gemseo / problems / scalable / parametric / core

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quadratic_programming_problem module

A quadratic programming (QP) problem.

class gemseo.problems.scalable.parametric.core.quadratic_programming_problem.QuadraticProgrammingProblem(Q, c, d, A, b)

Bases: NamedTuple

A quadratic programming (QP) problem.

Minimize \(0.5x^TQx + c^Tx + d\) with respect to \(x\) under the linear constraints \(Ax-b <= 0\).

Create new instance of QuadraticProgrammingProblem(Q, c, d, A, b)

Parameters:

• Q (ndarray[Any, dtype[float]]) –

• c (ndarray[Any, dtype[float]]) –

• d (ndarray[Any, dtype[float]]) –

• A (ndarray[Any, dtype[float]]) –

• b (ndarray[Any, dtype[float]]) –

count(value, /)

Return number of occurrences of value.

index(value, start=0, stop=9223372036854775807, /)

Return first index of value.

Raises ValueError if the value is not present.

A: ndarray[Any, dtype[float]]

The matrix \(A\) of the constraint function \(Ax-b\).

Q: ndarray[Any, dtype[float]]

The matrix \(Q\) of the objective function \(0.5x^TQx + c^Tx + d\).

This matrix must be symmetric.

b: ndarray[Any, dtype[float]]

The matrix \(b\) of the constraint function \(Ax-b\).

c: ndarray[Any, dtype[float]]

The matrix \(c\) of the objective function \(0.5x^TQx + c^Tx + d\).

d: ndarray[Any, dtype[float]]

The matrix \(d\) of the objective function \(0.5x^TQx + c^Tx + d\).