Comparer des méthodes

	Simulation stochastique de files d'attente	Simulation de files d'attente
Domaine	Simulation	Simulation
Famille	Process / pipeline	Process / pipeline
Année d'origine	1953	1909
Auteur d'origine	Kendall, D. G.	Agner Krarup Erlang
Type	Stochastic simulation — waiting-line system analysis	Stochastic simulation / analytical modeling
Source fondatrice	Kendall, D. G. (1953). Stochastic processes occurring in the theory of queues and their analysis by the method of the imbedded Markov chain. The Annals of Mathematical Statistics, 24(3), 338–354.	Kleinrock, L. (1975). Queueing Systems, Volume 1: Theory. Wiley-Interscience, New York. ISBN: 978-0471491101
Alias	SQS, Probabilistic Queueing Simulation, Stochastic Queue Modeling, Random Queueing Simulation	Queue Simulation, Queuing Theory Simulation, Waiting-Line Simulation, DES-Queue
Apparentées	6	6
Résumé	Stochastic Queueing Simulation models waiting-line systems where arrival and service processes follow probability distributions rather than fixed rates. By simulating thousands of random events, it estimates performance measures — mean waiting time, queue length, server utilization — under realistic uncertainty, making it the standard tool for designing and evaluating service systems from hospitals to call centers.	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.