Showing 18 open source projects for "simple-xml"

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  • 1
    Skalli

    Skalli

    IVS & ILRS Reference Point Determination

    Skalli is a simple tool to estimate the IVS (International VLBI Service for Geodesy and Astrometry) and ILRS (International Laser Ranging Service) reference point of a radio or laser telescope.
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  • 2

    OpenDino

    Open Source Java platform for Optimization, DoE, and Learning.

    ...Implemented Modules Evolutionary Algorithms: - CMA-ES - (1+1)-ES - Differential Evolution Deterministic optimization algorithm: - SIMPLEX Learning: - a simple Artificial Neural Net Optimization problems: - test functions - interface for executing other programs (solvers) - parallel execution of problems - distributed execution of problems via socket connection between computers Others: - data storage - data analyser and viewer
    Downloads: 0 This Week
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  • 3
    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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  • 4
    an simple thread pool in linux, based on POSIX thread API. Management thread will retrieve needless idle thread to keep in low resource consumption.
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  • 5

    ACOptim

    Ant Colony Optimizer

    Simple POSIX multithread Ant Colony Optimizer framework currently for solving Vehicle Routing Problem. Supports UDP, file synchronizatoin between computers.
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  • 6
    Track your friends in real time on a map.. and many more features
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  • 7
    Framework for development of simple evolutionary algorithms / island models programs in distributed environment using MapReduce programming model based on hadoop.
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  • 8
    A self-contained, fully configurable Java "game" to simulate multi-species evolution. Design species by optionally specifying every attribute; modify any or all environmental settings; let them loose to eat, fight, procreate, die, and Evolve!
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  • 9
    X-GAT
    X-GAT (XML-based Genetic Algorithm Toolkit) is a Java framework to optimize problems with Genetic Algorithms (GAs). Differently from other frameworks, X-GAT contains ready-to-use GAs implementations and new features can be easily added.
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  • 10
    simple-galib
    This library is a lightweight implementation of genetic algorithm, contains the most popular types of chromosomes and the basic algorithms for selection, elitism, crossing and mutation.
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  • 11
    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: 8 This Week
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  • 12
    This project is using genetics algorithms to complete scheduling tasks such as timetables for elementary / high schools etc. Currently NetBeans project with no GUI and simple HTML export.
    Downloads: 0 This Week
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  • 13
    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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  • 14
    Cutting Problem solved by Genetic algorithms. The goal is to cut a rectangular plate of material into more smaller rectangles. The cuts must be rectangular and guillotinable.
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  • 15
    A GLib/GTK+ classical encryption analysis and reversal tool that brings together multiple techniques into a single program to aide in decryption.
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  • 16
    A library for Cartesian Genetic Programming (CGP.) This project includes a simple Evolution Strategy library that can be used for evolution.
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  • 17
    Simple genetic programming framework. Features a robust set of interfaces and standard implementations for rapid development and ease of experimentation.
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  • 18
    MAIF is developed in Java 5 (especially Generics) and aims at building AI algorithms, by concentrating onto the mapping of real-world problems, while abstracting from their inner working. It can be extended with new algorithms and problem representations.
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