方法对比
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| 鲁棒排队仿真× | 蒙特卡洛模拟× | |
|---|---|---|
| 领域≠ | 仿真 | 决策 |
| 方法族≠ | Process / pipeline | MCDM |
| 起源年份≠ | 2000s–2018 | 1949 |
| 提出者≠ | Whitt, W. and colleagues; Bertsimas, D. and colleagues | Metropolis, N., Ulam, S. |
| 类型≠ | Simulation with worst-case uncertainty propagation | Robustness wrapper — Monte Carlo uncertainty propagation |
| 开创性文献≠ | Bertsimas, D., Natarajan, K., & Teo, C.-P. (2011). Distributionally robust optimization: A review. European Journal of Operational Research. link ↗ | Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗ |
| 别名≠ | RQS, Distributionally Robust Queueing, Robust Queue Simulation, Uncertainty-Aware Queueing Simulation | — |
| 相关≠ | 6 | 0 |
| 摘要≠ | Robust Queueing Simulation integrates robustness analysis into queueing system simulation by considering worst-case or uncertainty-set-driven scenarios for arrival rates, service distributions, and queue disciplines. It produces performance guarantees that hold across an entire family of plausible input distributions, making it essential for risk-sensitive service system design. | 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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