HiGHS - Linear optimization software

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• About HiGHS
• Documentation
• Installation
  • Build from source using CMake
  • Build with Meson*
  • Build with Nix*
  • Precompiled binaries
• Running HiGHS
• Interfaces
  • Python
  • C
  • CSharp
  • Fortran
• Reference

About HiGHS

HiGHS is a high performance serial and parallel solver for large scale sparse linear optimization problems of the form

$$ \min \quad \dfrac{1}{2}x^TQx + c^Tx \qquad \textrm{s.t.}~ \quad L \leq Ax \leq U; \quad l \leq x \leq u $$

where Q must be positive semi-definite and, if Q is zero, there may be a requirement that some of the variables take integer values. Thus HiGHS can solve linear programming (LP) problems, convex quadratic programming (QP) problems, and mixed integer programming (MIP) problems. It is mainly written in C++, but also has some C. It has been developed and tested on various Linux, MacOS and Windows installations. No third-party dependencies are required.

HiGHS has primal and dual revised simplex solvers, originally written by Qi Huangfu and further developed by Julian Hall. It also has an interior point solver for LP written by Lukas Schork, an active set solver for QP written by Michael Feldmeier, and a MIP solver written by Leona Gottwald. Other features have been added by Julian Hall and Ivet Galabova, who manages the software engineering of HiGHS and interfaces to C, C#, FORTRAN, Julia and Python.

Find out more about HiGHS at https://www.highs.dev.

Although HiGHS is freely available under the MIT license, we would be pleased to learn about users' experience and give advice via email sent to highsopt@gmail.com.

Documentation

Documentation is available at https://ergo-code.github.io/HiGHS/.

Installation

Build from source using CMake

HiGHS uses CMake as build system, and requires at least version 3.15. To generate build files in a new subdirectory called 'build', run:

shell cmake -S . -B build cmake --build build This installs the executable bin/highs and the library lib/highs.

To test whether the compilation was successful, change into the build directory and run

shell ctest More details on building with CMake can be found in HiGHS/cmake/README.md.

Build with Meson

As an alternative, HiGHS can be installed using the meson build interface: sh meson setup bbdir -Dwith_tests=True meson test -C bbdir The meson build files are provided by the community and are not officially supported by the HiGHS development team.

Build with Nix

There is a nix flake that provides the highs binary:

shell nix run .

You can even run without installing anything, supposing you have installed nix:

shell nix run github:ERGO-Code/HiGHS

The nix flake also provides the python package:

shell nix build .#highspy tree result/

And a devShell for testing it:

```shell nix develop .#highspy python

import highspy highspy.Highs() ```

The nix build files are provided by the community and are not officially supported by the HiGHS development team.

Precompiled binaries

Precompiled static executables are available for a variety of platforms at https://github.com/JuliaBinaryWrappers/HiGHSstatic_jll.jl/releases

These binaries are provided by the Julia community and are not officially supported by the HiGHS development team. If you have trouble using these libraries, please open a GitHub issue and tag @odow in your question.

See https://ergo-code.github.io/HiGHS/stable/installation/#Precompiled-Binaries.

Running HiGHS

HiGHS can read MPS files and (CPLEX) LP files, and the following command solves the model in ml.mps

shell highs ml.mps

Command line options

When HiGHS is run from the command line, some fundamental option values may be specified directly. Many more may be specified via a file. Formally, the usage is:

```shell $ bin/highs --help usage: ./bin/highs [options] [file]

options: --modelfile file File of model to solve. --optionsfile file File containing HiGHS options. --readsolutionfile file File of solution to read. --readbasisfile text File of initial basis to read. --writemodelfile text File for writing out model. --solutionfile text File for writing out solution. --writebasisfile text File for writing out final basis. --presolve text Set presolve option to: "choose" * default "on" "off" --solver text Set solver option to: "choose" * default "simplex" "ipm" --parallel text Set parallel option to: "choose" * default "on" "off" --runcrossover text Set runcrossover option to: "choose" "on" * default "off" --timelimit float Run time limit (seconds - double). --random_seed int Seed to initialize random number generation. --ranging text Compute cost, bound, RHS and basic solution ranging: "on" "off" * default -v, --version Print version. -h, --help Print help.

``` For a full list of options, see the options page of the documentation website.

Interfaces

There are HiGHS interfaces for C, C#, FORTRAN, and Python in HiGHS/highs/interfaces, with example driver files in HiGHS/examples/. More on language and modelling interfaces can be found at https://ergo-code.github.io/HiGHS/stable/interfaces/other/.

We are happy to give a reasonable level of support via email sent to highsopt@gmail.com.

Python

The python package highspy is a thin wrapper around HiGHS and is available on PyPi. It can be easily installed via pip by running

shell $ pip install highspy

Alternatively, highspy can be built from source. Download the HiGHS source code and run

shell pip install . from the root directory.

The HiGHS C++ library no longer needs to be separately installed. The python package highspy depends on the numpy package and numpy will be installed as well, if it is not already present.

The installation can be tested using the small example HiGHS/examples/call_highs_from_python_highspy.py.

The Google Colab Example Notebook also demonstrates how to call highspy.

C

The C API is in HiGHS/highs/interfaces/highs_c_api.h. It is included in the default build. For more details, check out the documentation website https://ergo-code.github.io/HiGHS/.

CSharp

The nuget package Highs.Native is on https://www.nuget.org, at https://www.nuget.org/packages/Highs.Native/.

It can be added to your C# project with dotnet

shell dotnet add package Highs.Native --version 1.11.0

The nuget package contains runtime libraries for

• win-x64
• win-x32
• linux-x64
• linux-arm64
• macos-x64
• macos-arm64

Details for building locally can be found in nuget/README.md.

Fortran

The Fortran API is in HiGHS/highs/interfaces/highs_fortran_api.f90. It is not included in the default build. For more details, check out the documentation website https://ergo-code.github.io/HiGHS/.

Reference

If you use HiGHS in an academic context, please acknowledge this and cite the following article.

Parallelizing the dual revised simplex method Q. Huangfu and J. A. J. Hall Mathematical Programming Computation, 10 (1), 119-142, 2018. DOI: 10.1007/s12532-017-0130-5