Simulation model

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A simulation model is a special model , the subject matter , content and representation of which is constructed for the purpose of simulation (construction process-oriented model definition, see model).

As usual, only those features of the system are modeled that are currently relevant for a specific problem to be solved. On the other hand, other features that are of lesser importance for the question are neglected.

For example, a crash test dummy can be viewed as a simulation model of the human body. With such a dummy , the focus is on certain anatomical features, while other features of the human body, such as the metabolism , are not modeled.

Simulation models are mainly implemented with the support of computers .

Differentiation of the simulation model types

purpose

If one differentiates between simulation models according to their purpose, then mostly according to descriptive and pragmatic-normative simulation models:

• Descriptive simulation models are used to study the behavior of systems, i.e. the description , explanation or prognosis . In most cases, the behavior of individual subsystems is known, but how they interact is unknown.
• In pragmatic-normative simulation models that will simulate a tool of planning for decision support used. In particular, a satisfactory fixation of decision variables plays a role here.

object

If one differentiates simulation models according to their subject, then mostly according to

• stochastic (model contains partly “random” influences) and
• deterministic simulation models (input data already clearly defined).

content

If one differentiates simulation models according to their content, then mostly according to

• event-driven (formal mapping of events, functions and status changes as well as the use of resources within a process) and
• Time-controlled models (formal mapping of elements that influence movement quantities, which update inventory quantities over time).

realization

Simulation models are implemented either as a continuous model (continuous time course), discrete model (discrete value range, step-by-step simulation of events) or as a hybrid model .

Phases of modeling

The procedure for modeling is as follows:

1. Problem
2. System study
3. Word model
4. mathematical model
5. Calculation model
6. Model validation