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| Simulation von ereignisdiskreten Systemen× | Monte-Carlo-Simulation× | |
|---|---|---|
| Fachgebiet≠ | Simulation | Entscheidungsfindung |
| Familie≠ | Process / pipeline | MCDM |
| Entstehungsjahr≠ | 1960s (formalised in literature through the 1980s–2000s) | 1949 |
| Urheber≠ | Kelton, Law & Sadowski (formalised methodology); SIMSCRIPT (Markowitz et al., 1963) and GPSS (Gordon, 1961) were pioneering tools | Metropolis, N., Ulam, S. |
| Typ≠ | Stochastic process simulation | Robustness wrapper — Monte Carlo uncertainty propagation |
| Wegweisende Quelle≠ | 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 ↗ |
| Aliasnamen≠ | DES, discrete event simulation, Kesikli Sistem Simülasyonu (Arena / AnyLogic tarzı) | — |
| Verwandt≠ | 4 | 0 |
| Zusammenfassung≠ | 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. |
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