Showing 5 open source projects for "nsga ii"

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  • 1
    Evolutionary.jl

    Evolutionary.jl

    Evolutionary & genetic algorithms for Julia

    A Julia package for evolutionary & genetic algorithms. The package can be installed with the Julia package manager.
    Downloads: 1 This Week
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  • 2

    BioNetExplorer

    Framework for Exploration of Bio-signal Processing DNNs in Wearables

    ..., such as NSGA-II, SPEA-2, etc. Our framework also enables hardware-aware DNN architecture search by imposing user requirements and hardware constraints (storage, FLOPs, etc.) during the exploration stage, thereby limiting the number of networks explored. In case of usage, please refer to: B. S. Prabakaran, A. Akhtar, S. Rehman, O. Hasan, M. Shafique, “BioNetExplorer: Architecture-Space Exploration of Bio-Signal Processing Deep Neural Networks for Wearables,” IEEE Internet of Things Journal, 2021.
    Downloads: 0 This Week
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  • 3
    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. In addition, the MOEA...
    Downloads: 0 This Week
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  • 4
    JNSGA2 is a Java library with an implementation of the multi-objective genetic algorithm NSGA-II published by Deb et al.
    Downloads: 0 This Week
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  • 5

    PyOptFrame-LEGACY

    PyOptFrame-LEGACY is Python OptFrame v2. Newest version v5 on github.

    PyOptFrame-LEGACY is a Python version of OptFrame v2, proposed in 2011, now superseeded in 2021 by v5 on GitHub and PIP. The main objective is to provide the same interface to OptFrame C++ optimization framework, including classic metaheuristics such as genetic algorithms, simulated annealing, variable neighborhood search, first/best/multi-improvement, hill climbing, and multi-objective methods such as nsga-ii. See NEWEST version v5 on GitHub and PIP. Please try Official pyoptframe on https...
    Downloads: 0 This Week
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