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LP

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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
lpSolve LGPL Michel Berkelaar Use URL or software channel for download and install lpsolve+Python binding. For Windows use *.exe files; for Linux: download lpsolve and its python wrapper (_source.tar.gz and _Python_source.tar.gz files from sourceforge), in subdirectory "lpsolve55" run "sh ccc", copy ./lpsolve55/bin/{your_arch}/liblpsolve55.so to /usr/lib or /usr/local/lib (former requires admin rights, latter requires you have LD_LIBRARY_PATH included the directory), then go to directory /extra/Python and run "python setup.py install" with admin rights.
pclp (since OO v. 0.31) MIT Translated from Octave code to Python and placed under MIT licence by Enzo Michelangeli with permission explicitly granted by the original author, Prof. Kazunobu Yoshida. Some Python cycles have been replaced by vectorization by Dmitrey, and possibility to use scipy.sparse matrices has been added. Unfortunately, both dense and sparse problems still run much slower (sometimes in several orders) than other LP solvers mentioned here, or even some converters (e.g. nlp:ipopt). Maybe, Unladen Swallow will improve the situation.
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
cvxopt_lp GPL3 Lieven Vandenberghe, Joachim Dahl requires CVXOPT installed
(since v. 0.33)
cplex
  • commercial
  • full version free for education
  • free 90-days trial with limitations up to 500 vars/cons
IBM (after ILOG acquisition) requires cplex and its Python API installed
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)
FuturePlans: CLP, mosek, GuRoBi, Xpress

See also:

  • MILP (Mixed-Integer Linear Problems)
  • SDP (Semidefinite Problems)
  • SOCP (Second-Order Cone Problems)
Retrieved from "http://openopt.org/LP"
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