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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 MathOptInterface API.

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

Build Status codecov

Installation

The package 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 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(Clp.Optimizer)
set_optimizer_attribute(model, "LogLevel", 1)
set_optimizer_attribute(model, "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)

Solver options

The following options are available to get/set via JuMP.set_optimizer_attribute or MOI.RawParameter.

Parameter Default value Description
PrimalTolerance 1e-7 Primal feasibility tolerance
DualTolerance 1e-7 Dual feasibility tolerance
DualObjectiveLimit 1e308 When using dual simplex (where the objective is monotonically changing), terminate when the objective exceeds this limit
MaximumIterations 2147483647 Terminate after performing this number of simplex iterations
MaximumSeconds -1.0 Terminate after this many seconds have passed. A negative value means no time limit
LogLevel 1 Set to 1, 2, 3, or 4 for increasing output. Set to 0 to disable output
PresolveType 0 Set to 1 to disable presolve
SolveType 5 Solution method: dual simplex (0), primal simplex (1), sprint (2), barrier with crossover (3), barrier without crossover (4), automatic (5)
InfeasibleReturn 0 Set to 1 to return as soon as the problem is found to be infeasible (by default, an infeasibility proof is computed as well)
Scaling 3 0 -off, 1 equilibrium, 2 geometric, 3 auto, 4 dynamic(later)
Perturbation 100 switch on perturbation (50), automatic (100), don't try perturbing (102)