A research toolkit for particle swarm optimization in Python

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 Genetic Algorithm Framework in Python (not for production level)

Experimental Global Optimization Algorithm

An implementation of the SE-Sync algorithm for synchronization over the special Euclidean group.

A Julia/JuMP-based Global Optimization Solver for Non-convex Programs

[JMLR-2024] PyPop7: A Pure-Python Library for POPulation-based Black-Box Optimization (BBO), especially *Large-Scale* variants (including evolutionary algorithms, swarm-based optimizers, pattern search, and random search). [https://jmlr.org/papers/v25/23-0386.html (CCF-A)] (Planned Extensions: PyCoPop7, PyNoPop7, PyPop77, and PyMePop7)

Surrogate Optimization Toolbox for Python

Hyperparameter optimization in Julia.

Derivative-Free Global Optimization Algorithm (C++, Python binding) - Continuous, Discrete, TSP, NLS, MINLP

A development environment for robust and global optimization

A collection of Benchmark functions for numerical optimization problems

A solver for mixed-integer nonlinear optimization problems

Toolbox for gradient-based and derivative-free non-convex constrained optimization with continuous and/or discrete variables.

[ICCV'19] Calibration Wizard: A Guidance System for Camera Calibration Based on Modelling Geometric and Corner Uncertainty

Julia interface to SCIP solver

Efficient global optimization toolbox in Rust: bayesian optimization, mixture of gaussian processes, sampling methods

Rigorous global optimisation in pure Julia

Heuristic global optimization algorithms in Python

Framework of intelligent optimization methods iOpt