QP

Quadratic Problems (QP)

$\frac{1}{2}\mathbf{x}^T\mathbf{Hx} + \mathbf{f}^T \mathbf{x \rightarrow min}$

subjected to

$\mathbf{lb} \le \mathbf{x} \le \mathbf{ub}$

$\mathbf{A x} \le \mathbf{b}$

$\mathbf{A}_\mathbf{eq} \mathbf{x} = \mathbf{b}_\mathbf{eq}$

QP solvers connected to OpenOpt:

Solver	License	Made by	Info
cvxopt_qp	GPL3	Lieven Vandenberghe, Joachim Dahl	requires CVXOPT installed
converter to nlp		Dmitrey	Example: r = p.solve('nlp:ipopt', plot=1). Can handle x0. Recommended solvers (mb require installation, see NLP doc page): ipopt, algencan. For ralg reducing p.ftol and p.xtol sometimes is helpful