NSGA2, NSGA3, R-NSGA3, MOEAD, Genetic Algorithms (GA), Differential Evolution (DE), CMAES, PSO

High-performance metaheuristics for optimization coded purely in Julia.

Tuning the Parameters of Heuristic Optimizers (Meta-Optimization / Hyper-Parameter Optimization)

Heuristic global optimization algorithms in Python

Implementation of Non-dominated Sorting Genetic Algorithm (NSGA-II), a Multi-Objective Optimization Algorithm in Python

This project is implemented by C#, and introduces a algorithm framework of MOEA, and some MOEA algorithms and multi-objective problems are provided.

An R package for multi/many-objective optimization with non-dominated genetic algorithms' family

A genetic algorithms library in C++ for single- and multi-objective optimization.

Refactored NSGA2, Non-dominated sorting genetic algorithm, implementation in C based on the code written by Dr. Kalyanmoy Deb.

A project on improving Neural Networks performance by using Genetic Algorithms.

Non-dominated Sorting Genetic Algorithm II (NSGA-II) in MATLAB

A NSGA-II implementation in Julia

An implementation of the NSGA-III algorithm in C++

multi objective, single objective optimization, genetic algorithm for multi-objective optimization, particle swarm intelligence, ... implementation in python

Implementation of NSGA-II in Python

Multi-objective optimisation framework in Rust

FuzzyNSGA-II-Algorithm (Fuzzy adaptive optimisation method)

Distributed surrogate-assisted evolutionary methods for multi-objective optimization of high-dimensional dynamical systems

Code for the Non-Dominated Sorting Genatic Algorithm II (NSGA-II) used in my PhD.

A hybrid feature selection algorithm combining Filter based methods and a Wrapper method.