A standard linear maximisation problem is a problem of the form:

Maximise an objective function `z`(`x`_{1}, `x`_{2}, … `x`_{n}), subject to the values of the variables all being nonnegative and the `m` constraints `f`_{1}(`x`_{1}, `x`_{2}, … `x`_{n}) ≤ `a`_{1}, `f`_{2}(`x`_{1}, `x`_{2}, … `x`_{n}) ≤ `a`_{2}, `f`_{m}(`x`_{1}, `x`_{2}, … `x`_{n}) ≤ `a`_{m} all being satisfied, where the functions `z` and `f`_{i} are all linear combinations of their parameters with nonnegative coefficients.
The constraints describe a feasible region; the problem, then, is to find the point within the feasible region which gives a value for `z` no less than any other point in the region.