Search Results for "ga"

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.

...Gene, Chromosome, Genotype, Phenotype, Population and fitness Function. Jenetics allows you to minimize or maximize the given fitness function without tweaking it. In contrast to other GA implementations, the library uses the concept of an evolution stream (EvolutionStream) for executing the evolution steps. Since the EvolutionStream implements the Java Stream interface, it works smoothly with the rest of the Java Stream API. Other repositories: - https://github.com/jenetics/jenetics Maven: - https://mvnrepository.com/artifact/io.jenetics

Genetic Algorithm File Fitter, GAFFitter for short, is a tool based on a genetic algorithm (GA) that tries to fit a collection of items, such as files/directories, into as few as possible volumes of a specific size (e.g. CDs or DVDs).

A Java based, pMars compatible, CoreWars simulator with Genetic Algorithm warrior evolver functionality. Java 8 is needed. See [Wiki:Tutorial]

GFP use Genetic Programming and LISP-like language for growing program.

libfgen is a library that implements an efficient and customizable genetic algorithm (GA). It also provides particle swarm optimization (PSO) functionality and an interface for real-valued function minimization or model fitting. It is written in C, but can also be compiled with a C++ compiler. Both Linux and Windows are supported.

GeneThello (read jə-ˈne-ˈthe-lō), is an acronym for genetic othello, an othello (reversi) playing program which based on Genetic Algorithm (GA). In principle GeneThello consist of an othello program and a genetic algorithm system.

NOTE: Project has been delayed due to other tasks. Genetic Algorithms General Solver (GAGENES) is a C++ implementation of the genetic algorithm concept.

This library is a lightweight implementation of genetic algorithm, contains the most popular types of chromosomes and the basic algorithms for selection, elitism, crossing and mutation.

This is implementation of parallel genetic algorithm with "ring" insular topology. Algorithm provides a dynamic choice of genetic operators in the evolution of. The library supports the 26 genetic operators. This is cross-platform GA written in С++.

This project aims to create an open source genetic algorithms (GA) library for the IBM Cell BE processor. A well-documented implementation of GAs is provided, along with a number of sample fitness functions illustrating how to use the GA library.

This is a cross-platform framework for using Genetic Algorithms for solutions. Written in Java and uses convinient plug-in features for every phase in the genetic development, while maintaining an easy-to-use API for easy integration into applications.