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Stochastic Queueing Simulation×Simulacija Monte Karlo×
OblastSimulacijaDonošenje odluka
PorodicaProcess / pipelineMCDM
Godina nastanka19531949
TvoracKendall, D. G.Metropolis, N., Ulam, S.
TipStochastic simulation — waiting-line system analysisRobustness wrapper — Monte Carlo uncertainty propagation
Temeljni izvorKendall, 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 ↗Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
Drugi naziviSQS, Probabilistic Queueing Simulation, Stochastic Queue Modeling, Random Queueing Simulation
Srodne60
SažetakStochastic 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.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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ScholarGateUporedite metode: Stochastic Queueing Simulation · MONTE-CARLO-SIMULATION. Preuzeto 2026-06-15 sa https://scholargate.app/sr/compare