Decisions for Simulating
Completing the required steps of a simulation study establishes the likelihood of the study's success. Although knowing the basic steps in the simulation study is important, it is equally important to realize that not every problem should be solved using simulation. In the past, simulation required the specialized training of programmers and analysts dedicated to very large and complex projects. Now, due to the large number of software available, simulation at times is used inappropriately by individuals lacking the sufficient training and experience. When simulation is applied inappropriately, the study will not produce meaningful results. The failure to achieve the desired goals of the simulation study may induce blaming the simulation approach itself when in fact the cause of the failure lies in the inappropriate application of simulation
To recognize if simulation is the correct approach to solving a particular problem, four items should be evaluated before deciding to conduct the study:
- Type of Problem
- Availability of Resources
- Costs
- Availability of Data
Type of Problem: If a problem can be solved by common sense or analytically, the use of simulation is unnecessary. Additionally, using algorithms and mathematical equations may be faster and less expensive than simulating. Also, if the problem can be solved by performing direct experiments on the system to be evaluated, then conducting direct experiments may be more desirable than simulating. To illustrate, recently the UH Transportation Department conducted field studies on expanding the campus shuttle system. The department used their own personnel and vehicles to perform the experiment during the weekend. In contrast, developing the simulation model for the shuttle system took one student several weeks to complete. However, one factor to consider when performing directing experiments is the degree in which the real system will be disturbed. If a high degree of disruption to the real system will occur, then another approach may be necessary.The real system itself plays another factor in deciding to simulate. If the system is too complex, cannot be defined, and not understandable then simulation will not produce meaningful results. This situation often occurs when human behavior is involved.
Availability of Resources: People and time are the determining resources for conducting a simulation study. An experienced analyst is the most important resource since such a person has the ability and experience to determine both the model's appropriate level of detail and how to verify and validate the model. Without a trained simulator, the wrong model may be developed which produces unreliable results. Additionally, the allocation of time should not be so limited so as to force the simulator to take shortcuts in designing the model. The schedule should allow enough time for the implementation of any necessary changes and for verification and validation to take place if the results are to be meaningful.
Costs: Cost considerations should be given for each step in the simulation process, purchasing simulation software if not already available, and computer resources. Obviously if these costs exceed the potential savings in altering the current system, then simulation should not be pursued.
Availability of Data: The necessary data should be identified and located, and if the data does not exist, then the data should be collectible. If the data does not exist and cannot be collected, then continuing with the simulation study will eventually yield unreliable and useless results. The simulation output cannot be compared to the real system's performance, which is vital for verifying and validating the model.
