{"adoption": {"forks": 348, "observed_at": "2026-08-28T04:05:38.289793+00:00", "stars": 1803}, "canonical_url": "https://ross.abutalabs.com/products/highs", "card": {"archived": false, "artifact_type": "library", "description": "Linear optimization software", "domain": ["mathematics"], "enriched": true, "function": ["math"], "health_score": 99, "homepage": null, "language": "C++", "license": "MIT", "license_family": "permissive", "maturity": "active", "member_repos": ["ERGO-Code/HiGHS"], "name": "ERGO-Code/HiGHS", "platform": ["windows", "cpp", "python", "cross-platform"], "pushed_at": "2026-08-26T17:14:16+00:00", "repo": "ERGO-Code/HiGHS", "stars": 1803, "tags": ["linear-programming", "simplex", "interior-point-method", "mixed-integer-programming", "quadratic-programming", "solver", "high-performance", "parallel", "optimization", "algorithms", "operations-research", "linux", "macos"], "topics": ["parallel", "linear-optimization", "simplex", "high-performance", "interior-point-method", "mixed-integer-programming", "quadratic-programming"], "urls": [], "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"], "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.", "when_to_avoid": ["you need nonlinear (non-quadratic) optimization", "you need stochastic or conic optimization", "you require commercial-grade support guarantees"], "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"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/highs", "repo": "ERGO-Code/HiGHS", "role": "main", "score": 92}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:05:38.289793+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-30T03:21:51.040843+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "5d46b1634440986e60560c22842138ddc67d4b800275d4e9d0b5959da57c83fe", "fetched_at": "2026-08-28T04:05:38.289793+00:00", "kind": "readme", "missing": false, "url": "https://github.com/ERGO-Code/HiGHS"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:05:38.289793+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-30T03:21:51.040843+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "5d46b1634440986e60560c22842138ddc67d4b800275d4e9d0b5959da57c83fe", "fetched_at": "2026-08-28T04:05:38.289793+00:00", "kind": "readme", "missing": false, "url": "https://github.com/ERGO-Code/HiGHS"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-30T03:21:51.040843+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "5d46b1634440986e60560c22842138ddc67d4b800275d4e9d0b5959da57c83fe", "fetched_at": "2026-08-28T04:05:38.289793+00:00", "kind": "readme", "missing": false, "url": "https://github.com/ERGO-Code/HiGHS"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:05:38.289793+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:05:38.289793+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:05:38.289793+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-30T03:21:51.040843+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "5d46b1634440986e60560c22842138ddc67d4b800275d4e9d0b5959da57c83fe", "fetched_at": "2026-08-28T04:05:38.289793+00:00", "kind": "readme", "missing": false, "url": "https://github.com/ERGO-Code/HiGHS"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:05:38.289793+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:05:38.289793+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-30T03:21:51.040843+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "5d46b1634440986e60560c22842138ddc67d4b800275d4e9d0b5959da57c83fe", "fetched_at": "2026-08-28T04:05:38.289793+00:00", "kind": "readme", "missing": false, "url": "https://github.com/ERGO-Code/HiGHS"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:05:38.289793+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:05:38.289793+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:05:38.289793+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-30T03:21:51.040843+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "5d46b1634440986e60560c22842138ddc67d4b800275d4e9d0b5959da57c83fe", "fetched_at": "2026-08-28T04:05:38.289793+00:00", "kind": "readme", "missing": false, "url": "https://github.com/ERGO-Code/HiGHS"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:05:38.289793+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:05:38.289793+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-30T03:21:51.040843+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "5d46b1634440986e60560c22842138ddc67d4b800275d4e9d0b5959da57c83fe", "fetched_at": "2026-08-28T04:05:38.289793+00:00", "kind": "readme", "missing": false, "url": "https://github.com/ERGO-Code/HiGHS"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-30T03:21:51.040843+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "5d46b1634440986e60560c22842138ddc67d4b800275d4e9d0b5959da57c83fe", "fetched_at": "2026-08-28T04:05:38.289793+00:00", "kind": "readme", "missing": false, "url": "https://github.com/ERGO-Code/HiGHS"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-30T03:21:51.040843+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "5d46b1634440986e60560c22842138ddc67d4b800275d4e9d0b5959da57c83fe", "fetched_at": "2026-08-28T04:05:38.289793+00:00", "kind": "readme", "missing": false, "url": "https://github.com/ERGO-Code/HiGHS"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-30T03:21:51.040843+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "5d46b1634440986e60560c22842138ddc67d4b800275d4e9d0b5959da57c83fe", "fetched_at": "2026-08-28T04:05:38.289793+00:00", "kind": "readme", "missing": false, "url": "https://github.com/ERGO-Code/HiGHS"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 99, "longevity": 100, "rhythm": 79}, "computed_at": "2026-09-02T17:46:02.011165+00:00", "flags": [], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 3081, "days_push": 7, "days_rel": 62, "gap_med": 65.0, "n_releases_24m": 11}, "score": 92, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}