Blog: Steps in a Simulation Study

Blog: Steps in a Simulation Study

A simulation is the imitation of the operation of a real world process or system over time.

The behaviour of the system as it evolves over time is studied by developing a simulation model.

This model usually takes the form of a set of assumptions concerning the operation of the system. These assumptions are expressed in mathematical, logical, and symbolic relationships between the entities, or objects of interest, of the system. Once developed and validated, a model can be used to investigate a wide variety of "what-if" questions about the real world system.

Steps in a Simulation Study:

1.Problem formulation:

Every study should begin with a statement of the problem. If the statement is provided by the policy makers, or those that have the problem, the analyst must ensure that the problem being described is clearly understood. If the problem is being developed by the analyst, it is important that the policy makers understand and agree with the formulation.

2.Setting of objectives and overall project plan:

The objective indicates the questions to be answered by simulation. At this point a determination should be made concerning whether simulation is the appropriate methodology for the problem as formulated and objectives as state. Assuming it is decided that simulation is appropriate; the overall project plan should include a statement of the alternative systems to be considered, and a method for evaluating the effectiveness of these alternatives. It should also include the plan for the study in terms of the number of people involve, the cost of the study, and the number of days required to accomplish each phase of work with the anticipated results at the end of each stage.

3.Model conceptualization:

The construction of a model of the system is problem as much art as science. The art of modelling is enhanced by an ability to abstract the essential features of a problem, to select and modify basic assumptions that characterize the system, and then to enrich and elaborate the model until a useful approximation results. Thus it is best to start with a simple model and build toward greater complexity. However, the model complexity need not exceed that required to accomplish the purposes for which the model is intended. It is not necessary to have a one-to-one mapping between the model and the real system.

4.Data collection:

There is a constant interplay between the construction of the model and the collection of the needed input data. As the complexity of the model changes, the required data elements may also change. Also, since data collection takes such a large portion of the total time required to perform a simulation, it necessary to begin it as early as possible, usually together with early stages of the model building.

5.Model translation:

Since most real world systems result in models that require a great deal of information storage and computation, the model must be entered into a computer-recognizable format. We use the term "program". The modeller must decide whether to program the model in a simulation language such as Arena, GPSS/H, SUMUL8, ProModel, AutoModel, CISM, and etc, or to use special-purpose simulation software.


Verification is refers to the process of ensuring that the model is free from logical errors; that it does what it is intended to do.

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