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Stokastisk kösimulering – Probabilistisk modellering av kösystem×Stokastisk diskret händelsessimulering×
ÄmnesområdeSimuleringSimulering
FamiljProcess / pipelineProcess / pipeline
Ursprungsår19531960s–1970s
UpphovspersonKendall, D. G.Banks, Carson, Nelson, Nicol; Law, A. M.
TypStochastic simulation — waiting-line system analysisStochastic simulation model
UrsprungskällaKendall, 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
AliasSQS, Probabilistic Queueing Simulation, Stochastic Queue Modeling, Random Queueing SimulationStochastic DES, SDES, Probabilistic DES, Monte Carlo DES
Närliggande66
SammanfattningStochastic 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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ScholarGateJämför metoder: Stochastic Queueing Simulation · Stochastic Discrete-Event Simulation. Hämtad 2026-06-17 från https://scholargate.app/sv/compare