Search Results for "parallel genetic algorithm" - Page 2
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Showing 75 open source projects for "parallel genetic algorithm"
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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. -
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OpenAIL
Open Artificial Intelligence Library
[Open Artificial Intelligence Library]. This library main goal is to provide a tool box to those who want to use algorithm such as neural network or genetics Algorithm and all algorithms that are commonly within the Artificial Intelligence field. -
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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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Evolving Objects
This project have been merged within Paradiseo.
See the new project page: https://nojhan.github.io/paradiseo/ (Archived project page: http://eodev.sourceforge.net/) -
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This project provides a set of Python tools for creating various kinds of neural networks, which can also be powered by genetic algorithms using grammatical evolution. MLP, backpropagation, recurrent, sparse, and skip-layer networks are supported.
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Genetic Basis
A general genetic algorithm framework
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ats - Automated Testing System
Object oriented Python-based tool for test automation.
...ATS is an object-oriented Python program that provides abstractions for user defined tests (usually specified with an executable and command line and / or an input file). It runs these tests, either in serial or in parallel, and creates a log file (or files) describing the results of running the tests. ATS provides the capability to run serial or parallel tests simultaneously up to the resource limits it has been given (i.e. some number of processors on which to run). Tests can be given a priority rating and be dependent upon other tests, and these features are accounted for in its scheduling algorithm. ... -
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MbPc Pagerank Simulator
Testbed for playing with the algorithm "pagerank" of Google
Provide a testbed to play with pagerank-like algorithm on graph. You can easily add vertices, edges, save the graph for reuse, etc. For now, only Pagerank is implemented, but in the future, other algorithms will be added. -
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GeneThello (read jə-ˈne-ˈthe-lō), is an acronym for genetic othello, an othello (reversi) playing program which based on Genetic Algorithm (GA). In principle GeneThello consist of an othello program and a genetic algorithm system.
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Creatio Low-Code Development PlatformIntelligent low-code platform to empower both IT and non-IT staff to effortlessly build enterprise-grade apps and processes
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Project aim to provide simple easy APIs for Java developers to use interactive abilities in their Java Applications like speech recognition, handwriting recognition, use of web cam , sound record/play, decision trees , text to speech and many others.
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Genetic Algorithm General Solver-GAGENES
Genetic algorithms (GA) in C++
NOTE: Project has been delayed due to other tasks. Genetic Algorithms General Solver (GAGENES) is a C++ implementation of the genetic algorithm concept. -
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This project is a complete cross-platform (Windows, Linux) framework for Evolutionary Computation in pure python. See the project site at http://pyevolve.sourceforge.net or the blog at http://pyevolve.sourceforge.net/wordpress
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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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Based on the introduction of Genetic Algorithms in the excellent book "Collective Intelligence" I have put together some python classes to extend the original concepts.
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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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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.
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Evolutionary Structural Optimization Package (ESOP) consists of software for viewing, analyzing, and optimizing structures containing beam, truss, and membrane plate elements utilizing OpenGL and the Genetic Algorithm (GA). Created for use in M.S. theses
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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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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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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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gaKnn(Genetic Algorithm Optimized K Nearest Neighbor Classification framework) is a frameowork for KNN optimization with a genetic algorithm. The genetic algothm used for this is JGAP (http://jgap.sourceforge.net/).
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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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Evolve is a simulation written in java that uses the Genetic Algorithm to evolve intelligent agents acting in a rich environment.
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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.
