Search Results for "knapsack genetic algorithm" - Page 4
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Showing 161 open source projects for "knapsack genetic algorithm"
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Developed as a final year project at Islamic University of Technology (IUT) during 2010 - 2011 academic year. This code is a simple implementation of real coded genetic algorithm for numerical optimization. Code is written in C/C++.
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BIL++ is a set of standalone C++ packages for data processing in Bioinformatics (Graph mining, Bayesian networks, Genetic algorithm, Discretization, Gene expression data analysis, Hypothesis testing).
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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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Open Song Composer is a free/open source music generator written in Java that learns through use of a genetic algorithm. It can generate music in all major modes.
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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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Audio Analysis/Resynthesis the way Darwin would have done it if he were only into computer music. Using a genetic algorithm to evolve a sinusoidal/noise based sound model, create variations as the audio chromosome of a sound's family tree progresses.
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Mainly include the codes of genetic algorithm, interative genetic algorithm, that are written in Java Applcations also included such as function optimization, simple fashion design optimization, face optimization and so on
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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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AEvolution is an artificial life simulator, simulating (multi)cellular behavior using a genetics algorithm. Multiple planes can be connected via either local or ftp-based teleporters...
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Moved to github! https://github.com/aaronbot3000/image-evolver The goal of the Image Evolver is to recreate a source picture using overlapping transparent shapes positioned a genetic algorithm.
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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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A small C# Library that provides the scaffolding for Genetic Algorithm based functionality. Requires .Net 3.5 or above.
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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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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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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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PGAF provides a framework tuned, user-specific genetic algorithms by handling I/O, UI, and parallelism. It is designed for optimizing functions that take a "very long time" to evaluate.
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This is C++ application code that implements Gene Expression Programming, or GEP - a form of genetic algorithm.
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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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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/).