Showing 6 open source projects for "genetic algorithm for knapsack problem"

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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). ...
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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. The goal of Opt4J is to simplify the evolutionary optimization of user-defined problems as well as the implementation of arbitrary...
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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
    An implementation of LAYAGEN G(Diego-Mas 2010) for solves the layout planning problem using a simple genetic algorithm, and fully written in GAMBAS
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  • 5
    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.
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  • 6
    This project aims at providing a set of tools for solving the class of monodimensional packing problems (such as cutting stock, bin packing and knapsack problem) mainly using genetic algoritms.
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