Clp
Interface to the Clp linear programming solver. Provides a complete interface to the low-level C API, as well as an implementation of the solver-independent MathProgSolverInterface for efficiently solving sequences of linear programs. The Cbc julia package is used to provide the binary dependencies; see that package's README for supported platforms and installation instructions.
Using with MathProgBase
Clp provides a solver object that can be passed to linprog in MathProgBase (and used to create instances of the solver-independent AbstractMathProgModel type):
using Clp
using MathProgBase
linprog(..., ClpSolver(Option1=value1,Option2=value2,...))see the MathProgBase documentation for further information.
Options are solver-dependent. The following options are the most useful (and well documented):
-
PrimalTolerance- primal feasibility tolerance (default 1e-7) -
DualTolerance- dual feasibility tolerance (default 1e-7) -
DualObjectiveLimit- when using dual simplex (where the objective is monotonically changing), terminate when the objective exceeds this limit -
MaximumIterations- terminate after performing this number of simplex iterations -
MaximumSeconds- terminate after this many seconds have passed -
LogLevel- set to 1, 2, 3, or 4 for increasing output (default 0) -
PresolveType- set to 1 to disable presolve -
SolveType- choose the solution method:- 0 - dual simplex
- 1 - primal simplex
- 3 - barrier with crossover to optimal basis
- 4 - barrier without crossover to optimal basis
- 5 - automatic
-
InfeasibleReturn- set to 1 to return as soon as the problem is found to be infeasible (by default, an infeasibility proof is computed as well)
Using the C interface
The low-level C interface is available in the ClpCInterface submodule:
using Clp.ClpCInterfaceUsing this interface is only recommended for advanced users. The Julia API is essentially a thin wrapper around the interface exported by Clp/src/Clp_C_Interface.h, which is documented in-line.