Showing 48 open source projects for "parallel genetic algorithm"

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  • 1
    simple-galib
    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.
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  • 2
    Game Toolbox is a C# assembly designed to facilitate the creation of games and game prototypes. It contains no graphics code, does not depend on XNA, and is Mono-compatible. It provides implementations of A*, GOAP, a genetic algorithm, and more.
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  • 3
    Geneur is an Open Source scheduler for GRID. It is based on variation of genetic algorithms. Geneur uses backfill scheduling algorithm to create first genetic population.
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  • 4
    An implementation of LAYAGEN G(Diego-Mas 2010) for solves the layout planning problem using a simple genetic algorithm, and fully written in GAMBAS
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  • 5
    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++.
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  • 6
    A .net implementation of a framework for genetic algorithms. This tool enables programmers to write the "core" of their problem and have a genetic algorithm immediately setup for solving it.
    Downloads: 1 This Week
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  • 7
    A Multi-objective evolutionary algorithm library
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  • 8
    A Tcl extension for genetic/evolutionary algorithm processing. It is using the GAUL library for the core functionality.
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  • 9
    Evolve is a simulation written in java that uses the Genetic Algorithm to evolve intelligent agents acting in a rich environment.
    Downloads: 0 This Week
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  • 10
    A 2D rigid physics simulator and set of genetic algorithm tools. Evolve cute little walking creatures.
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  • 11
    JNSGA2 is a Java library with an implementation of the multi-objective genetic algorithm NSGA-II published by Deb et al.
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  • 12
    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.
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  • 13
    A framework for utilising the Genetic Algorithm in the domain of Game Theory
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  • 14
    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.
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  • 15
    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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  • 16
    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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  • 17
    Implement a scheduling algorithm to schedule classes at a university
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  • 18
    Genetic Algorithm implementation.
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  • 19

    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.
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  • 20
    Evolutionary computation library and benchmark utility. Integer encoded genetic algorithm.
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  • 21

    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.
    Downloads: 0 This Week
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  • 22
    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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  • 23
    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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