There are 16 repositories under constrained-optimization topic.
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.
a lightweight header-only C++17 library of numerical optimization methods for (un-)constrained nonlinear functions and expression templates
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.
Towards Generalized and Efficient Blackbox Optimization System/Package (KDD 2021 & JMLR 2024)
A highly customizable SQP & barrier solver for nonlinearly constrained optimization
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.
NMFLibrary: Non-negative Matrix Factorization (NMF) Library: Version 2.1
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.
High-performance metaheuristics for optimization coded purely in Julia.
A curated collection of Python examples for optimization-based solid simulation, emphasizing algorithmic convergence, penetration-free, and inversion-free conditions, designed for readability and understanding.
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 general-purpose, deep learning-first library for constrained optimization in PyTorch
The Constrained and Unconstrained Testing Environment with safe threads (CUTEst) for optimization software
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)
Modern Fortran Edition of the SLSQP Optimizer
A curated set of C++ examples for optimization-based elastodynamic contact simulation using CUDA, emphasizing algorithmic convergence, penetration-free, and inversion-free conditions. Designed for readability and understanding, this tutorial helps beginners learn how to write simple GPU code for efficient solid simulations.
Generalized and Efficient Blackbox Optimization System.
An interior-point method written in python for solving constrained and unconstrained nonlinear optimization problems.
Constrained Differential Dynamic Programming Solver for Trajectory Optimization and Model Predictive Control
Safe Pontryagin Differentiable Programming (Safe PDP) is a new theoretical and algorithmic safe differentiable framework to solve a broad class of safety-critical learning and control tasks.
Riemannian stochastic optimization algorithms: Version 1.0.3
A dependency free library of standardized optimization test functions written in pure Python.
PyTorch implementation of Constrained Policy Optimization
Python implementation of the genetic algorithm MAP-Elites with applications in constrained optimization