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
Surrogate Optimization Toolbox for Python
Hyperparameter optimization in Julia.
Efficient global optimization toolbox in Rust: bayesian optimization, mixture of gaussian processes, sampling methods
A collection of Benchmark functions for numerical optimization problems
Derivative-Free Global Optimization Algorithm (C++, Python binding) - Continuous, Discrete, TSP, NLS, MINLP
A development environment for robust and global optimization
A curated survey and paper list for global solvers in 3D vision: certifiable optimization, convex relaxation, Branch-and-Bound, and robust estimation.
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.
Julia interface to SCIP solver
[ICCV'19] Calibration Wizard: A Guidance System for Camera Calibration Based on Modelling Geometric and Corner Uncertainty
Rigorous global optimisation
Heuristic global optimization algorithms in Python
Evolutionary Computation: A Modern Perspective |<...>| This is an online book, which is free-access and actively-updated (1st Edition: from 2023 to 2027).