Suppose that a chain of big-box retail stores is considering a rearrangement of the way that customers go through the check-out process, in hopes of processing customers more efficiently, helping them spend less time waiting in line, and keeping their business from being lost to more efficient competitors.
In this project, we'll write a simulation like this one. If you can write a simulation that models reality well enough that it can demonstrate how things would turn out in various scenarios, you might be able to more cheaply find the answer you're looking for - should I make this change or not? - and, if it turns out to be a positive one, you can proceed. But if the experimentation is too costly, you might never be willing to pay the cost of finding out whether the changes you're considering are worthwhile or not.Ĭomputers have a role to play in situations like this. Unfortunately, you don't always know if they'll yield those benefits without some experimentation. In business or scientific contexts, it's sometimes very costly to make changes to the way that you're doing things, yet sometimes the changes you consider might yield great benefits.