A large scale non-linear optimization library

An object-oriented algebraic modeling language in Python for structured optimization problems.

Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear)

CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT etc. It can be used from C++, Python or Matlab/Octave.

An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations

A light-weight, Eigen-based C++ library for trajectory optimization for legged robots.

With Uno, finally take full control of your SQP/barrier solver for nonlinearly constrained optimization

Represent trained machine learning models as Pyomo optimization formulations

A Julia interface to the NLopt nonlinear-optimization library

A solver for nonlinear programming with GPU support

HPC solver for nonlinear optimization problems

Data Structures for Optimization Models

MATLAB implementations of a variety of nonlinear programming algorithms.

A Julia interface to the Ipopt nonlinear solver

Proximal algorithms for nonsmooth optimization in Julia

Proximal operators for nonsmooth optimization in Julia

Model and solve optimal control problems in Julia, both on CPU and GPU.

Python-based algebraic modeling interface to GAMS

Toolbox for gradient-based and derivative-free non-convex constrained optimization with continuous and/or discrete variables.

A set of lightweight header-only template functions implementing commonly-used optimization methods on Riemannian manifolds and convex spaces.