Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.
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Updated
Dec 4, 2024 - Python
Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.
Python interface for the SCIP Optimization Suite
An Eigen-based, light-weight C++ Interface to Nonlinear Programming Solvers (Ipopt, Snopt)
Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable interface.
Nonconvex embedded optimization: code generation for fast real-time optimization + ROS support
skscope: Sparse-Constrained OPtimization via itErative-solvers
LBFGS-Lite: A header-only L-BFGS unconstrained optimizer.
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.
A next-gen Lagrange-Newton solver for nonconvex constrained optimization. Unifies barrier and SQP methods in a generic way, and implements various globalization flavors (line search/trust region and merit function/filter method/funnel method). Competitive against filterSQP, IPOPT, SNOPT, MINOS and CONOPT.
Represent trained machine learning models as Pyomo optimization formulations
A Julia interface to the NLopt nonlinear-optimization library
An intuitive modeling interface for infinite-dimensional optimization problems.
A Julia/JuMP-based Global Optimization Solver for Non-convex Programs
A collection of work using nonlinear model predictive control (NMPC) with discrete-time control Lyapunov functions (CLFs) and control barrier functions (CBFs)
[***JMLR-2024***] PyPop7: A Pure-Python Library for POPulation-based Black-Box Optimization (BBO), especially *Large-Scale* versions/variants (e.g., evolutionary algorithms, swarm-based optimizers, pattern search, and random search, etc.). [Citation: https://jmlr.org/papers/v25/23-0386.html (***CCF-A***)]
HPC solver for nonlinear optimization problems
iterative Linear Quadratic Regulator with constraints.
A JuMP-based Nonlinear Integer Program Solver
Data Structures for Optimization Models
A toolkit for testing control and planning algorithm for car racing.
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