Search Results for "genetic algorithm cloudsim" - Page 4
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Showing 130 open source projects for "genetic algorithm cloudsim"
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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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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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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/).
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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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Springbots is a python application which takes a set of 2d physical structures built with nodes and movable springs and evolve them for specific tasks like walking, swimming and jumping using genetic algorithm.
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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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A 2D rigid physics simulator and set of genetic algorithm tools. Evolve cute little walking creatures.
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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 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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Trilobots is an arcade-style shooter that evolves the abilities and programming of the enemies using a genetic algorithm. The end goal is to make the evolution transparent, allowing users to learn how genetic algorithms work while having fun.
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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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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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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
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NullAllEst is the implementation of a maximum likelihood algorithm to estimate the frequency of a null allele in microsatellite genetic data. A Markov Chain Monte Carlo simulation is used to solve the likelihood function.
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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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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.
