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

skscope: Sparse-Constrained OPtimization via itErative-solvers

Represent trained machine learning models as Pyomo optimization formulations

[JMLR (CCF-A)] PyPop7: A Pure-Python LibrarY for POPulation-based Black-Box Optimization (BBO), especially *Large-Scale* variants (including evolutionary algorithms, swarm-based randomized optimizers, pattern search, and random search). [https://jmlr.org/papers/v25/23-0386.html] (Its Planned Extensions: PyCoPop7, PyNoPop7, PyDPop77, and PyMePop7)

iterative Linear Quadratic Regulator with constraints.

A toolkit for testing control and planning algorithm for car racing.

[CVPR 2020, Oral] Category-Level Articulated Object Pose Estimation

An interior-point method written in python for solving constrained and unconstrained nonlinear optimization problems.

Python-based Derivative-Free Optimization with Bound Constraints

Improved LBFGS and LBFGS-B optimizers in PyTorch.

This repository contains the source code for “Unscented Kalman filter stochastic nonlinear model predictive control” (UKF-SNMPC).

A toolbox for trajectory optimization of dynamical systems

Simplicial Homology Global Optimization

Automatic parametric modeling with symbolic regression

A basic nonlinear model predictive control implementation using Casadi with Unscented Kalman filter state estimation

An extensible MINLP solver

Python-based Derivative-Free Optimizer for Least-Squares

Python trust-region subproblem solvers for nonlinear optimization

Special Structure Detection for Pyomo

DFO-GN: Derivative-Free Optimization using Gauss-Newton