Search Results for "genetic algorithm for knapsack problem"

Showing 15 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). ...
    Downloads: 0 This Week
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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
    Genetic Oversampling Weka Plugin

    Genetic Oversampling Weka Plugin

    A Weka Plugin that uses a Genetic Algorithm for Data Oversampling

    Weka genetic algorithm filter plugin to generate synthetic instances. This Weka Plugin implementation uses a Genetic Algorithm to create new synthetic instances to solve the imbalanced dataset problem. See my master thesis available for download, for further details.
    Downloads: 2 This Week
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  • 4

    GA-tools

    general genetic algorithms optimization fortran 95 routines

    High level optimization routines in Fortran 95 for optimization problems using a genetic algorithm with elitism, steady-state-reproduction, dynamic operator scoring by merit, no-duplicates-in-population. Chromosome representation may be integer-array, real-array, permutation-array, character-array. Single objective and multi-objective maximization routines are present. Possible to incorporate own crossover and mutation operators exclusively or in addition to standard operators that are included by default. ...
    Downloads: 0 This Week
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  • 5
    tsp-problem-ga-aco-comparisson

    tsp-problem-ga-aco-comparisson

    Genetic Algorithm and Ant Colony to solve the TSP problem

    This project compares the classical implementation of Genetic Algorithm and Ant Colony Optimization, to solve a TSP problem. It's possible to define the number of cities to visit , and also interactively create new cities to visit in a 2D spatial panel. A total distance is given for AG and ACO solution at end.
    Downloads: 0 This Week
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  • 6
    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...
    Downloads: 0 This Week
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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
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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
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  • 9

    Open Genetic Algorithm Toolbox

    This is a MATLAB toolbox to run a GA on any problem you want to model.

    This is a toolbox to run a GA on any problem you want to model. You can use one of the sample problems as reference to model your own problem with a few simple functions. You can collaborate by defining new example problems or new functions for GA, such as scaling, selection or adaptation methods. In that case, you should then include your credits in the file, upload it to matlab central and contact the author. Suggestions are also welcome but naturally I won't be able to attend...
    Downloads: 0 This Week
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  • 10
    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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  • 11
    GAAF is a tool for analyzing Genetic Algorithms (GA for short). It allows to check the behavior of a particular GA resolving a particular problem so one can get empirical information to decide which GA best fits problem's conditions.
    Downloads: 0 This Week
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  • 12
    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.
    Downloads: 0 This Week
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  • 13
    Genetic Algorithm based software to resolve the Traveling Salesman Problem (Problema del Commesso Viaggiatore).
    Downloads: 0 This Week
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  • 14
    Gazoo is a Java framework for genetic algorithms development. Gazoo provides the core of a genetic algorithm, leaving to the user the implementation of specific-problem classes.
    Downloads: 0 This Week
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  • 15
    Solving the travelling salesman problem with genetic (evolutionary) algorithms. The distance calculations are based on geographical coordinates. The progress of the algorithm is visualized with a geo-map and some statistics.
    Downloads: 0 This Week
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