HiGHS.jl

Build Status codecov

HiGHS.jl is a wrapper for the HiGHS solver.

It has two components:

Affiliation

This wrapper is maintained by the JuMP community and is not an official project of the HiGHS developers.

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

HiGHS.jl is licensed under the MIT License.

The underlying solver, ERGO-Code/HiGHS, is licensed under the MIT license.

Installation

Install HiGHS as follows:

import Pkg
Pkg.add("HiGHS")

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

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

Use with JuMP

To use HiGHS with JuMP, use HiGHS.Optimizer:

using JuMP, HiGHS
model = Model(HiGHS.Optimizer)
# Set options as needed, for example:
set_attribute(model, "presolve", "on")
set_attribute(model, "time_limit", 60.0)

MathOptInterface API

The HiGHS 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

See the HiGHS documentation for a full list of the available options.

C API

The C API can be accessed via HiGHS.Highs_xxx functions, where the names and arguments are identical to the C API.

Threads

HiGHS uses a global scheduler that is shared between threads.

Before changing the number of threads using MOI.Threads(), you must call Highs_resetGlobalScheduler(1):

using JuMP, HiGHS
model = Model(HiGHS.Optimizer)
Highs_resetGlobalScheduler(1)
set_attribute(model, MOI.NumberOfThreads(), 1)

If modifying the number of HiGHS threads across different Julia threads, be sure to read the docstring of Highs_resetGlobalScheduler. In particular, resetting the scheduler is not thread-safe.