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	Policy Scenario Queueing Simulation	マルコフモデル
分野	シミュレーション	シミュレーション
系統	Process / pipeline	Process / pipeline
提唱年	1909 (queueing theory); scenario application from 1960s–1970s OR literature	1906
提唱者	Erlang, A. K. (foundation); generalized by operations research community	Andrei Markov
種類	Comparative simulation experiment	Probabilistic state-transition model
原典	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
別名	PSQS, policy queueing analysis, queueing policy comparison, scenario-based queueing model	Markov Chain, Discrete-Time Markov Chain, DTMC, Markov Process
関連	5	5
概要	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.