If you're not terribly concerned about speed, I would try to understand a bit of optimization in general instead of linear programming (which is a special case).
I should probably do that sometime in my life, if not for this.
Any suggestions for how? Would the wikipedia page be enough?
I'm not sure what the best way is; I do recommend playing around in excel. Excel has some pretty decent optimization functionality built in (not hard to use either) and it's quite visual. The wikipedia page is a good start, you probably just need to know how to use some tools and some idea about how they work.
The two most traditional approaches to optimization are approximating the function of interest locally as 1) a hyper-plane 2) a quadratic function.
Looking at your list of backgrounds, the missing thing that jumps out at me is discrete math. You might also want to think about learning some differential equations, if it wasn't included in your calculus sequence.
I'm going to be competing in the Moody's Mega Math Challenge, and I was wondering if there was anything in particular I should brush up on.
If you look at previous problems, you can see that they're pretty varied. I want to know if there's any widely applicable math that we could study (in a fairly short amount of time) to maximize the odds of us knowing something useful for the competition.
Our math backgrounds include:
Edit:
I suppose we could also use a genetic algorithm, but those don't seem particularly suited to the competition.