方法对比

	确定性马尔可夫模型	离散事件仿真 (DES)
领域	仿真	仿真
方法族	Process / pipeline	Process / pipeline
起源年份	1993	1960s (formalized); modern computational form from 1970s onward
提出者	Sonnenberg, F. A. & Beck, J. R.	Banks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s)
类型	Cohort state-transition model with fixed transition probabilities	Stochastic process simulation
开创性文献	Sonnenberg, F. A., & Beck, J. R. (1993). Markov models in medical decision making: a practical guide. Medical Decision Making, 13(4), 322–338.	Banks, J., Carson, J.S., Nelson, B.L. & Nicol, D.M. (2010). Discrete-Event System Simulation (5th ed.). Pearson. ISBN: 978-0136062127
别名	DMM, Deterministic Markov Chain, Cohort Markov Model, Fixed-Parameter Markov Model	DES, event-driven simulation, Ayrık Olay Simülasyonu (DES)
相关	5	4
摘要	A Deterministic Markov Model is a cohort-level state-transition model in which all transition probabilities, state utilities, and costs are assigned single fixed values and the model is solved analytically in a single pass. Widely used in health technology assessment, policy analysis, and operations research, it traces a hypothetical cohort through mutually exclusive health or system states over discrete time cycles, accumulating expected outcomes such as quality-adjusted life years (QALYs) or costs.	Discrete-Event Simulation (DES) is a computational modeling paradigm in which the state of a system changes only at a countable sequence of points in time — the events. Between events nothing changes, so the simulation clock jumps directly from one event to the next. Formalized through the foundational textbooks of Banks, Carson, Nelson and Nicol and of Law in the 1960s–2000s, DES has become the standard tool for analyzing queuing systems, healthcare patient flows, manufacturing lines, and logistics networks where entities move through resources over time.