Search Results for "particle swarm optimization algorithm java code"

Showing 10 open source projects for "particle swarm optimization algorithm java code"

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  • 1
    PlatEMO

    PlatEMO

    Evolutionary multi-objective optimization platform

    Evolutionary multi-objective optimization platform. PlatEMO consists of a number of MATLAB functions without using any other libraries. Any machines able to run MATLAB can use PlatEMO regardless of the operating system. PlatEMO includes more than ninety existing popular MOEAs, including genetic algorithm, differential evolution, particle swarm optimization, memetic algorithm, estimation of distribution algorithm, and surrogate model-based algorithm. ...
    Downloads: 3 This Week
    Last Update:
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  • 2
    Smart Algorithm

    Smart Algorithm

    Repository implementing a variety of intelligent algorithms

    Particle Swarm Optimization (PSO) implementations in multiple languages. Immune Algorithm (or immune-inspired optimization) implementations. Multiple versions/language compatibility (Java, Python, MATLAB).
    Downloads: 0 This Week
    Last Update:
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  • 3

    TEESer

    Tool for Engineering Emergent Selforganizing bEhavioR

    ...Designers can continue to use their domain tools such as favorable simulator and by pluging it into the framework can take advantage of distributed simulations in the grid, various analyzers, optimizers (particle swarm optimization, genetic algorithms, ...). See Wiki pages for more information.
    Downloads: 0 This Week
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  • 4
    Solid Python

    Solid Python

    A comprehensive gradient-free optimization framework written in Python

    Solid is a Python framework for gradient-free optimization. It contains basic versions of many of the most common optimization algorithms that do not require the calculation of gradients, and allows for very rapid development using them.
    Downloads: 1 This Week
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  • 5
    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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  • 6
    MOEA Framework

    MOEA Framework

    A Free and Open Source Java Framework for Multiobjective Optimization

    The MOEA Framework is a free and open source Java library for developing and experimenting with multiobjective evolutionary algorithms (MOEAs) and other general-purpose multiobjective optimization algorithms. The MOEA Framework supports genetic algorithms, differential evolution, particle swarm optimization, genetic programming, grammatical evolution, and more. A number of algorithms are provided out-of-the-box, including NSGA-II, NSGA-III, ε-MOEA, GDE3 and MOEA/D. ...
    Downloads: 0 This Week
    Last Update:
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  • 7
    Bin Packing with Genectic Algorithm

    Bin Packing with Genectic Algorithm

    Bin Packing problem solved using Genectic Algorithm

    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.
    Downloads: 0 This Week
    Last Update:
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  • 8

    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.
    Downloads: 0 This Week
    Last Update:
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  • 9
    SEAGE
    Search Agents - a framework for collaboration of meta-heuristic agents
    Downloads: 0 This Week
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  • 10
    An attempt to design minimum cost broadband networks with the use of a modified version of the Particle Swarm Optimization method. A GIS subsystem is used for the visualization of data and results.
    Downloads: 0 This Week
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