While HiGHS is ready to use today, you should be aware that it is still under active development. That means it might be slow or unstable on some problems. However, by reporting these problems you can help make HiGHS better!

To report a problem (e.g., incorrect results, or a crash of the solver), or make a suggestion for how to improve HiGHS, please file a GitHub issue.

If you use HiGHS from JuMP, use JuMP.write_to_file(model, "filename.mps") to write your model an MPS file, then upload the MPS file to https://gist.github.com and provide a link to the gist in the GitHub issue.

HiGHS.jl

HiGHS.jl is a wrapper for the HiGHS linear solver.

It has two components:

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

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

Installation

Minimum version requirement: HiGHS.jl requres at least Julia v1.3.

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.)

Use with JuMP

Pass HiGHS.Optimizer to JuMP.Model to create a JuMP model with HiGHS as the optimizer. Set options using set_optimizer_attribute.

using JuMP
import HiGHS
model = Model(HiGHS.Optimizer)
set_optimizer_attribute(model, "presolve", "on")
set_optimizer_attribute(model, "time_limit", 60.0)