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 Basket of Hand-Picked Krylov Methods
A Julia/JuMP Package for Power Network Optimization
🏔️Optimization on Riemannian Manifolds in Julia
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.
Surrogate modeling and optimization for scientific machine learning (SciML)
Arrays with arbitrarily nested named components.
A JuMP extension for Stochastic Dual Dynamic Programming
Sequential Convex Programming Toolbox for nonconvex trajectory optimization.
Evolutionary & genetic algorithms for Julia
An intuitive modeling interface for infinite-dimensional optimization problems.
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.
Julia for optimization simulation and modeling of PowerSystems.
High-performance metaheuristics for optimization coded purely in Julia.
To associate your repository with the optimization topic, visit your repo's landing page and select "manage topics."