Search Results for "parallel genetic algorithm" - Page 10
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Showing 313 open source projects for "parallel genetic algorithm"
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Primarily applied in experimental psychology, where it is used to create experiment schedules. It even can be applied to other planning-activities that have to met boundary constraints. Rando uses a genetic-algorithm to construct a fulfilled schedule.
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A 2D rigid physics simulator and set of genetic algorithm tools. Evolve cute little walking creatures.
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A hierarchical representation language for music, which can be used as a human algorithmic composition tool or as a semi-automated composition tool using a genetic algorithm with human listeners as the fitness function.
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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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Searches for adecuate design for feedforward backpropagation neural network, employing genetic algorithm as refining engine. The result topolgy may not be orthodox.
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czip is a unix based utility written for the cell broadband engine. It allows its users to compress files in gzip format. It uses Jean-loup Gailly's deflate algorithm and is based in part on pigz, Mark Adlers parallel version of zlib.
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This project aims to create an application to solve the job shop schedule problem using genetic algorithm on the IBM Cell BE processor. This is useful especially using the power of Cell for the large scale job shop schedule problem.
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This project is about an algorithm for multi-resolution texture systhesis on Cell.BE.There are there source code files.One is serial on x86.One is serial code on cell ppu,and the last is parallel code,which use ppu and 8 spus.
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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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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.
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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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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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Popular Game 15 implemented in Java. The most intersting part of the project is the genetic algorithm which solving the puzzle. Play the game here: http://www.geocities.com/todordimitrovbalabanov/the15/
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This project aims to improve the Civilization 4 AI using a genetic algorithm. We also have some alternative AI algorithms which have been custom written that will hopefully also improve the AI.
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OGA, Open Genetic Algorithm implements the evolutionary genetic algorithms with an user interface in GTK+. The main goal of the program is solve complex problems using evolutionary algorithms like genetic algorithms or evolutionary strategies.
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Galapagos is a Genetic Algorithm framework written in Java 5 with the intended audience of undergraduates in an Artificial Intelligence class. The goal of Galapagos is usability: a competent student should be able to learn this library in an afternoon.
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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
