A natural extension of a discussion of simulation, given our existing understanding of optimization, is how the two methods can be used together. The basic question behind simulation optimization is:

Simulation provides the means by which to incorporate uncertainty into the evaluation of a specific decision, or a predetermined handful of such decisions; however, this question implies much greater scope. It suggests a formal search for the best decision across a very wide range of possible alternative decisions. For simulated variants, the term best takes into account not just the average/expected value of parameters describing the setting (as would be common in discrete optimization), but also the potentially extreme performance of outliers, be that good or bad. For system simulations, the best would necessarily need to further relate to performance as the result of a sequence of events where the interplay of initial guiding decisions, complicated by uncertainty, might be extremely difficult to assess without sufficient simulation runs. The follow-up question then is:

Here again we gain from the robustness of Excel and the availability of additional applications that capitalize on Excel's computational strengths.