Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Diskrētās notikumu sistēmu simulācija× | Monte Carlo simulācija× | |
|---|---|---|
| Nozare≠ | Simulācija | Lēmumu pieņemšana |
| Saime≠ | Process / pipeline | MCDM |
| Izcelsmes gads≠ | 1960s (formalised in literature through the 1980s–2000s) | 1949 |
| Autors≠ | Kelton, Law & Sadowski (formalised methodology); SIMSCRIPT (Markowitz et al., 1963) and GPSS (Gordon, 1961) were pioneering tools | Metropolis, N., Ulam, S. |
| Tips≠ | Stochastic process simulation | Robustness wrapper — Monte Carlo uncertainty propagation |
| Pirmavots≠ | Kelton, W.D., Sadowski, R.P. & Zupick, N.B. (2014). Simulation with Arena (6th ed.). McGraw-Hill. ISBN: 978-0073401317 | Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗ |
| Citi nosaukumi≠ | DES, discrete event simulation, Kesikli Sistem Simülasyonu (Arena / AnyLogic tarzı) | — |
| Saistītās≠ | 4 | 0 |
| Kopsavilkums≠ | Discrete-event system simulation (DES) is a computational modelling technique in which the state of a system changes only at discrete points in time — called events — such as a customer arriving, a machine starting, or a job completing. Formalised through foundational texts by Kelton, Sadowski, and Zupick (2014) and Law (2015), DES represents processes as networks of resources, queues, and activities, allowing analysts to test capacity and policy changes on a virtual model before touching the real system. | 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. |
| ScholarGateDatu kopa ↗ |
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