Comparar métodos

	Simulación Determinista de Eventos Discretos	Modelo de Markov determinista
Campo	Simulación	Simulación
Familia	Process / pipeline	Process / pipeline
Año de origen	1960s–present	1993
Autor original	Banks, J.; Carson, J. S.; Nelson, B. L. (codified); roots in 1960s simulation pioneers (Tocher, Conway)	Sonnenberg, F. A. & Beck, J. R.
Tipo	Simulation — deterministic event-driven model	Cohort state-transition model with fixed transition probabilities
Fuente seminal	Banks, J., Carson, J. S., Nelson, B. L., and Nicol, D. M. (2010). Discrete-Event System Simulation (5th ed.). Prentice Hall. ISBN: 9780136062127	Sonnenberg, F. A., & Beck, J. R. (1993). Markov models in medical decision making: a practical guide. Medical Decision Making, 13(4), 322–338.
Alias	Deterministic DES, Fixed-Input DES, Non-Stochastic Discrete-Event Simulation, Deterministic Event-Driven Simulation	DMM, Deterministic Markov Chain, Cohort Markov Model, Fixed-Parameter Markov Model
Relacionados	5	5
Resumen	Deterministic Discrete-Event Simulation (Deterministic DES) models a system as a sequence of events occurring at precise, pre-specified times using fixed input parameters. Unlike stochastic DES, no probability distributions are sampled; every arrival, service time, and resource availability is known in advance, making runs fully reproducible and producing a single definitive output trajectory.	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.