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A large scale non-linear optimization library
Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear)
An object-oriented algebraic modeling language in Python for structured optimization problems.
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.
A next-gen 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
HPC solver for nonlinear optimization problems
A solver for nonlinear programming with GPU support
Data Structures for Optimization Models
MATLAB implementations of a variety of nonlinear programming algorithms.
A Julia interface to the Ipopt nonlinear solver
Proximal operators for nonsmooth optimization in Julia
Proximal algorithms for nonsmooth optimization in Julia
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.
Optimization models using various solvers
