In my last post on game theory, I said that you could find an optimal

probabilistic grand strategy for any two-player, simultaneous move, zero-sum game.

It's done through something called linear programming. But linear programming

is useful for a whole lot more than just game theory.

Linear programming is a general technique for solving a huge family of

optimization problems. It's incredibly useful for scheduling, resource

allocation, economic planning, financial portfolio management,

and a ton of of other, similar things.

The basic idea of it is that you have a linear function,

called an *objective function*, which describes what you'd like

to maximize. Then you have a collection of inequalities, describing

the constraints of the values in the objective function. The solution to

the problem is a set of assignments to the variables in the objective function

that provide a maximum.