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Stochastic Discrete-Event Simulation×Simulacija Monte Karlo×
OblastSimulacijaDonošenje odluka
PorodicaProcess / pipelineMCDM
Godina nastanka1960s–1970s1949
TvoracBanks, Carson, Nelson, Nicol; Law, A. M.Metropolis, N., Ulam, S.
TipStochastic simulation modelRobustness wrapper — Monte Carlo uncertainty propagation
Temeljni izvorBanks, J., Carson, J. S., Nelson, B. L., & Nicol, D. M. (2010). Discrete-Event System Simulation (5th ed.). Prentice Hall. ISBN: 9780136062127Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
Drugi naziviStochastic DES, SDES, Probabilistic DES, Monte Carlo DES
Srodne60
SažetakStochastic 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.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 Discrete-Event Simulation · MONTE-CARLO-SIMULATION. Preuzeto 2026-06-18 sa https://scholargate.app/sr/compare