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Simulação Estocástica de Filas×Simulação Estocástica de Eventos Discretos×
ÁreaSimulaçãoSimulação
FamíliaProcess / pipelineProcess / pipeline
Ano de origem19531960s–1970s
Autor originalKendall, D. G.Banks, Carson, Nelson, Nicol; Law, A. M.
TipoStochastic simulation — waiting-line system analysisStochastic simulation model
Fonte seminalKendall, 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 ↗Banks, J., Carson, J. S., Nelson, B. L., & Nicol, D. M. (2010). Discrete-Event System Simulation (5th ed.). Prentice Hall. ISBN: 9780136062127
Outros nomesSQS, Probabilistic Queueing Simulation, Stochastic Queue Modeling, Random Queueing SimulationStochastic DES, SDES, Probabilistic DES, Monte Carlo DES
Relacionados66
ResumoStochastic 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.Stochastic Discrete-Event Simulation (Stochastic DES) models complex systems by advancing simulated time from one discrete event to the next, drawing event durations and inter-arrival times from fitted probability distributions. It is the standard technique for analyzing queues, manufacturing lines, healthcare pathways, and logistics networks under uncertainty, producing output statistics with confidence intervals.
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ScholarGateComparar métodos: Stochastic Queueing Simulation · Stochastic Discrete-Event Simulation. Recuperado em 2026-06-15 de https://scholargate.app/pt/compare