The wrapper has two components:
- a thin wrapper around the complete C API
- an interface to MathOptInterface
This wrapper is maintained by the JuMP community and is not a COIN-OR project.
Clp.jl is licensed under the MIT License.
Install Clp using
import Pkg Pkg.add("Clp")
In addition to installing the Clp.jl package, this will also download and install the Clp binaries. You do not need to install Clp separately.
To use a custom binary, read the Custom solver binaries section of the JuMP documentation.
To use Clp with JuMP, use
using JuMP, Clp model = Model(Clp.Optimizer) set_attribute(model, "LogLevel", 1) set_attribute(model, "Algorithm", 4)
The Clp optimizer supports the following constraints and attributes.
List of supported objective functions:
List of supported variable types:
List of supported constraint types:
List of supported model attributes:
Options are, unfortunately, not well documented.
The following options are likely to be the most useful:
|Primal feasibility tolerance|
|Dual feasibility tolerance|
|When using dual simplex (where the objective is monotonically changing), terminate when the objective exceeds this limit|
|Terminate after performing this number of simplex iterations|
|Terminate after this many seconds have passed. A negative value means no time limit|
|Set to 1, 2, 3, or 4 for increasing output. Set to |
|Set to |
|Solution method: dual simplex (|
|Set to 1 to return as soon as the problem is found to be infeasible (by default, an infeasibility proof is computed as well)|
|switch on perturbation (|
The C API can be accessed via
Clp.Clp_XXX functions, where the names and arguments are identical to the C API.