Open Source Java Genetic Algorithms

JGAP is a Genetic Algorithms and Genetic Programming package written in Java. It is designed to require minimum effort to use, but is also designed to be highly modular. JGAP features grid functionality and a lot of examples. Many unit tests included. Legal notice/Impressum: Klaus Meffert An der Struth 25 D-65510 Idstein sourceforge <at> klausmeffert.de

JAG3D is no longer developed at source-forge, and has moved to GitHub. Please visit https://github.com/applied-geodesy/jag3d or https://software.applied-geodesy.org to get the latest version.

jMetal is an object-oriented Java-based framework for solving multi-objective optimization problems with metaheuristics.

The source code has been migrated and is now hosted on Github: https://github.com/jenetics/jenetics Jenetics is an advanced Genetic Algorithm, Evolutionary Algorithm and Genetic Programming library, respectively, written in modern day Java. It is designed with a clear separation of the several algorithm concepts, e. g. 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

NaruGo is game AI project. Current targets are GO board game and Texas Holdem poker. It investigates Genetic programming to build game AI logic. Also EA/GP simulations for TSP, Graph layout and Prisoners Dilemma problem.

The Distributed Genetic Programming Framework is a scalable Java genetic programming environment. It comes with an optional specialization for evolving assembler-syntax algorithms. The evolution can be performed in parallel in any computer network.

Formicidae is the official simulator and visualizer for the Ant-Wars competitive programming site, written in Java and SISC. The site is hosted at www.ant-wars.net.

This project contains a solution for a Bin Packing problem solved using Genectic Algorithms. The code in the project was created as a solution for a problem in a combinatorial optimization class at the Univeridade Federal do Rio Grande do Sul (UFRGS - Brasil) in 2007.

Opt4J is an open source Java-based framework for evolutionary computation. It contains a set of (multi-objective) optimization algorithms such as evolutionary algorithms (including SPEA2 and NSGA2), differential evolution, particle swarm optimization, and simulated annealing. The benchmarks that are included comprise ZDT, DTLZ, WFG, and the knapsack problem. The goal of Opt4J is to simplify the evolutionary optimization of user-defined problems as well as the implementation of arbitrary meta-heuristic optimization algorithms. For this purpose, Opt4J relies on a module-based implementation and offers a graphical user interface for the configuration as well as a visualization of the optimization process.

This site hosts the source code for C++ version of the Broker for SBW, NOM module, advanced simulation suite, analysis applications and model editors.

CILib is a framework for developing Computational Intelligence software in swarm intelligence, evolutionary computing, neural networks, artificial immune systems, fuzzy logic and robotics.

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

Logi (Local Observations to Global Integration) transforms several local coordinate systems (composed of polar measurements) into a global spatial uniform network with respect to the Guide to the Expression of Uncertainty in Measurement (GUM).

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.

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.

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

OAP Lite is Optimized Algorithms Platform Lite, which simplifies the process of solving some optimization problems by Genetic Algorithms. It is a highly configurable, efficient tool for user to get the optimum result without programming.

OpenDino is an open source Java platform for optimization, design of experiment and learning. It provides a graphical user interface (GUI) and a platform which simplifies integration of new algorithms as "Modules". Implemented Modules Evolutionary Algorithms: - CMA-ES - (1+1)-ES - Differential Evolution Deterministic optimization algorithm: - SIMPLEX Learning: - a simple Artificial Neural Net Optimization problems: - test functions - interface for executing other programs (solvers) - parallel execution of problems - distributed execution of problems via socket connection between computers Others: - data storage - data analyser and viewer

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

a framework library with a template method interface and inheritable classes for an executable process design which produces an executable which is both a GUI and a console application. It provides multi-threading for work items of the provider process .

a sandbox for trying my engine ideas

Agenda desenvolvida em Java, utilizando banco PostGreSQL. Itens: Cadastro de Contatos Cadastro de Tarefas

The Gene Expression Programming Framework in Java. It separates the process of evolution from the process of interpretation of the chromosome, allowing the use of various schemes in the chromosome.

The main goal of the Analytical Customer Relationship Management system is to improve services provided to customers, and to use customer contact information for targeted marketing.

Test of Artificial Life