השוואת שיטות

	מודל מרקוב	סימולציית תורים
תחום	סימולציה	סימולציה
משפחה	Process / pipeline	Process / pipeline
שנת המקור	1906	1909
הוגה השיטה	Andrei Markov	Agner Krarup Erlang
סוג	Probabilistic state-transition model	Stochastic simulation / analytical modeling
מקור מכונן	Norris, J. R. (1997). Markov Chains. Cambridge University Press, Cambridge. ISBN: 9780521633963	Kleinrock, L. (1975). Queueing Systems, Volume 1: Theory. Wiley-Interscience, New York. ISBN: 978-0471491101
כינויים	Markov Chain, Discrete-Time Markov Chain, DTMC, Markov Process	Queue Simulation, Queuing Theory Simulation, Waiting-Line Simulation, DES-Queue
קשורות	5	6
תקציר	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.	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.