# ERGO-Code/HiGHS

Linear optimization software

Repository: https://github.com/ERGO-Code/HiGHS
Canonical: https://ross.abutalabs.com/products/highs
Language: C++
License: MIT
License Family: permissive
Topics: parallel, linear-optimization, simplex, high-performance, interior-point-method, mixed-integer-programming, quadratic-programming
Last push: 2026-08-26T17:14:16+00:00

## Health v2 (maintenance only)
Score: 92/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 79, longevity 100
- inputs: {"age_days": 3081, "days_push": 7, "days_rel": 62, "gap_med": 65.0, "n_releases_24m": 11}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1803, forks 348 (observed 2026-08-28T04:05:38.289793+00:00)

## What it is
HiGHS is a high-performance open-source solver for large-scale sparse linear optimization problems, supporting linear programming (LP), convex quadratic programming (QP), and mixed integer programming (MIP). Written primarily in C++ with no third-party dependencies, it offers serial and parallel primal/dual simplex and interior point solvers, plus interfaces for Python, C, C#, and Fortran.

## Use cases
- solve large-scale linear programming problems
- solve mixed integer programming models
- solve convex quadratic programming problems
- embed an LP/MIP solver in a C++ application
- solve optimization problems from Python via highspy
- run a high-performance simplex or interior point solver

## When to choose
- you need a free, dependency-free LP/QP/MIP solver with high performance
- you want bindings for Python, C, C#, or Fortran
- you need serial or parallel simplex and interior point methods
- you want an MIT-licensed alternative to commercial solvers

## When to avoid
- you need nonlinear (non-quadratic) optimization
- you need stochastic or conic optimization
- you require commercial-grade support guarantees

## Facets
- artifact type: library
- maturity: active
- function: math
- domain: mathematics
- platform: windows, cpp, python, cross-platform
- tags: linear-programming, simplex, interior-point-method, mixed-integer-programming, quadratic-programming, solver, high-performance, parallel, optimization, algorithms, operations-research, linux, macos

## Member repositories
- ERGO-Code/HiGHS (main) score 92

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:38.289793+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:21:51.040843+00:00, confidence not recorded.
  - readme: https://github.com/ERGO-Code/HiGHS (fetched 2026-08-28T04:05:38.289793+00:00, sha 5d46b1634440)
- Data as of 2026-08-30T08:39:29.467469+00:00.