Search Results for "knapsack genetic algorithm"
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23 projects for "knapsack genetic algorithm" with 2 filters applied:
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pgapack, the parallel genetic algorithm library is a powerfull genetic algorithm library by D. Levine, Mathematics and Computer Science Division Argonne National Laboratory. The library is written in C. PGAPy wraps this library for use with Python.
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Evolutionary Computation Framework
C++ framework for application of any type of evolutionary computation.
ECF is a framework intended for application of any type of evolutionary computation (GA/GP, DE, Clonalg, ES, PSO, ABC, GAn, local search...). It offers simplicity for the end-user (parameterless usage, tutorial) and customization for experienced EC practicioners. -
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Sudoku Maker is a generator for Sudoku number puzzles. It uses a genetic algorithm internally, so it can serve as an introduction to genetic algorithms. The generated Sudokus are usually very hard to solve -- good for getting rid of a Sudoku addiction.
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OpenDino
Open Source Java platform for Optimization, DoE, and Learning.
OpenDino is an open source Java platform for optimization, design of experiment and learning. It provides a graphical user interface (GUI) and a platform which simplifies integration of new algorithms as "Modules". Implemented Modules Evolutionary Algorithms: - CMA-ES - (1+1)-ES - Differential Evolution Deterministic optimization algorithm: - SIMPLEX Learning: - a simple Artificial Neural Net Optimization problems: - test functions - interface for executing... -
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The source code has been migrated and is now hosted on Github: https://github.com/jenetics/jenetics Jenetics is an advanced Genetic Algorithm, Evolutionary Algorithm and Genetic Programming library, respectively, written in modern day Java. It is designed with a clear separation of the several algorithm concepts, e. g. Gene, Chromosome, Genotype, Phenotype, Population and fitness Function. Jenetics allows you to minimize or maximize the given fitness function without tweaking it. ...
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MicroGP
A multi-purpose extensible self-adaptive evolutionary algorithm
MicroGP (µGP, ugp) is a versatile optimizer able to outperform both human experts and conventional heuristics in finding the optimal solution of hard problems. It is an evolutionary algorithm since it mimics some principles of the Neo-Darwinian paradigm. ⚠️ A new version is available on https://github.com/squillero/microgp4 -
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Opt4J
Modular Java framework for meta-heuristic optimization
Opt4J is an open source Java-based framework for evolutionary computation. It contains a set of (multi-objective) optimization algorithms such as evolutionary algorithms (including SPEA2 and NSGA2), differential evolution, particle swarm optimization, and simulated annealing. The benchmarks that are included comprise ZDT, DTLZ, WFG, and the knapsack problem. The goal of Opt4J is to simplify the evolutionary optimization of user-defined problems as well as the implementation of arbitrary... -
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Java CoreWars Evolver
A Java based, pMars compatible, CoreWars simulator with GA
A Java based, pMars compatible, CoreWars simulator with Genetic Algorithm warrior evolver functionality. Java 8 is needed. See [Wiki:Tutorial] -
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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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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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Genetic Basis
A general genetic algorithm framework
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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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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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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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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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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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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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