Módszerek összehasonlítása
Tekintse át a kiválasztott módszereket egymás mellett; az eltérő sorok kiemelve jelennek meg.
| Robuszt Diszkrét Eseményű Szimuláció× | MONTE-CARLO-SIMULATION× | |
|---|---|---|
| Tudományterület≠ | Szimuláció | Döntéshozatal |
| Módszercsalád≠ | Process / pipeline | MCDM |
| Keletkezés éve≠ | 1990s–2000s | 1949 |
| Megalkotó≠ | Banks, Carson, Nelson, Nicol (canonical DES); robust extensions: operations research community | Metropolis, N., Ulam, S. |
| Típus≠ | Simulation with robustness analysis | Robustness wrapper — Monte Carlo uncertainty propagation |
| Alapmű≠ | Banks, J., Carson, J. S., Nelson, B. L., & Nicol, D. M. (2010). Discrete-Event System Simulation (5th ed.). Prentice Hall. ISBN: 9780136062127 | Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗ |
| Alternatív nevek≠ | Robust DES, Uncertainty-Aware DES, Robust DEVS, Resilient Discrete-Event Simulation | — |
| Kapcsolódó≠ | 6 | 0 |
| Összefoglaló≠ | Robust Discrete-Event Simulation (Robust DES) is a simulation methodology that extends classical discrete-event simulation by explicitly incorporating uncertainty in model parameters — such as interarrival times, service durations, and resource capacities — and evaluating system performance across worst-case or distributional uncertainty sets rather than point estimates alone. It is widely applied in manufacturing, healthcare, logistics, and supply chain systems where parameter misspecification or real-world variability can lead to misleading simulation conclusions. | 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. |
| ScholarGateAdatkészlet ↗ |
|
|