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Simulation should be easy and fun!

It may seem absurd to assert that stochastic discreteevent simulation should be easy. The technique is used to study systems exhibiting complex, timedependent behavior systems that cannot reasonably be studied by any other means. Where direct observation of the live system is impractical; where linear programming is insufficient; where queueing theory is inadequate; on these problems, we use simulation. Simulation enables us to study systems that are otherwise intractable. How then can it be easy? It is no part of my argument that simulation modeling is, or should be, trivial. I believe that simulation is one of the most demanding fields of the programmer’s art. I further believe that the construction of useful models requires special skills, quite independent of programming or project management ability, which will be increasingly in demand as mainstream computing comes to adopt more of the techniques developed by simulationists. It is my contention that one of the most important of these skills is the ability to keep things simple. Yes, real problems are messes, but it is not desirable to model them by creating an automated mess. Simplification is the essence of simulation. The whole modeling process consists in capturing the important elements of a system, and leaving out the rest. How many projects do you know that failed because they were too simple?