Simulation and Modelling > Introduction > Classification of simulation models
Classification of simulation models
- Static vs. dynamic - A static simulation model, sometimes called Monte Carlo simulation, represents a system at particular point in time. A dynamic simulation model represents systems as they change over time.
- Deterministic vs. stochastic (contain randomness)- Deterministic models that produce the same exact results for a particular set of inputs but stochastic models present data and predicts outcomes that account for certain levels of unpredictability or randomness.
- Continuous vs. discrete- in a discrete model, the state variables change only at a countable number of points in time. These points in time are the ones at which the event occurs/change in state. But, in continuous, the state variables change in a continuous way, and not abruptly from one state to another (infinite number of states).
Most operational models are dynamic, stochastic, and discrete - will be called discrete-event simulation models