Cbc.jl

Cbc.jl is a wrapper for the COIN-OR Branch and Cut (Cbc) solver.

The wrapper has two components:

• a thin wrapper around the complete C API
• an interface to MathOptInterface

Affiliation

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

Getting help

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.

License

Cbc.jl is licensed under the MIT License.

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

Installation

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.

Use with JuMP

To use Cbc with JuMP, use Cbc.Optimizer:

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

MathOptInterface API

The COIN Branch-and-Cut (Cbc) optimizer supports the following constraints and attributes.

List of supported objective functions:

• MOI.ObjectiveFunction{MOI.ScalarAffineFunction{Float64}}

List of supported variable types:

• MOI.Reals

List of supported constraint types:

• MOI.ScalarAffineFunction{Float64} in MOI.EqualTo{Float64}
• MOI.ScalarAffineFunction{Float64} in MOI.GreaterThan{Float64}
• MOI.ScalarAffineFunction{Float64} in MOI.Interval{Float64}
• MOI.ScalarAffineFunction{Float64} in MOI.LessThan{Float64}
• MOI.VariableIndex in MOI.EqualTo{Float64}
• MOI.VariableIndex in MOI.GreaterThan{Float64}
• MOI.VariableIndex in MOI.Integer
• MOI.VariableIndex in MOI.Interval{Float64}
• MOI.VariableIndex in MOI.LessThan{Float64}
• MOI.VariableIndex in MOI.ZeroOne
• MOI.VectorOfVariables in MOI.SOS1{Float64}
• MOI.VectorOfVariables in MOI.SOS2{Float64}

List of supported model attributes:

• Cbc.Status
• Cbc.SecondaryStatus
• MOI.DualStatus
• MOI.NodeCount
• MOI.NumberOfVariables
• MOI.ObjectiveBound
• MOI.ObjectiveSense
• MOI.ObjectiveValue
• MOI.PrimalStatus
• MOI.RelativeGap
• MOI.ResultCount
• MOI.SolveTimeSec
• MOI.TerminationStatus

List of supported optimizer attributes:

• Cbc.SetVariableNames
• MOI.AbsoluteGapTolerance
• MOI.NumberOfThreads
• MOI.RawOptimizerAttribute
• MOI.RelativeGapTolerance
• MOI.Silent
• MOI.SolverName
• MOI.SolverVersion
• MOI.TimeLimitSec

List of supported variable attributes:

• MOI.VariablePrimal
• MOI.VariablePrimalStart
• MOI.VariableName

List of supported constraint attributes:

• MOI.ConstraintPrimal

Options

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