Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear)

An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations

Concise and beautiful algorithms written in Julia

Optimization functions for Julia

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.

A data structure for mathematical optimization problems

A Julia/JuMP Package for Power Network Optimization

A Julia Basket of Hand-Picked Krylov Methods

Makes Julia reason with equations. General purpose metaprogramming, symbolic computation and algebraic equational reasoning library for the Julia programming language: E-Graphs & equality saturation, term rewriting and more.

🏔️Manopt. jl – Optimization on Manifolds in Julia

Surrogate modeling and optimization for scientific machine learning (SciML)

Evolutionary & genetic algorithms for Julia

A JuMP extension for Stochastic Dual Dynamic Programming

Arrays with arbitrarily nested named components.

Automatic Differentiation Library for Computational and Mathematical Engineering

COSMO: Accelerated ADMM-based solver for convex conic optimisation problems (LP, QP, SOCP, SDP, ExpCP, PowCP). Automatic chordal decomposition of sparse semidefinite programs.

Sequential Convex Programming Toolbox for nonconvex trajectory optimization.

Julia for optimization simulation and modeling of PowerSystems. Part of the Scalable Integrated Infrastructure Planning Initiative at the National Renewable Energy Lab.

An intuitive modeling interface for infinite-dimensional optimization problems.

A Julia interface to the NLopt nonlinear-optimization library