Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Закон Літтла (L = λW)× | M/M/c Черга: Багатосерверна модель черг× | |
|---|---|---|
| Галузь | Дослідження операцій | Дослідження операцій |
| Родина | Regression model | Regression model |
| Рік появи≠ | 1961 | 1998 |
| Автор методу≠ | John D. C. Little | Queueing-theory tradition; Gross & Harris |
| Тип≠ | Exact queueing identity | Multi-server Markovian queueing model |
| Основоположне джерело≠ | Little, J. D. C. (1961). A proof for the queuing formula: L = λW. Operations Research, 9(3), 383–387. DOI ↗ | Gross, D., & Harris, C. M. (1998). Fundamentals of Queueing Theory (3rd ed.). Wiley. ISBN: 978-0-471-17083-9 |
| Інші назви | L = λW Theorem, Little's Theorem, Little's Result, Little Yasası | Multi-Server Erlang Queue, c-Server Markovian Queue, Erlang-C Queue, Çok Sunuculu M/M/c Kuyruğu |
| Пов'язані | 3 | 3 |
| Підсумок≠ | Little's Law is a fundamental theorem in queueing theory that relates the long-run average number of items in a stable system (L) to the long-run average arrival rate (λ) and the long-run average time an item spends in the system (W), expressed as L = λW. Introduced and rigorously proved by John D. C. Little in 1961, the law holds for virtually any stable stochastic system, requiring no assumptions about arrival distributions, service distributions, or queue disciplines. | 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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