Linear Programming sounds really difficult, but it’s
just a neat way to use math to find out the best way to do things – for
example, how many things to make or buy. It usually involves a system of linear inequalities, called constraints,
but in the end, we want to either maximize something (like profit) or
minimize something (like cost). Whatever we’re maximizing or
minimizing is called the objective function.
Bounded and Unbounded Regions:
With our Linear Programming examples, we’ll have a set of compound inequalities, and they will be bounded inequalities, meaning the inequalities will have both maximum and minimum values. (We’ll show examples below, but think of bounded meaning that you could draw a “circle” around the feasible region, which is the solution set to the inequalities).
Here are what some typical Systems of Linear Inequalities might look like in Linear Programming:
Video:
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