Showing 18 open source projects for "java framework"

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  • 1
    jMetal
    jMetal is an object-oriented Java-based framework for solving multi-objective optimization problems with metaheuristics.
    Downloads: 1 This Week
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  • 2
    Opt4J

    Opt4J

    Modular Java framework for meta-heuristic optimization

    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.
    Downloads: 0 This Week
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  • 3

    serein

    A Framework to Model Metaheuristics

    Downloads: 0 This Week
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  • 4
    JCLEC
    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
    Downloads: 2 This Week
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  • 5
    SEAGE
    Search Agents - a framework for collaboration of meta-heuristic agents
    Downloads: 0 This Week
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  • 6

    Genetic Basis

    A general genetic algorithm framework

    Downloads: 0 This Week
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  • 7
    Framework for development of simple evolutionary algorithms / island models programs in distributed environment using MapReduce programming model based on hadoop.
    Downloads: 0 This Week
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  • 8
    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.
    Downloads: 0 This Week
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  • 9
    X-GAT
    X-GAT (XML-based Genetic Algorithm Toolkit) is a Java framework to optimize problems with Genetic Algorithms (GAs). Differently from other frameworks, X-GAT contains ready-to-use GAs implementations and new features can be easily added.
    Downloads: 0 This Week
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  • 10
    CILib is a framework for developing Computational Intelligence software in swarm intelligence, evolutionary computing, neural networks, artificial immune systems, fuzzy logic and robotics.
    Downloads: 0 This Week
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  • 11
    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.
    Downloads: 0 This Week
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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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    Downloads: 93 This Week
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  • 13
    A framework for utilising the Genetic Algorithm in the domain of Game Theory
    Downloads: 0 This Week
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  • 14
    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.
    Downloads: 0 This Week
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  • 15
    Simple genetic programming framework. Features a robust set of interfaces and standard implementations for rapid development and ease of experimentation.
    Downloads: 0 This Week
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  • 16
    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.
    Downloads: 0 This Week
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  • 17
    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.
    Downloads: 0 This Week
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  • 18
    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.
    Downloads: 0 This Week
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