# stevengj/nlopt

library for nonlinear optimization, wrapping many algorithms for global and local, constrained or unconstrained, optimization

Repository: https://github.com/stevengj/nlopt
Canonical: https://ross.abutalabs.com/products/nlopt
Language: C
License: NOASSERTION
License Family: other
Last push: 2026-06-06T05:37:14+00:00

## Health v2 (maintenance only)
Score: 81/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 86, release rhythm 63, longevity 100
- inputs: {"age_days": 4754, "days_push": 88, "days_rel": 89, "gap_med": 93.0, "n_releases_24m": 5}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2267, forks 681 (observed 2026-08-28T04:06:32.840655+00:00)

## What it is
NLopt is a C library providing a unified interface to many free/open-source algorithms for nonlinear local and global optimization, with or without gradient information, supporting constrained and unconstrained problems. It offers bindings for numerous languages including C++, Python, Fortran, Julia, R, and Java.

## Use cases
- minimize a nonlinear objective function with constraints
- fit model parameters via least-squares optimization
- solve global optimization problems without gradients
- perform gradient-based local optimization in C or Python
- wrap multiple optimization algorithms behind one API

## When to choose
- you need a mature, multi-language nonlinear optimization library with many algorithm choices
- you need both gradient-based and derivative-free optimizers in one interface
- you work in C/C++, Python, Julia, or R and need constrained optimization

## When to avoid
- you need mixed-integer or discrete optimization
- you want a pure high-level Python experience like scipy.optimize with rich ecosystem integration
- you need machine-learning-specific optimizers such as SGD or Adam for neural networks

## Facets
- artifact type: library
- maturity: stable
- function: math, sdk
- domain: mathematics, data-science
- platform: cpp, python, cross-platform, jvm, rust
- tags: nonlinear-optimization, global-optimization, constrained-optimization, gradient-based, numerical-methods, scientific-computing, algorithms, julia

## Member repositories
- stevengj/nlopt (main) score 81

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:32.840655+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 2026-08-30T02:42:21.612861+00:00, confidence not recorded.
  - readme: https://github.com/stevengj/nlopt (fetched 2026-08-28T04:06:32.840655+00:00, sha 8b95e8a625de)
- Data as of 2026-08-30T08:39:29.467469+00:00.