Search Results for "parallel genetic algorithm"

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Showing 6 open source projects for "parallel genetic algorithm"

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  • Next-Gen Encryption for Post-Quantum Security | CLEAR by Quantum Knight Icon
    Next-Gen Encryption for Post-Quantum Security | CLEAR by Quantum Knight

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  • 1
    GeneticSharp

    GeneticSharp

    GeneticSharp is a fast, extensible, multi-platform and multithreading

    GeneticSharp is a fast, extensible, multi-platform and multithreading C# Genetic Algorithm library that simplifies the development of applications using Genetic Algorithms (GAs). Can be used in any kind of .NET 6, .NET Standard and .NET Framework apps, like ASP .NET MVC, ASP .NET Core, Blazor, Web Forms, UWP, Windows Forms, GTK#, Xamarin, MAUI and Unity3D games. GeneticSharp and extensions (TSP, AutoConfig, Bitmap equality, Equality equation, Equation solver, Function builder, etc). ...
    Downloads: 0 This Week
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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.
    Downloads: 0 This Week
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  • 3
    In this project we develop a software, that uses evolutionary algorithm to evolve a solution, that can drive a car on an arbitrari path.
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  • 4
    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: 0 This Week
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  • Skillfully - The future of skills based hiring Icon
    Skillfully - The future of skills based hiring

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    Skillfully transforms hiring through AI-powered skill simulations that show you how candidates actually perform before you hire them. Our platform helps companies cut through AI-generated resumes and rehearsed interviews by validating real capabilities in action. Through dynamic job specific simulations and skill-based assessments, companies like Bloomberg and McKinsey have cut screening time by 50% while dramatically improving hire quality.
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  • 5
    GEP is an evolutionary algorithm for function finding. This framework is a powerful way of expressing and coding genetic-like structures and quickly finding solutions through evolution by common genetic operators.
    Downloads: 2 This Week
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  • 6
    Application to test a GA solution for the Knapsack problem, it will compare Genetic Algorithm solution of the Knapsack problem to greedy algorithm.
    Downloads: 0 This Week
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