LP

Linear Problems (LP)

$\mathbf{f^T x \to min,\ max}$

subjected to

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

$\mathbf{A x \le b}$

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

LP solvers connected to OpenOpt:

Solver	License	Made by	Info	Parameters
lpSolve	LGPL	Michel Berkelaar	use URL or software channel for download and install lpsolve+Python binding. Ensure liblpsolve55.so (maybe other version or extension for non-Linux OS) is included to OS library path. Run [sudo] lp_solve_5.5/extra/Python/build.bat (i.e. with root (admin) privileges)	scale = {1, 0, True, False} default: False
cvxopt_lp	GPL3	Lieven Vandenberghe, Joachim Dahl	requires CVXOPT installed
glpk	GPL	Andrew Makhorin	Requires installation glpk + CVXOPT. Ensure CVXOPT setup.py file has line BUILD_GLPK=1 or use software install/update channels like aptitude, apt-get etc
converter to nlp (premature)		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 is usually required (it's intended to be fixed in future versions)

See also: