Linear Programming Simplex Method (Not in Base Package)

Determines the solution of a linear programming problem. Details

C is a vector describing the linear functional to maximize.
M is a matrix describing the different constraints.
B is a vector describing the right sides of the constraints inequalities.
maximum is the maximal value, if it exists, of x under the constraints.
X is the solution vector.
ticks is the time in milliseconds for the whole calculation.
error returns any error or warning condition from the VI. The nonexistence of a solution x leads to an error.

Linear Programming Simplex Method Details

The optimization problem cx = max! with the constraints x 0 and mx b.

Here

and M a k by n matrix. Now you must decide whether or not an optimal vector x does exist, and if so, determine this vector x. The solution of a linear programming problem is a two-step process. The first step transforms the original problem into a problem in restricted normal form (essentially without inequalities in the formulation). The second step consists of the solution of this restricted normal form problem.

Note  The previous formulation seems to be special. But there are many ways to reformulate terms. For instance, dx e is equivalent to –dx –e and, dx = e is equivalent to the combination dx e and –dx –e.