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| Mô phỏng sự kiện rời rạc mạnh mẽ× | Mô hình Markov Mạnh mẽ× | |
|---|---|---|
| Lĩnh vực | Mô phỏng | Mô phỏng |
| Họ | Process / pipeline | Process / pipeline |
| Năm ra đời≠ | 1990s–2000s | 2005 |
| Người khởi xướng≠ | Banks, Carson, Nelson, Nicol (canonical DES); robust extensions: operations research community | Nilim & El Ghaoui; Iyengar |
| Loại≠ | Simulation with robustness analysis | Robust probabilistic model |
| Công trình gốc≠ | Banks, J., Carson, J. S., Nelson, B. L., & Nicol, D. M. (2010). Discrete-Event System Simulation (5th ed.). Prentice Hall. ISBN: 9780136062127 | Nilim, A., El Ghaoui, L. (2005). Robust control of Markov decision processes with uncertain transition matrices. Operations Research, 53(5), 780-798. DOI ↗ |
| Tên gọi khác | Robust DES, Uncertainty-Aware DES, Robust DEVS, Resilient Discrete-Event Simulation | RMM, Robust Markov Chain, Uncertain Markov Model, Interval Markov Model |
| Liên quan≠ | 6 | 4 |
| Tóm tắt≠ | 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. | A Robust Markov Model applies robustness principles to Markov chains by replacing single-point transition probabilities with uncertainty sets, then optimizing against the worst-case realization. Originally developed for robust Markov decision processes in operations research, it is used wherever transition rates are estimated with noise or are subject to adversarial variation, ensuring decisions remain safe across the full uncertainty range. |
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