The Feasibility Pump for finding a feasible solution (python) Symbolic Constraints in Integer Linear programming (C++) (MATLAB) The milp.m solver (needs lp.m from Matlab optimization toolbox) Simple branch&cut solver, part of COIN-OR (C++)Ĭallable library for solving mixed-integer linear programs, uses Clp as default LP solver (C) GNU LP library, B&B, dual/revised simplex, interior point, C, Windows-executables, Matlab interface, Java interface. Simplex/IPM, Matlab, AMPL, GAMS interfaces, student license The following simplex-based solvers allow some or all of the variables to be constrained to attain integer values all allow input inįramework for Constraint Integer Programming, links to CPLEX, SOPLEX, or CLP as LP solver (C)Ĭ source, various binaries, and interfacesī&C, using CPLEX, GLPK, or SOPLEX AMPL interface The description of the most widely used LP input formatĪ utility to convert this LP format to (and from) MPS Windows/Unix executablesĪ utility (extracted from lp_solve) to convert the simple LP format to (and from) MPSĪ general branch&cut library with mixed integer capability (C++) Some are listed here: plamĪ free MILP modeling environment using lp_solve as MILP solver and SWI-Prolog Several tools are necessary to deal with such problems. The LP-problem is often very high-dimensional. The general nonlinear problem (dense, sparse, nonsmooth, SIP)

Semidefinite and second-order cone programming The LP-problem, also mixed integer and stochastic

Infeasible points are shown in dark brown and the levels of f are shown in the feasible domain. The picture shows feasible domain and level sets for

Free download software pclp