Search Results for "parallel genetic algorithm" - Page 3
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Showing 95 open source projects for "parallel genetic algorithm"
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Geneur is an Open Source scheduler for GRID. It is based on variation of genetic algorithms. Geneur uses backfill scheduling algorithm to create first genetic population.
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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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Beagle is Java open source framework for running and managing nondeterministic algorithms such as genetic algorithms for solving complex problems. Beagle is fully modular and maintains whole history of algorithm progress for further analysis.
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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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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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Collect! is a highly configurable debt collection softwareThe flexible & scalable debt collection software built to automate your workflow. From startup to enterprise, we have the solution for you.
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A Tcl extension for genetic/evolutionary algorithm processing. It is using the GAUL library for the core functionality.
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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.
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This is an academic project; the main objective is to generate an algorithm to parallelize a CNF formula and then feed the distributed parts to sequential SAT solvers, for this project we have choose to use Sat4J as the solver.
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A 2D rigid physics simulator and set of genetic algorithm tools. Evolve cute little walking creatures.
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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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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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The Distributed Genetic Programming Framework is a scalable Java genetic programming environment. It comes with an optional specialization for evolving assembler-syntax algorithms. The evolution can be performed in parallel in any computer network.
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PyLife is an implementation of the game of life algorithm featuring parallel programming. It uses MPI and python to achieve a consistent software architecture and reliably performance.
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spGAL is a C++ Genetic Algorithm (GA) library. This is a portable scalable, and easy to use library written with ANSI C++.
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A flexible programming library for evolutionary computation. Steady-state, generational and island model genetic algorithms are supported, using Darwinian, Lamarckian or Baldwinian evolution. Includes support for multiprocessor and distributed systems.
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A concise example of the classical genetic algorithm, with a fancy windows terminal display. Features DNA editing, save/load, customizable constraints and statistics logging.
