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M/M/1 опашка: Основният модел на опашка с един обслужващ канал×Модел на Ерланг C×
ОбластИзследване на операциитеИзследване на операциите
СемействоRegression modelRegression model
Година на възникване19531981
СъздателA. K. Erlang; David Kendall (notation)Agner Krarup Erlang; Cooper
ТипStochastic queueing modelSteady-state queueing model
Основополагащ източникKendall, 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. DOI ↗Cooper, R. B. (1981). Introduction to Queueing Theory (2nd ed.). North-Holland. ISBN: 978-0-444-00379-7
Други названияSingle-Server Markovian Queue, Birth-Death Queue, Poisson Queue, M/M/1 Kuyruk ModeliM/M/c Queue, Multi-Server Queueing Model, Erlang Delay Formula, Erlang-C Bekleme Modeli
Свързани33
РезюмеThe M/M/1 queue is the foundational single-server queueing model in which customers arrive according to a Poisson process with rate λ, are served one at a time by a single server with exponentially distributed service times at rate μ, and wait in an infinite-capacity first-come-first-served queue. Formalized within the Kendall notation framework by David Kendall in 1953, building on A. K. Erlang's early twentieth-century telephone traffic work, it yields closed-form steady-state performance measures when the traffic intensity ρ = λ/μ is less than one.The Erlang C model is a steady-state queueing formula that determines the probability a customer must wait before being served in a system with c parallel servers, Poisson arrivals at rate lambda, and exponentially distributed service times. Originally developed by Danish engineer Agner Krarup Erlang in the early twentieth century for telephone exchange design, and formalized in the queueing theory literature by Cooper (1981), it remains the canonical staffing model for call centers and service operations worldwide.
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ScholarGateСравнение на методи: M/M/1 Queue · Erlang C Model. Извлечено на 2026-06-17 от https://scholargate.app/bg/compare