Function opencv::core::solve_lp

pub fn solve_lp(func: &Mat, constr: &Mat, z: &mut Mat) -> Result<i32>

Solve given (non-integer) linear programming problem using the Simplex Algorithm (Simplex Method).

What we mean here by "linear programming problem" (or LP problem, for short) can be formulated as:

Where is fixed 1-by-n row-vector, is fixed m-by-n matrix, is fixed m-by-1 column vector and is an arbitrary n-by-1 column vector, which satisfies the constraints.

Simplex algorithm is one of many algorithms that are designed to handle this sort of problems efficiently. Although it is not optimal in theoretical sense (there exist algorithms that can solve any problem written as above in polynomial time, while simplex method degenerates to exponential time for some special cases), it is well-studied, easy to implement and is shown to work well for real-life purposes.

The particular implementation is taken almost verbatim from Introduction to Algorithms, third edition by T. H. Cormen, C. E. Leiserson, R. L. Rivest and Clifford Stein. In particular, the Bland's rule http://en.wikipedia.org/wiki/Bland%27s_rule is used to prevent cycling.

Parameters

• Func: This row-vector corresponds to in the LP problem formulation (see above). It should contain 32- or 64-bit floating point numbers. As a convenience, column-vector may be also submitted, in the latter case it is understood to correspond to .
• Constr: m-by-n+1 matrix, whose rightmost column corresponds to in formulation above and the remaining to . It should contain 32- or 64-bit floating point numbers.
• z: The solution will be returned here as a column-vector - it corresponds to in the formulation above. It will contain 64-bit floating point numbers.

Returns

One of cv::SolveLPResult