Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Имитационное моделирование систем массового обслуживания× | Метод Монте-Карло× | |
|---|---|---|
| Область≠ | Имитационное моделирование | Принятие решений |
| Семейство≠ | Process / pipeline | MCDM |
| Год появления≠ | 1909 | 1949 |
| Автор метода≠ | Agner Krarup Erlang | Metropolis, N., Ulam, S. |
| Тип≠ | Stochastic simulation / analytical modeling | Robustness wrapper — Monte Carlo uncertainty propagation |
| Основополагающий источник≠ | Kleinrock, L. (1975). Queueing Systems, Volume 1: Theory. Wiley-Interscience, New York. ISBN: 978-0471491101 | Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗ |
| Другие названия≠ | Queue Simulation, Queuing Theory Simulation, Waiting-Line Simulation, DES-Queue | — |
| Связанные≠ | 6 | 0 |
| Сводка≠ | 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. | 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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