Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Deterministiskā diskrēto notikumu simulācija× | Simulācija rindās× | |
|---|---|---|
| Nozare | Simulācija | Simulācija |
| Saime | Process / pipeline | Process / pipeline |
| Izcelsmes gads≠ | 1960s–present | 1909 |
| Autors≠ | Banks, J.; Carson, J. S.; Nelson, B. L. (codified); roots in 1960s simulation pioneers (Tocher, Conway) | Agner Krarup Erlang |
| Tips≠ | Simulation — deterministic event-driven model | Stochastic simulation / analytical modeling |
| Pirmavots≠ | 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 |
| Citi nosaukumi | Deterministic DES, Fixed-Input DES, Non-Stochastic Discrete-Event Simulation, Deterministic Event-Driven Simulation | Queue Simulation, Queuing Theory Simulation, Waiting-Line Simulation, DES-Queue |
| Saistītās≠ | 5 | 6 |
| Kopsavilkums≠ | 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. |
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