base on Linear optimization software # HiGHS - Linear optimization software <!--  --> [![Build Status][fast_build_svg]][fast_build_link] [![Build Status][linux_build_svg]][linux_build_link] [![Build Status][macos_build_svg]][macos_build_link] [![Build Status][windows_build_svg]][windows_build_link] \ [](https://conan.io/center/recipes/highs) \ [](https://pypi.python.org/pypi/highspy) [](https://pypi.python.org/pypi/highspy) \ [](https://www.nuget.org/packages/Highs.Native) [](https://www.nuget.org/packages/Highs.Native) [fast_build_svg]: https://github.com/ERGO-Code/HiGHS/actions/workflows/build-fast.yml/badge.svg [fast_build_link]: https://github.com/ERGO-Code/HiGHS/actions/workflows/build-fast.yml [linux_build_svg]: https://github.com/ERGO-Code/HiGHS/actions/workflows/build-linux.yml/badge.svg [linux_build_link]: https://github.com/ERGO-Code/HiGHS/actions/workflows/build-linux.yml [macos_build_svg]: https://github.com/ERGO-Code/HiGHS/actions/workflows/build-macos.yml/badge.svg [macos_build_link]: https://github.com/ERGO-Code/HiGHS/actions/workflows/build-macos.yml [windows_build_svg]: https://github.com/ERGO-Code/HiGHS/actions/workflows/build-windows.yml/badge.svg [windows_build_link]: https://github.com/ERGO-Code/HiGHS/actions/workflows/build-windows.yml - [About HiGHS](#about-highs) - [Documentation](#documentation) - [Installation](#installation) - [Build from source using CMake](#build-from-source-using-cmake) - [Build with Meson*](#build-with-meson) - [Build with Nix*](#build-with-nix) - [Precompiled binaries](#precompiled-binaries) - [Running HiGHS](#running-highs) - [Interfaces](#interfaces) - [Python](#python) - [C](#c) - [CSharp](#csharp) - [Fortran](#fortran) - [Reference](#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 [email protected]. ## 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](https://determinate.systems/posts/nix-run/), supposing you have installed [nix](https://nixos.org/download.html): ```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: --model_file file File of model to solve. --options_file file File containing HiGHS options. --read_solution_file file File of solution to read. --read_basis_file text File of initial basis to read. --write_model_file text File for writing out model. --solution_file text File for writing out solution. --write_basis_file 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" --run_crossover text Set run_crossover option to: "choose" "on" * default "off" --time_limit 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](https://ergo-code.github.io/HiGHS/stable/options/definitions/) 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 [email protected]. ### Python The python package `highspy` is a thin wrapper around HiGHS and is available on [PyPi](https://pypi.org/project/highspy/). 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](https://colab.research.google.com/drive/1JmHF53OYfU-0Sp9bzLw-D2TQyRABSjHb?usp=sharing) 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](https://link.springer.com/article/10.1007/s12532-017-0130-5) ", Assign "at most 3 tags" to the expected json: {"id":"13823","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"