Showing 88 open source projects for "genetic algorithm in matlab"

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  • 1
    This easy to run and change program for developers, it contains several evolutionary based strategies allowing you try among some function samples
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  • 2
    POGA - Parameter's Optimization by Genetic Algorithm - Developed by Leonardo Santos (LAC-INPE :: santoslbl@gmail.com) and José Miranda (IF-UFBA :: vivas@ufba.br). 114 Downloads of the first version. Second version avaliable.
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  • 3
    This is implementation of parallel genetic algorithm with "ring" insular topology. Algorithm provides a dynamic choice of genetic operators in the evolution of. The library supports the 26 genetic operators. This is cross-platform GA written in С++.
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  • 4
    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.
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  • 5
    Linear Time Invariant (LTI) system identification using particle swarm optimization (PSO) algorithm. Creators : Vahid Kiani, Hadi Sadoghi Yazdi
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  • 6
    This is C++ application code that implements Gene Expression Programming, or GEP - a form of genetic algorithm.
    Downloads: 2 This Week
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  • 7
    TrimGA is a lightweight genetic algorithm library written in pure Java 6.0 that can be quickly applied to most optimization problems.
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  • 8
    Java API for implementing any kind of Genetic Algorithm and Genetic Programming applications quickly and easily. Contains a wide range of ready-to-use GA and GP algorithms and operators to be plugged-in or extended. Includes Tutorials and Examples.
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  • 9
    Springbots is a python application which takes a set of 2d physical structures built with nodes and movable springs and evolve them for specific tasks like walking, swimming and jumping using genetic algorithm.
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  • 10
    A flexible and easy-to-use toolkit for implementing genetic algorithm in Python
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  • 11
    The Automatic Model Optimization Reference Implementation, AMORI, is a framework that integrates the modelling and the optimization processes by providing a plug-in interface for both. A genetic algorithm and Markov simulations are currently implemented.
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  • 12
    JNSGA2 is a Java library with an implementation of the multi-objective genetic algorithm NSGA-II published by Deb et al.
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  • 13
    Wodka is the implementation of a genetic algorithm (GA) that can bread two dimensional structures that might be used as robots in sodarace competitions.
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  • 14
    DrPangloss is a python implementation of a three operator genetic algorithm, complete with a java swing GUI for running the GA and visualising performance, generation by generation
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  • 15
    A Java implementation of the NEAT algorithm as created by Kenneth O Stanley. Also provides a toolkit for further experiments to be created and can provide both local and distributed learning environments.
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  • 16
    musicomp is a program which most important element is an evolutionary algorithm which uses data mining methods as a fitness function to generate monophone melodies.
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  • 17
    Neural networks evolution (genetic algorithm) written in Java. Now neural networks try to playing Go, Tic-Tac-Toe.
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  • 18
    Genetic Algorithm implementation.
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  • 19
    EasyAI is a project to build classical AI program and method in Java language, such as resolution for logic, greedy search, genetic algorithm, neural network and so on...
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  • 20
    IslandEv distributes a Genetic Algorithm (like <a href="/projects/jaga">JaGa</a>) across a network (see <a href="/projects/distrit">DistrIT</a>) using an island based coevolutionary model in which neighbouring islands swap migrating individuals every
    Downloads: 0 This Week
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  • 21
    C++ genetic algorithms library (solving of the NP opnimisation problems). More GA strategies, more useability, more algorithm speed.
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  • 22
    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.
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  • 23
    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.
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  • 24
    GACS (Genetic Algorithm Class Scheduler) aims to provide to academic institutions an efficient and automatic way to generate their time scheduling for the classes that will be imparted in an academic period.
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  • 25
    Galileo is a library for developing custom distributed genetic algorithms developed in Python. It provides a robust set of objects that can be used directly or as the basis of derived objects. Its modularity makes it easy to extend the functionality. The
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