Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Simulation à événements discrets (DES)× | File d'attente M/M/c : Modèle de file d'attente multi-serveurs× | |
|---|---|---|
| Domaine≠ | Simulation | Recherche opérationnelle |
| Famille≠ | Process / pipeline | Regression model |
| Année d'origine≠ | 1960s (formalized); modern computational form from 1970s onward | 1998 |
| Auteur d'origine≠ | Banks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s) | Queueing-theory tradition; Gross & Harris |
| Type≠ | Stochastic process simulation | Multi-server Markovian queueing model |
| Source fondatrice≠ | Banks, J., Carson, J.S., Nelson, B.L. & Nicol, D.M. (2010). Discrete-Event System Simulation (5th ed.). Pearson. ISBN: 978-0136062127 | Gross, D., & Harris, C. M. (1998). Fundamentals of Queueing Theory (3rd ed.). Wiley. ISBN: 978-0-471-17083-9 |
| Alias≠ | DES, event-driven simulation, Ayrık Olay Simülasyonu (DES) | Multi-Server Erlang Queue, c-Server Markovian Queue, Erlang-C Queue, Çok Sunuculu M/M/c Kuyruğu |
| Apparentées≠ | 4 | 3 |
| Résumé≠ | 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. | The M/M/c queue is a multi-server stochastic model in which customers arrive according to a Poisson process at rate λ, are served by c identical servers each with exponentially distributed service times at rate μ, and wait in a single common queue when all servers are busy. Systematized within classical queueing theory and thoroughly treated by Gross and Harris (1998), it extends the simpler M/M/1 model to settings with parallel servers, making it the foundational tool for capacity planning in service systems. |
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