Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.
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Updated
Nov 6, 2024 - Python
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.
Generic Constraint Development Environment
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.
A next-gen Lagrange-Newton solver for nonconvex optimization. It unifies barrier and SQP methods in a modern and generic way, and implements different globalization flavors (line search/trust region and merit function/filter method/funnel method). Competitive against filterSQP, IPOPT, SNOPT, MINOS and CONOPT.
High-performance metaheuristics for optimization coded purely in Julia.
HPC solver for nonlinear optimization problems
Source Codes for Codimensional Incremental Potential Contact (C-IPC)
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
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
The Constrained and Unconstrained Testing Environment with safe threads (CUTEst) for optimization software
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