Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.
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Updated
May 24, 2024 - Python
Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.
NMFLibrary: Non-negative Matrix Factorization (NMF) Library: Version 2.1
Generalized and Efficient Blackbox Optimization System.
Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.
Generic Constraint Development Environment
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.
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
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.
HPC solver for nonlinear optimization problems
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.
Source Codes for Codimensional Incremental Potential Contact (C-IPC)
Constrained optimization toolkit for PyTorch
High-performance metaheuristics for optimization coded purely in Julia.
An interior-point method written in python for solving constrained and unconstrained nonlinear optimization problems.
Powell's Derivative-Free Optimization solvers.
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)
Riemannian stochastic optimization algorithms: Version 1.0.3
Modern Fortran Edition of the SLSQP Optimizer
The Constrained and Unconstrained Testing Environment with safe threads (CUTEst) for optimization software
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