https://github.com/jump-dev/clp.jl
A Julia interface to the Coin-OR Linear Programming solver (CLP)
https://github.com/jump-dev/clp.jl
julia jump-jl linear-programming
Last synced: 8 months ago
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A Julia interface to the Coin-OR Linear Programming solver (CLP)
- Host: GitHub
- URL: https://github.com/jump-dev/clp.jl
- Owner: jump-dev
- License: other
- Created: 2013-01-23T14:47:16.000Z (almost 13 years ago)
- Default Branch: master
- Last Pushed: 2024-12-29T23:00:32.000Z (about 1 year ago)
- Last Synced: 2025-05-12T06:22:52.837Z (8 months ago)
- Topics: julia, jump-jl, linear-programming
- Language: Julia
- Homepage: https://projects.coin-or.org/Clp
- Size: 271 KB
- Stars: 52
- Watchers: 9
- Forks: 25
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
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README
# Clp.jl
[](https://github.com/jump-dev/Clp.jl/actions?query=workflow%3ACI)
[](https://codecov.io/gh/jump-dev/Clp.jl)
[Clp.jl](https://github.com/jump-dev/Clp.jl) is a wrapper for the
[COIN-OR Linear Programming](https://projects.coin-or.org/Clp) solver.
The wrapper has two components:
* a thin wrapper around the complete C API
* an interface to [MathOptInterface](https://github.com/jump-dev/MathOptInterface.jl)
## 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](https://jump.dev/forum).
If you have a reproducible example of a bug, please [open a GitHub issue](https://github.com/jump-dev/Clp.jl/issues/new).
## License
`Clp.jl` is licensed under the [MIT License](https://github.com/jump-dev/Clp.jl/blob/master/LICENSE.md).
The underlying solver, [coin-or/Clp](https://github.com/coin-or/Clp), is
licensed under the [Eclipse public license](https://github.com/coin-or/Clp/blob/master/LICENSE).
## Installation
Install Clp using `Pkg.add`:
```julia
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](https://jump.dev/JuMP.jl/stable/developers/custom_solver_binaries/)
section of the JuMP documentation.
## Use with JuMP
To use Clp with JuMP, use `Clp.Optimizer`:
```julia
using JuMP, Clp
model = Model(Clp.Optimizer)
set_attribute(model, "LogLevel", 1)
set_attribute(model, "Algorithm", 4)
```
## MathOptInterface API
The Clp optimizer supports the following constraints and attributes.
List of supported objective functions:
* [`MOI.ObjectiveFunction{MOI.ScalarAffineFunction{Float64}}`](@ref)
List of supported variable types:
* [`MOI.Reals`](@ref)
List of supported constraint types:
* [`MOI.ScalarAffineFunction{Float64}`](@ref) in [`MOI.EqualTo{Float64}`](@ref)
* [`MOI.ScalarAffineFunction{Float64}`](@ref) in [`MOI.GreaterThan{Float64}`](@ref)
* [`MOI.ScalarAffineFunction{Float64}`](@ref) in [`MOI.Interval{Float64}`](@ref)
* [`MOI.ScalarAffineFunction{Float64}`](@ref) in [`MOI.LessThan{Float64}`](@ref)
* [`MOI.VariableIndex`](@ref) in [`MOI.EqualTo{Float64}`](@ref)
* [`MOI.VariableIndex`](@ref) in [`MOI.GreaterThan{Float64}`](@ref)
* [`MOI.VariableIndex`](@ref) in [`MOI.Interval{Float64}`](@ref)
* [`MOI.VariableIndex`](@ref) in [`MOI.LessThan{Float64}`](@ref)
List of supported model attributes:
* [`MOI.ObjectiveSense()`](@ref)
## Options
Options are, unfortunately, not well documented.
The following options are likely to be the most useful:
| Parameter | Example | Explanation |
| -------------------- | ------- | ------------------------------------------- |
| `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`) |
## C API
The C API can be accessed via `Clp.Clp_XXX` functions, where the names and
arguments are identical to the C API.