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Закон Литтла (L = λW)×Имитационное моделирование дискретных событий (DES)×
ОбластьИсследование операцийИмитационное моделирование
СемействоRegression modelProcess / pipeline
Год появления19611960s (formalized); modern computational form from 1970s onward
Автор методаJohn D. C. LittleBanks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s)
ТипExact queueing identityStochastic process simulation
Основополагающий источникLittle, J. D. C. (1961). A proof for the queuing formula: L = λW. Operations Research, 9(3), 383–387. DOI ↗Banks, J., Carson, J.S., Nelson, B.L. & Nicol, D.M. (2010). Discrete-Event System Simulation (5th ed.). Pearson. ISBN: 978-0136062127
Другие названияL = λW Theorem, Little's Theorem, Little's Result, Little YasasıDES, event-driven simulation, Ayrık Olay Simülasyonu (DES)
Связанные34
СводкаLittle'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.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.
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ScholarGateСравнение методов: Little's Law · Discrete-Event Simulation. Получено 2026-06-19 из https://scholargate.app/ru/compare