HiGHS optimization solver: Difference between revisions

Revision as of 18:10, 13 May 2025

Revision as of 18:17, 13 May 2025

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'''HiGHS''' is open-source software to solve [[linear programming]] (LP), [[Integer programming|mixed-integer programming]] (MIP), and convex [[quadratic programming]] (QP) models.<ref name="hall-2020"/>

Written in [[C++]] and published under an [[MIT License|MIT]] license, HiGHS provides programming interfaces to [[C (programming language)|C]], [[Python (programming language)|Python]], [[Julia (programming language)|Julia]], [[Rust (programming language)|Rust]], [[R (programming language)|R]], [[JavaScript]], [[Fortran]], and [[C Sharp (programming language)|C#]]. It has no external dependencies. A{{nbsp}}convenient thin wrapper to Python is available via the {{url|https://pypi.org/project/highspy/|highspy}} [[Python Package Index|PyPI]] package. HiGHS is also callable via {{url|https://www[[NuGet]].<ref name="nuget.org/packages/Highs.Native/|nuget}}.-repo">

{{cite web

| title = Highs.Native

| url = https://nuget.org/packages/Highs.Native/

| access-date = 2025-05-13

}}

</ref>

Although generally single-threaded, some solver components can utilize multi-core architectures and, from {{URL|https://github.com/ERGO-Code/HiGHS/releases/tag/v1.10.0|Version 1.10.0}}, can run its first order LP solver on NVIDIA GPUs. HiGHS is designed to solve large-scale models and exploits [[sparse matrix|problem sparsity]]. Its performance relative to commercial and other open-source software is reviewed periodically using industry-standard [[Benchmark (computing)|benchmarks]].<ref name="mittelmann-benchmarks"/>