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COIN-OR Linear Programming Interface (Clp.jl)

Clp.jl is an interface to the COIN-OR Linear Programming solver. It provides a complete interface to the low-level C API, as well as an implementation of the solver-independent MathProgBase and MathOptInterface API's.

Note: This wrapper is maintained by the JuliaOpt community and is not a COIN-OR project.

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Installation

The package is registered in METADATA.jl and so can be installed with Pkg.add.

julia> import Pkg; Pkg.add("Clp")

Clp.jl will use BinaryProvider.jl to automatically install the Clp binaries. This should work for both the official Julia binaries from https://julialang.org/downloads/ and source-builds.

Custom Installation

To install custom built Clp binaries set the environmental variable JULIA_CLP_LIBRARY_PATH and call import Pkg; Pkg.build("Clp"). For instance, if the libraries are installed in /opt/lib, then call

ENV["JULIA_CLP_LIBRARY_PATH"] = "/opt/lib"
import Pkg; Pkg.build("Clp")

If you do not want BinaryProvider to download the default binaries on install, set JULIA_CLP_LIBRARY_PATH before calling import Pkg; Pkg.add("Clp").

To switch back to the default binaries clear JULIA_CLP_LIBRARY_PATH and call import Pkg; Pkg.build("Clp").

Using with JuMP

Due to some restrictions in Clp's C api, the Clp's MathOptInterface wrapper does not support directly modifying a problem after it has been created, e.g., changing variable bounds or modifying constraints coefficients.

Therefore, we highly recommend that you use the Clp.jl package with higher-level package such as JuMP.jl. This can be done with following syntax:

using JuMP, Clp

model = Model(with_optimizer(Clp.Optimizer, LogLevel=1, Algorithm=4))

See the list of options below.

Furthermore, the following features are not supported:

  • Querying the dual bound via JuMP.objective_bound (not in the C API)
  • Setting a time limit (the C API behaves inconsistently, see #65)
  • Setting the number of threads used (not in the C API)
  • Quadratic objective (not supported yet)
  • Querying infeasibility certificates (bug in Clp)

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 list of options below, and the MathProgBase documentation for further information.

Using the C interface

The low-level C interface is available in the ClpCInterface submodule:

using Clp.ClpCInterface

Using 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.

Solver options

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)