ABSTRACT
This chapter presents an overview of the major types of simulation models with simple illustrations. The systems and/or their models can be discrete, continuous, or a combination. The essential difference in modeling is how the simulation time is advanced. Continuous systems modeling methods such as system dynamics always advance time with a constant delta (dt), a fixed time slice. Models may be deterministic (having no probabilistic variables) or stochastic (including probabilistic variables). Few engineering applications are wholly deterministic. When a model has probabilistic variables, each run can have a different outcome constituting an estimate of the model characteristics. Dynamism in discrete systems is caused by the movement of entities which results in the occurrence of events that change the system state over time. Auxiliary operations used in discrete event modeling include handling and utilization of variables, manipulation of entities (e.g. transfer, delete, copy), file operations and others. Custom user variables may be specified along with default system variables.
