Showing 96 open source projects for "parallel genetic algorithm"

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  • 1
    A concise example of the classical genetic algorithm, with a fancy windows terminal display. Features DNA editing, save/load, customizable constraints and statistics logging.
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  • 2
    A framework for utilising the Genetic Algorithm in the domain of Game Theory
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  • 3

    gaDesignLib

    Genetic algorithm for mechatronic product design

    This C++/STL library provides you with the basic genetic algorithms needed for engineering design, such as simple GA and variable population.
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  • 4
    A Java implementation of the NEAT algorithm as created by Kenneth O Stanley. Also provides a toolkit for further experiments to be created and can provide both local and distributed learning environments.
    Downloads: 3 This Week
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  • 5
    Galapagos is a Genetic Algorithm framework written in Java 5 with the intended audience of undergraduates in an Artificial Intelligence class. The goal of Galapagos is usability: a competent student should be able to learn this library in an afternoon.
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  • 6
    musicomp is a program which most important element is an evolutionary algorithm which uses data mining methods as a fitness function to generate monophone melodies.
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  • 7
    NeuroDraughts is a Draughts/Checkers game that teaches itself how to play through self play. It combines an Artificial Neural Network, trained by Temporal Difference Learning using some Genetic Algorithm style behaviour.
    Downloads: 0 This Week
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  • 8
    Implement a scheduling algorithm to schedule classes at a university
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  • 9
    Genetic Algorithm based software to resolve the Traveling Salesman Problem (Problema del Commesso Viaggiatore).
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  • 10
    Genetic Algorithm implementation.
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  • 11
    unEvo is an Eclipse plug-in that provides support for the experimentation and research process on Evolutionary Algorithms, intended so that the user can implement an evolutionary algorithm without lost time in the code of the algorithm.
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  • 12
    Galileo is a library for developing custom distributed genetic algorithms developed in Python. It provides a robust set of objects that can be used directly or as the basis of derived objects. Its modularity makes it easy to extend the functionality. The
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  • 13
    ga2 is a simple C++ library providing the necessary base classes to implement a genetic algorithm in C++. It is based loosely on Goldberg's canonical GA, but with many modifications, improvements and additional features. Essentially feature-complete, and
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  • 14
    Application to test a GA solution for the Knapsack problem, it will compare Genetic Algorithm solution of the Knapsack problem to greedy algorithm.
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  • 15

    GENet

    A genetic algorithm framework for artificial neural networks.

    A genetic algorithm framework to allow the evolution of synapse weights and topologies of artificial neural networks.
    Downloads: 0 This Week
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  • 16
    Integer Singular Value Decomposition Genetic Algorithm Function Fitter. This is an optimization algorithm that performs a similar role to a neural network.
    Downloads: 0 This Week
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  • 17
    A Visual Studio .NET C++ application can perform machine learning using genetic algorithm, naive bayes, KNN, and Artificial Neural Networks (ANNs) read and processed from any standard ARFF.
    Downloads: 0 This Week
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  • 18
    Evolutionary computation library and benchmark utility. Integer encoded genetic algorithm.
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  • 19

    biojazz

    In silico evolution of biochemical networks.

    In silico evolution of biochemical networks using a genetic algorithm combined with a rule-based biochemical network model.
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  • 20
    The SBMLevolver is an evolutionary algorithm package that creates SBML models with user-specified properties and behaviour from a given set of building blocks. Applications lie in network reconstruction and synthetic biology.
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  • 21
    cosmos

    cosmos

    Algorithms that run our universe | Your personal library of every algo

    Cosmos (by OpenGenus Foundation) is your personal offline collection of every algorithm and data structure one will ever encounter and use in a lifetime. This provides solutions in various languages spanning C, C++, Java, JavaScript, Swift, Python, Go and others. This work is maintained by a community of hundreds of people and is a massive collaborative effort to bring the readily available coding knowledge offline.
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