Salīdzināt metodes

	Simulācija rindās	Markov Model
Nozare	Simulācija	Simulācija
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	1909	1906
Autors	Agner Krarup Erlang	Andrei Markov
Tips	Stochastic simulation / analytical modeling	Probabilistic state-transition model
Pirmavots	Kleinrock, L. (1975). Queueing Systems, Volume 1: Theory. Wiley-Interscience, New York. ISBN: 978-0471491101	Norris, J. R. (1997). Markov Chains. Cambridge University Press, Cambridge. ISBN: 9780521633963
Citi nosaukumi	Queue Simulation, Queuing Theory Simulation, Waiting-Line Simulation, DES-Queue	Markov Chain, Discrete-Time Markov Chain, DTMC, Markov Process
Saistītās	6	5
Kopsavilkums	Queueing Simulation combines classical queueing theory with discrete-event simulation to model systems where entities arrive, wait for service, and depart. It predicts performance metrics such as average waiting time, queue length, and server utilization, enabling capacity planning and bottleneck identification across service, manufacturing, healthcare, and network systems.	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.