विधियों की तुलना करें

	नीति परिदृश्य कतार सिमुलेशन	मार्कोव मॉडल
क्षेत्र	अनुकरण	अनुकरण
परिवार	Process / pipeline	Process / pipeline
उद्भव वर्ष	1909 (queueing theory); scenario application from 1960s–1970s OR literature	1906
प्रवर्तक	Erlang, A. K. (foundation); generalized by operations research community	Andrei Markov
प्रकार	Comparative simulation experiment	Probabilistic state-transition model
मौलिक स्रोत	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
उपनाम	PSQS, policy queueing analysis, queueing policy comparison, scenario-based queueing model	Markov Chain, Discrete-Time Markov Chain, DTMC, Markov Process
संबंधित	5	5
सारांश	Policy Scenario Queueing Simulation applies queueing theory and discrete-event simulation to evaluate two or more competing service or resource-allocation policies under realistic demand and capacity conditions. By holding the system structure constant and varying only the policy rules, analysts can directly compare throughput, waiting times, utilization, and equity outcomes before committing to real-world implementation.	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.