The choice of a simulation methodology is fundamentally driven by how a system’s state changes over time. Whether a process evolves in distinct steps or flows smoothly determines the entire structure of the model. This section will define the core concepts of system state variables and system classifications that form the basis for differentiating simulation models.

2.1. System State Variables

System State Variables are the set of data required to define the internal processes within a system at a specific point in time. The behavior of these variables is a key differentiator between simulation approaches:

• In a discrete-event model, the system state variables remain constant over intervals of time. Their values change only at defined, discontinuous points called “event times.”
• In a continuous model, the system state variables change continuously over time, with their behavior defined by the results of differential equations.

2.2. Core System Distinctions

The behavior of state variables leads to a fundamental classification of systems themselves. The following table outlines this core distinction.

These classifications provide the framework for understanding the unique principles and applications of each simulation model.