Comparer des méthodes

	Simulation Robuste de Files d'Attente	Simulation stochastique de files d'attente
Domaine	Simulation	Simulation
Famille	Process / pipeline	Process / pipeline
Année d'origine	2000s–2018	1953
Auteur d'origine	Whitt, W. and colleagues; Bertsimas, D. and colleagues	Kendall, D. G.
Type	Simulation with worst-case uncertainty propagation	Stochastic simulation — waiting-line system analysis
Source fondatrice	Bertsimas, D., Natarajan, K., & Teo, C.-P. (2011). Distributionally robust optimization: A review. European Journal of Operational Research.	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.
Alias	RQS, Distributionally Robust Queueing, Robust Queue Simulation, Uncertainty-Aware Queueing Simulation	SQS, Probabilistic Queueing Simulation, Stochastic Queue Modeling, Random Queueing Simulation
Apparentées	6	6
Résumé	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.