Сравнение методов

	Байесовское моделирование очередей	Имитационное моделирование систем массового обслуживания
Область	Имитационное моделирование	Имитационное моделирование
Семейство	Process / pipeline	Process / pipeline
Год появления	1994	1909
Автор метода	Armero, C. & Bayarri, M. J.	Agner Krarup Erlang
Тип	Bayesian inference + stochastic simulation	Stochastic simulation / analytical modeling
Основополагающий источник	Armero, C., & Bayarri, M. J. (1994). Bayesian prediction in M/M/1 queues. Queueing Systems, 15(1–4), 401–417.	Kleinrock, L. (1975). Queueing Systems, Volume 1: Theory. Wiley-Interscience, New York. ISBN: 978-0471491101
Другие названия	BQS, Bayesian Queue Simulation, Bayesian Stochastic Queueing, Bayesian Queuing Analysis	Queue Simulation, Queuing Theory Simulation, Waiting-Line Simulation, DES-Queue
Связанные	6	6
Сводка	Bayesian Queueing Simulation combines Bayesian statistical inference with stochastic queueing simulation to model waiting-line systems under parameter uncertainty. Instead of treating arrival and service rates as fixed known values, it places prior distributions over them, updates these with observed data to obtain posteriors, and propagates the resulting parameter uncertainty through repeated simulation runs to produce probabilistic predictions of system performance metrics such as queue length, waiting time, and server utilisation.	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.