Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Детерминированная дискретно-событийная симуляция× | Имитационное моделирование систем массового обслуживания× | |
|---|---|---|
| Область | Имитационное моделирование | Имитационное моделирование |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1960s–present | 1909 |
| Автор метода≠ | Banks, J.; Carson, J. S.; Nelson, B. L. (codified); roots in 1960s simulation pioneers (Tocher, Conway) | Agner Krarup Erlang |
| Тип≠ | Simulation — deterministic event-driven model | Stochastic simulation / analytical modeling |
| Основополагающий источник≠ | Banks, J., Carson, J. S., Nelson, B. L., and Nicol, D. M. (2010). Discrete-Event System Simulation (5th ed.). Prentice Hall. ISBN: 9780136062127 | Kleinrock, L. (1975). Queueing Systems, Volume 1: Theory. Wiley-Interscience, New York. ISBN: 978-0471491101 |
| Другие названия | Deterministic DES, Fixed-Input DES, Non-Stochastic Discrete-Event Simulation, Deterministic Event-Driven Simulation | Queue Simulation, Queuing Theory Simulation, Waiting-Line Simulation, DES-Queue |
| Связанные≠ | 5 | 6 |
| Сводка≠ | Deterministic Discrete-Event Simulation (Deterministic DES) models a system as a sequence of events occurring at precise, pre-specified times using fixed input parameters. Unlike stochastic DES, no probability distributions are sampled; every arrival, service time, and resource availability is known in advance, making runs fully reproducible and producing a single definitive output trajectory. | 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. |
| ScholarGateНабор данных ↗ |
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