Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Simulare Deterministică a Evenimentelor Discrete× | Simularea Stocastică a Evenimentelor Discrete× | |
|---|---|---|
| Domeniu | Simulare | Simulare |
| Familie | Process / pipeline | Process / pipeline |
| Anul apariției≠ | 1960s–present | 1960s–1970s |
| Autorul original≠ | Banks, J.; Carson, J. S.; Nelson, B. L. (codified); roots in 1960s simulation pioneers (Tocher, Conway) | Banks, Carson, Nelson, Nicol; Law, A. M. |
| Tip≠ | Simulation — deterministic event-driven model | Stochastic simulation model |
| Sursa seminală≠ | Banks, J., Carson, J. S., Nelson, B. L., and Nicol, D. M. (2010). Discrete-Event System Simulation (5th ed.). Prentice Hall. ISBN: 9780136062127 | Banks, J., Carson, J. S., Nelson, B. L., & Nicol, D. M. (2010). Discrete-Event System Simulation (5th ed.). Prentice Hall. ISBN: 9780136062127 |
| Denumiri alternative | Deterministic DES, Fixed-Input DES, Non-Stochastic Discrete-Event Simulation, Deterministic Event-Driven Simulation | Stochastic DES, SDES, Probabilistic DES, Monte Carlo DES |
| Înrudite≠ | 5 | 6 |
| Rezumat≠ | 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. | Stochastic Discrete-Event Simulation (Stochastic DES) models complex systems by advancing simulated time from one discrete event to the next, drawing event durations and inter-arrival times from fitted probability distributions. It is the standard technique for analyzing queues, manufacturing lines, healthcare pathways, and logistics networks under uncertainty, producing output statistics with confidence intervals. |
| ScholarGateSet de date ↗ |
|
|