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| Robust Queueing Simulation× | Stohhastiline oote-liini simulatsioon× | |
|---|---|---|
| Valdkond | Simulatsioon | Simulatsioon |
| Perekond | Process / pipeline | Process / pipeline |
| Tekkeaasta≠ | 2000s–2018 | 1953 |
| Looja≠ | Whitt, W. and colleagues; Bertsimas, D. and colleagues | Kendall, D. G. |
| Tüüp≠ | Simulation with worst-case uncertainty propagation | Stochastic simulation — waiting-line system analysis |
| Algallikas≠ | Bertsimas, D., Natarajan, K., & Teo, C.-P. (2011). Distributionally robust optimization: A review. European Journal of Operational Research. link ↗ | Kendall, D. G. (1953). Stochastic processes occurring in the theory of queues and their analysis by the method of the imbedded Markov chain. The Annals of Mathematical Statistics, 24(3), 338–354. DOI ↗ |
| Rööpnimetused | RQS, Distributionally Robust Queueing, Robust Queue Simulation, Uncertainty-Aware Queueing Simulation | SQS, Probabilistic Queueing Simulation, Stochastic Queue Modeling, Random Queueing Simulation |
| Seotud | 6 | 6 |
| Kokkuvõte≠ | 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. | Stochastic Queueing Simulation models waiting-line systems where arrival and service processes follow probability distributions rather than fixed rates. By simulating thousands of random events, it estimates performance measures — mean waiting time, queue length, server utilization — under realistic uncertainty, making it the standard tool for designing and evaluating service systems from hospitals to call centers. |
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