≠ | 1909 | 1960s (formalized); modern computational form from 1970s onward |
| Autorul original≠ | Agner Krarup Erlang | Banks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s) |
| Tip≠ | Stochastic simulation / analytical modeling | Stochastic process simulation |
| Sursa seminală≠ | Kleinrock, L. (1975). Queueing Systems, Volume 1: Theory. Wiley-Interscience, New York. ISBN: 978-0471491101 | Banks, J., Carson, J.S., Nelson, B.L. & Nicol, D.M. (2010). Discrete-Event System Simulation (5th ed.). Pearson. ISBN: 978-0136062127 |
| Denumiri alternative≠ | Queue Simulation, Queuing Theory Simulation, Waiting-Line Simulation, DES-Queue | DES, event-driven simulation, Ayrık Olay Simülasyonu (DES) |
| Înrudite≠ | 6 | 4 |
| Rezumat≠ | Queueing Simulation combines classical queueing theory with discrete-event simulation to model systems where entities arrive, wait for service, and depart. It predicts performance metrics such as average waiting time, queue length, and server utilization, enabling capacity planning and bottleneck identification across service, manufacturing, healthcare, and network 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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