A large scale non-linear optimization library
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Updated
Jul 28, 2024 - C++
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.
Package to call the NLopt nonlinear-optimization library from the Julia language
Represent trained machine learning models as Pyomo optimization formulations
A next-gen solver for optimization with nonconvex objective and constraints. Reimplements filterSQP and IPOPT (barrier) in a modern and generic way, and unlocks a variety of novel methods. Competitive against filterSQP, IPOPT, SNOPT, MINOS and CONOPT.
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
A solver for nonlinear programming
FelooPy: Efficient & Feature-Rich Integrated Decision Environment
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
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