a lightweight header-only C++17 library of numerical optimization methods for (un-)constrained nonlinear functions and expression templates
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Updated
Jul 28, 2025 - C++
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.
A highly customizable SQP & barrier solver for nonlinearly constrained optimization
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.
Source Codes for Codimensional Incremental Potential Contact (C-IPC)
HPC solver for nonlinear optimization problems
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 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)
Constrained Differential Dynamic Programming Solver for Trajectory Optimization and Model Predictive Control
Implementation of the paper "Improving Optimization Bounds using Machine Learning: Decision Diagrams meet Deep Reinforcement Learning".
Derivative-free nonlinear global optimizer with python interface
L-BFGS-B as a C++ header-only library
Library for nonconvex constrained optimization using the augmented Lagrangian method and the matrix-free PANOC algorithm.
Powerful and scalable black-box optimization algorithms for Python and C++.
Trajectory Optimization using Augment Lagrangian and iLQR
Constrained multi-objective derivative-free global solver
Leopard is a fast, modern implementation of sparse, multifrontal symmetric indefinite matrix factorization.
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