Showing 14 open source projects for "genetic algorithm scheduling python"

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  • 1
    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.
    Downloads: 0 This Week
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  • 2
    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.
    Downloads: 2 This Week
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  • 3
    Solid Python

    Solid Python

    A comprehensive gradient-free optimization framework written in Python

    Solid is a Python framework for gradient-free optimization. It contains basic versions of many of the most common optimization algorithms that do not require the calculation of gradients, and allows for very rapid development using them.
    Downloads: 0 This Week
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  • 4
    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.
    Downloads: 0 This Week
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  • 5
    Evolving Objects

    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/)
    Downloads: 0 This Week
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  • 6

    ats - Automated Testing System

    Object oriented Python-based tool for test automation.

    .... ATS provides the capability to run serial or parallel tests simultaneously up to the resource limits it has been given (i.e. some number of processors on which to run). Tests can be given a priority rating and be dependent upon other tests, and these features are accounted for in its scheduling algorithm. The software is configurable and extensible. ATS provides numerous options for creating dependent chains of tests, filtering based on various criteria, and running tests with custom arguments.
    Downloads: 1 This Week
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  • 7
    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.
    Downloads: 0 This Week
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  • 8
    Free Resource Leveling Algorithm
    Free and easy to implement algorithm that can be used for resource leveling in Gantt projects. Uses resources assignment policies, availibility calendars, tasks\' priorities, dependencies, sizings, complexity due to human communication.
    Downloads: 0 This Week
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  • 9
    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
    Downloads: 0 This Week
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  • 10
    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.
    Downloads: 0 This Week
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  • 11
    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.
    Downloads: 0 This Week
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  • 12
    Implement a scheduling algorithm to schedule classes at a university
    Downloads: 0 This Week
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  • 13
    Galileo is a library for developing custom distributed genetic algorithms developed in Python. It provides a robust set of objects that can be used directly or as the basis of derived objects. Its modularity makes it easy to extend the functionality. The
    Downloads: 0 This Week
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  • 14
    cosmos

    cosmos

    Algorithms that run our universe | Your personal library of every algo

    Cosmos (by OpenGenus Foundation) is your personal offline collection of every algorithm and data structure one will ever encounter and use in a lifetime. This provides solutions in various languages spanning C, C++, Java, JavaScript, Swift, Python, Go and others. This work is maintained by a community of hundreds of people and is a massive collaborative effort to bring the readily available coding knowledge offline.
    Downloads: 0 This Week
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