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Имитационное моделирование дискретных событий (DES)×Метод Монте-Карло×
ОбластьИмитационное моделированиеПринятие решений
СемействоProcess / pipelineMCDM
Год появления1960s (formalized); modern computational form from 1970s onward1949
Автор методаBanks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s)Metropolis, N., Ulam, S.
ТипStochastic process simulationRobustness wrapper — Monte Carlo uncertainty propagation
Основополагающий источникBanks, J., Carson, J.S., Nelson, B.L. & Nicol, D.M. (2010). Discrete-Event System Simulation (5th ed.). Pearson. ISBN: 978-0136062127Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
Другие названияDES, event-driven simulation, Ayrık Olay Simülasyonu (DES)
Связанные40
СводкаDiscrete-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.MONTE-CARLO-SIMULATION (Monte Carlo Simulation — Stochastic uncertainty propagation through MCDM model) is a ranking multi-criteria decision-making (MCDM) method introduced by Metropolis, N., Ulam, S. in 1949. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
ScholarGateНабор данных
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  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 1 Источники
  3. PUBLISHED

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ScholarGateСравнение методов: Discrete-Event Simulation · MONTE-CARLO-SIMULATION. Получено 2026-06-17 из https://scholargate.app/ru/compare