Search Results for "genetic algorithms"

ECF is a framework intended for application of any type of evolutionary computation (GA/GP, DE, Clonalg, ES, PSO, ABC, GAn, local search...). It offers simplicity for the end-user (parameterless usage, tutorial) and customization for experienced EC practicioners.

GeneticSharp is a fast, extensible, multi-platform and multithreading C# Genetic Algorithm library that simplifies the development of applications using Genetic Algorithms (GAs). Can be used in any kind of .NET 6, .NET Standard and .NET Framework apps, like ASP .NET MVC, ASP .NET Core, Blazor, Web Forms, UWP, Windows Forms, GTK#, Xamarin, MAUI and Unity3D games. GeneticSharp and extensions (TSP, AutoConfig, Bitmap equality, Equality equation, Equation solver, Function builder, etc). ...

Solid is a Python framework for gradient-free optimization. It contains basic versions of many of the most common optimization algorithms that do not require the calculation of gradients, and allows for very rapid development using them.

The MOEA Framework is a free and open source Java library for developing and experimenting with multiobjective evolutionary algorithms (MOEAs) and other general-purpose multiobjective optimization algorithms. The MOEA Framework supports genetic algorithms, differential evolution, particle swarm optimization, genetic programming, grammatical evolution, and more. A number of algorithms are provided out-of-the-box, including NSGA-II, NSGA-III, ε-MOEA, GDE3 and MOEA/D. ...

JCLEC is a general purpose evolutionary computation framework developed in Java. Some of its mains features are: multilevel architecture, highly reusable and integrable with other systems, easy to use and a lot of implemented algorithms and operation

An optimized java library for genetic algorithms. The library is designed to be fast and memory light, but still very easy to use.

Math tools in Python to tackle down problems in Operational Research fields. Comes with a Django based web interface to allow remote access to complex simulation means.

Search Agents - a framework for collaboration of meta-heuristic agents

Framework for development of simple evolutionary algorithms / island models programs in distributed environment using MapReduce programming model based on hadoop.

A generic implementation of STL containers and some STL algorithms. The main intent is no make this STL implementation to work with any kind of pointers defined by allocator classes, e.g. memory_mgr::offset_ptr.

Sleepwalker aims to provide a highly abstract, universal, reusable, extensible Java-based genetic algorithms framework which can be used as a basis for modelling and programming virtually any practical optimisation problem.

Generic System for Data Processing

LazyEngine is a collection of Tools for PHP, C# and JavaScript (based on JQuery). The goal is to have a Library that contains most common functions daily used by software developers.

This project has moved and is not any longer developed. Please see http://sibirjak.com/blog/index.php/lite-collections/ for more details.

The Neo A.I Framework is a group of technologies and tools used to create A.I like software or software with A.I integrated into it

Very useful framework library, contains many frequent used code snippets, algorithms, data structures, WinForms & APS.NET controls for all-day work.

CuberGA project is the flexible Genetic Algorithms framework. Realize your ideas easy with deliveries of this project. Keywords: genetic algorithms, framework, permutation, mutation, crossover, genotype, selection, survival, Левченко Илья.

MAIF is developed in Java 5 (especially Generics) and aims at building AI algorithms, by concentrating onto the mapping of real-world problems, while abstracting from their inner working. It can be extended with new algorithms and problem representations.

A java framework for developing meta-heuristics that supports the use of grids environments. The meta-heuristics planned to be realeased are GAs, VNS and NNs. The grid middleware that will be firstly explored is the OurGrid solution.

Transport Framework

PyOptFrame-LEGACY is a Python version of OptFrame v2, proposed in 2011, now superseeded in 2021 by v5 on GitHub and PIP. The main objective is to provide the same interface to OptFrame C++ optimization framework, including classic metaheuristics such as genetic algorithms, simulated annealing, variable neighborhood search, first/best/multi-improvement, hill climbing, and multi-objective methods such as nsga-ii. See NEWEST version v5 on GitHub and PIP. Please try Official pyoptframe on https://pypi.org/project/optframe/ for OptFrame v5 (last updated 2022).