quadprog#

swordfish.function.quadprog()#

Solve the following optimization problem with a quadratic objective function and a set of linear constraints.

\(\substack{\displaystyle{\min}\limits_x} \displaystyle{\frac{1}{2}}x^THx + f^T x\text{ such that}\begin{cases}A\cdot x\le b\\Aeq \cdot x=beq\end{cases}\)

The result is a 2-element tuple. The first element is the minimum value of the objective function. The second element is the value of x where the value of the objective function is minimized.

Parameters:
  • H (Constant) – A matrix.

  • f (Constant) – _description_

  • A (Constant, optional) – The coefficient matrix of linear inequality constraints.

  • b (Constant, optional) – The right-hand-side vector of the linear inequality constraint.

  • Aeq (Constant, optional) – A linear equality constraint coefficient matrix.

  • beq (Constant, optional) – The right-hand-side vector of the linear equality constraint.