A Julia/JuMP-based Global Optimization Solver for Non-convex Programs
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Updated
Aug 14, 2024 - Julia
A Julia/JuMP-based Global Optimization Solver for Non-convex Programs
MIRT: Michigan Image Reconstruction Toolbox (Julia version)
Proximal algorithms for nonsmooth optimization in Julia
Tools for developing nonlinear optimization solvers.
Julia implementation for various Frank-Wolfe and Conditional Gradient variants
Clarabel.jl: Interior-point solver for convex conic optimisation problems in Julia.
OptimKit: A blissfully ignorant Julia package for gradient optimization
Structured optimization in Julia
Model and solve optimal control problems in Julia
A Julia framework for implementing branch-and-bound-type algorithms
An algorithmic framework for parallel dual decomposition methods in Julia
Documentation for the Clarabel interior point conic solver
This package is the implementation of a one-phase interior point method that finds KKT points of nonconvex optimization problems.
Mixed-Integer Convex Programming: Branch-and-bound with Frank-Wolfe-based convex relaxations
Optimization approach to the trimmed Lasso penalty for sparse modeling
Solves a Quadratic Programming problem using Alternating Direction Method of Multipliers (ADMM). This is a MATLAB implementation of the paper - OSQP: An Operator Splitting Solver for Quadratic Programs.
Large scale convex optimization solvers in julia
A framework to implement iterative algorithms
An algorithm for solving nonconvex problems of the "convex+bilinear constraint" type with convex optimization.
Extended Mathematical Programming in Julia
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