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	Stochastická simulácia obslužných procesov	Markovov model
Odbor	Simulácia	Simulácia
Rodina	Process / pipeline	Process / pipeline
Rok vzniku	1953	1906
Tvorca	Kendall, D. G.	Andrei Markov
Typ	Stochastic simulation — waiting-line system analysis	Probabilistic state-transition model
Pôvodný zdroj	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.	Norris, J. R. (1997). Markov Chains. Cambridge University Press, Cambridge. ISBN: 9780521633963
Ďalšie názvy	SQS, Probabilistic Queueing Simulation, Stochastic Queue Modeling, Random Queueing Simulation	Markov Chain, Discrete-Time Markov Chain, DTMC, Markov Process
Príbuzné	6	5
Zhrnutie	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.	A Markov Model represents a system as a finite set of states and specifies the probability of moving from one state to another at each time step. By capturing only the current state — not the full history — it enables tractable analysis of complex dynamic processes across health economics, engineering reliability, operations research, and social-science modeling.