Showing 7 open source projects for "ga"

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    ntuacarlo

    A open-source implementation library of optimization algorithms

    ntuacarlo: library of open-source implementation of optimization algorithms for Matlab/GNU Octave The library implements matlab functions for the following optimization algorithms: Simulated Annealing Particle Swarm Optimization Monte Carlo Exhaustive search The signature of the functions follow the same as the ga() function of Matlab. All the functions support lower and upper bounds, linear and non-linear constraints, and integer variables.Octave
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  • 2

    popt4jlib

    Parallel Optimization Library for Java

    popt4jlib is an open-source parallel optimization library for the Java programming language supporting both shared memory and distributed message passing models. Implements a number of meta-heuristic algorithms for Non-Linear Programming, including Genetic Algorithms, Differential Evolution, Evolutionary Algorithms, Simulated Annealing, Particle Swarm Optimization, Firefly Algorithm, Monte-Carlo Search, Local Search algorithms, Gradient-Descent-based algorithms, as well as some well-known...
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  • 3

    libfgen

    Library for optimization using a genetic algorithm or particle swarms

    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.
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  • 4
    GA Sandbox is a library providing geometric algebra implementations for geometric algebras. It comes with many programming examples. It is the software companion to the book `Geometric Algebra for Computer Science' (Morgan Kaufmann).
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  • 5
    GA++ is a Genetic Algorithm library written in C++,
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  • 6

    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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  • 7
    C++ genetic algorithms library (solving of the NP opnimisation problems). More GA strategies, more useability, more algorithm speed.
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