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Management Support Systems
Notes 3. Test and validate the model: The simulation model must represent the system being
studied.
4. Design the simulation experiments: When the model has been proven valid, an experiment
is designed – how long to run the simulation (accuracy and cost?).
5. Conduct the experiments: involves issues ranging from random-number : generation to
result presentation.
6. Evaluate the results: The results must be interpreted – sensitivity analysis.
7. Implement the results: The chances of success are better because the manager is usually
more involved with the simulation process then other models.
The Process of Simulation is shown in the figure 5.4:
Figure 5.4: Simulation Process
Source: http://www.cs.ubbcluj.ro/~per/Dss/Dss_11.pdf
5.5.5 Simulation Types
The types of Simulation are:
1. Probabilistic Simulation: The independent variables are probabilistic:
Discrete distributions: A situation with a limited number of events (variables) that
can take on only a finite number of values.
Continuous distributions: Unlimited number of possible events that follow density
functions, such as the normal distribution.
2. Time Dependent Simulation: It is important to know the precise time of arrival.
3. Time Independent Simulation: It is not important to know exactly when the event occurred.
4. Object-oriented Simulation: SIMPROCESS: object-oriented process modeling tool that
lets the user create a simulation model by using screen-based objects. UML could be used
in practice for modeling complex, real-time systems.
5. Visual Simulation: The graphical display of computerized results, which may include
animation, is one of the most successful developments in computer-human interaction
and problem solving.
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