Awesome

Cbc.jl

The wrapper has two components:

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

If you need help, please ask a question on the JuMP community forum.

If you have a reproducible example of a bug, please open a GitHub issue.

Cbc.jl is licensed under the MIT License.

The underlying solver, coin-or/Cbc, is licensed under the Eclipse public license.

Install Cbc using Pkg.add:

import Pkg
Pkg.add("Cbc")

In addition to installing the Cbc.jl package, this will also download and install the Cbc binaries. You do not need to install Cbc separately.

To use a custom binary, read the Custom solver binaries section of the JuMP documentation.

To use Cbc with JuMP, use Cbc.Optimizer:

using JuMP, Cbc
model = Model(Cbc.Optimizer)
set_attribute(model, "logLevel", 1)

The COIN Branch-and-Cut (Cbc) 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:

List of supported optimizer attributes:

List of supported variable attributes:

List of supported constraint attributes:

Options are, unfortunately, not well documented.

The following options are likely to be the most useful:

Parameter	Example	Explanation
`seconds`	`60.0`	Solution timeout limit
`logLevel`	`2`	Set to 0 to disable solution output
`maxSolutions`	`1`	Terminate after this many feasible solutions have been found
`maxNodes`	`1`	Terminate after this many branch-and-bound nodes have been evaluated
`allowableGap`	`0.05`	Terminate after optimality gap is less than this value (on an absolute scale)
`ratioGap`	`0.05`	Terminate after optimality gap is smaller than this relative fraction
`threads`	`1`	Set the number of threads to use for parallel branch & bound

The complete list of parameters can be found by running the cbc executable and typing ? at the prompt.

Start the cbc executable from Julia as follows:

using Cbc_jll
Cbc_jll.cbc() do exe
    run(`$(exe)`)
end