Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.

Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.

Constrained optimization toolkit for PyTorch

Incremental Potential Contact (IPC) is for robust and accurate time stepping of nonlinear elastodynamics. IPC guarantees intersection- and inversion-free trajectories regardless of materials, time-step sizes, velocities, or deformation severity.

Generalized and Efficient Blackbox Optimization System

NMFLibrary: Non-negative Matrix Factorization (NMF) Library: Version 2.1

PRIMA is a package for solving general nonlinear optimization problems without using derivatives. It provides the reference implementation for Powell's derivative-free optimization methods, i.e., COBYLA, UOBYQA, NEWUOA, BOBYQA, and LINCOA. PRIMA means Reference Implementation for Powell's methods with Modernization and Amelioration, P for Powell.

OptCuts, a new parameterization algorithm, jointly optimizes arbitrary embeddings for seam quality and distortion. OptCuts requires no parameter tuning; automatically generating mappings that minimize seam-lengths while satisfying user-requested distortion bounds.

Generic Constraint Development Environment

High-performance metaheuristics for optimization coded purely in Julia.

HPC solver for nonlinear optimization problems

Source Codes for Codimensional Incremental Potential Contact (C-IPC)

Robotics tools in C++11. Implements soft real time arm drivers for Kuka LBR iiwa plus V-REP, ROS, Constrained Optimization based planning, Hand Eye Calibration and Inverse Kinematics integration.

A next-gen solver for optimization with nonconvex objective and constraints. Reimplements filterSQP (SQP) and IPOPT (barrier/interior-point method) in a modern and modular way, and unlocks methods never seen before. Competitive against filterSQP, IPOPT, SNOPT, MINOS and CONOPT.

A general-purpose, deep learning-first library for constrained optimization in PyTorch

A compact Constrained Model Predictive Control (MPC) library with Active Set based Quadratic Programming (QP) solver for Teensy4/Arduino system (or any real time embedded system in general)

Powell's Derivative-Free Optimization solvers.

Modern Fortran Edition of the SLSQP Optimizer

Generalized and Efficient Blackbox Optimization System.

The Constrained and Unconstrained Testing Environment with safe threads (CUTEst) for optimization software