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I tend to agree with your colleagues. Simio is probably not the fastest executing product, in part because it has so much built into it that other products don't have. When you do trivial models you don't see that, but when you do "real" models you will. Computer time is cheap; skilled modeler time is not. If you can do a typical project in 2 weeks in Simio versus 6 weeks with a competing project what is that 4 weeks of time saved worth? What is the benefit of producing answers (and the resulting savings) sooner? And what is it worth to be able to model something accurately that would have been approximated in other products? To take your assertion from above, what if Simio happened to take 6X (say 60 minutes versus 10 minutes) to replicate that typical project? In the worst case to do 30 reps would take 30 hours of unattended computer time versus 5 hours. Who cares? You are still seeing your results more than 3 weeks earlier with dramatically reduced effort. Given that Simio can use multiple processors and most competitors don't, on a common quad processor machine there is little difference (8 hours vs 5 hours). And if you take advantage of Simio's ability to use up to 16 external processors, then Simio can actually produce results in less than half the time (2 hours versus 5 hours). All of that is assuming that 6X figure you used is accurate on a real system model - which I tend to doubt. The point is, as a modeler my top concerns include: --Can I model the situation accurately enough to generate meaningful results? --How much skill and effort (my time) does it require to do so? --How long (calendar time) until I can provide an answer to my stakeholders? In most applications I feel that Simio provides the best answer to the above questions.

As you have discovered (and I discussed in my post above), running an experiment puts Simio in its fastest run mode possible. And in this mode it will automatically distribute the replications and scenarios across all of your processors/cores. This alone can provide dramatic speedups. If you have Team Edition, you can actually extend that to use spare processing power in your work group. So if you have 4 quad-processor machines available on your local network, you can run up to 16 simultaneous replications or scenarios. In terms of modeling, the most dramatic improvement you could make is to build your model at a lower level. The model you described is simple to model entirely in a single process with steps: (begin) - Seize - Delay - Release - Tally - (end) with the process triggered by a Timer element and using TallyStatistics elements for any token-related statistics like Time In System. You would not even need to create any entities, it could all be done using tokens which are smaller and faster. The process approach should be many times faster.

In the current version of Simio, there is no fixed relationship between simulated time and real time. The model will run as fast as possible given the contraints of the number of simulation events and related "work" being done. The two other things that most dramatically impact simulation speed are Trace (when trace is on it excuted slower) and Animation (3D animation with a low speed factor runs slower). We have plans to provide an Emulation product for use in training and testing. Before that product is created, we will add the capability for Simio to run in real time or any multiple of real time. Speed Factor can be used to speed or slow the animation. Its main purpose is to improve the quality of an animation by decreasing the factor. This also has the side effect of slowing the animation so you can see certain events more clearly. Conversely, if you increase the speed factor, the animation will run faster, but in doing so, certain events (like movement on a path) might become jumpy or too fast to observe. Fast-Forward can be used to temporarily disable animation to allow the model to execute much fsater. Running an Experiment provides the fastest execution possible. Not only is animation and user interaction turned off, but it will also take full advantage of all processors on a multiprocessor machine, often running 2-4 times faster.