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Simulation de files d'attente×Simulation à événements discrets (DES)×
DomaineSimulationSimulation
FamilleProcess / pipelineProcess / pipeline
Année d'origine19091960s (formalized); modern computational form from 1970s onward
Auteur d'origineAgner Krarup ErlangBanks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s)
TypeStochastic simulation / analytical modelingStochastic process simulation
Source fondatriceKleinrock, L. (1975). Queueing Systems, Volume 1: Theory. Wiley-Interscience, New York. ISBN: 978-0471491101Banks, J., Carson, J.S., Nelson, B.L. & Nicol, D.M. (2010). Discrete-Event System Simulation (5th ed.). Pearson. ISBN: 978-0136062127
AliasQueue Simulation, Queuing Theory Simulation, Waiting-Line Simulation, DES-QueueDES, event-driven simulation, Ayrık Olay Simülasyonu (DES)
Apparentées64
RésuméQueueing 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.
ScholarGateJeu de données
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ScholarGateComparer des méthodes: Queueing Simulation · Discrete-Event Simulation. Consulté le 2026-06-15 sur https://scholargate.app/fr/compare