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Commit 16c5ad9

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PyGAD 2.18.0 Documentation
1. Raise an exception if the sum of fitness values is zero while either roulette wheel or stochastic universal parent selection is used. #129 2. Initialize the value of the `run_completed` property to `False`. #122 3. The values of these properties are no longer reset with each call to the `run()` method `self.best_solutions, self.best_solutions_fitness, self.solutions, self.solutions_fitness`: #123. Now, the user can have the flexibility of calling the `run()` method more than once while extending the data collected after each generation. Another advantage happens when the instance is loaded and the `run()` method is called, as the old fitness value are shown on the graph alongside with the new fitness values. Read more in this section: [Continue without Loosing Progress](https://pygad.readthedocs.io/en/latest/README_pygad_ReadTheDocs.html#continue-without-loosing-progress) 4. Thanks [Prof. Fernando Jiménez Barrionuevo](http://webs.um.es/fernan) (Dept. of Information and Communications Engineering, University of Murcia, Murcia, Spain) for editing this [comment](https://github.com/ahmedfgad/GeneticAlgorithmPython/blob/5315bbec02777df96ce1ec665c94dece81c440f4/pygad.py#L73) in the code. 5315bbe 5. A bug fixed when `crossover_type=None`. 6. Support of elitism selection through a new parameter named `keep_elitism`. It defaults to 1 which means for each generation keep only the best solution in the next generation. If assigned 0, then it has no effect. Read more in this section: [Elitism Selection](https://pygad.readthedocs.io/en/latest/README_pygad_ReadTheDocs.html#elitism-selection). #74 7. A new instance attribute named `last_generation_elitism` added to hold the elitism in the last generation. 8. A new parameter called `random_seed` added to accept a seed for the random function generators. Credit to this issue #70 and [Prof. Fernando Jiménez Barrionuevo](http://webs.um.es/fernan). Read more in this section: [Random Seed](https://pygad.readthedocs.io/en/latest/README_pygad_ReadTheDocs.html#random-seed). 9. Editing the `pygad.TorchGA` module to make sure the tensor data is moved from GPU to CPU. Thanks to Rasmus Johansson for opening this pull request: ahmedfgad/TorchGA#2 
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PyGAD <https://pygad.readthedocs.io/en/latest/README_pygad_ReadTheDocs.html#parallel-processing-in-pygad>`__
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section for more information and examples.
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PyGAD 2.18.0
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------------
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Release Date: 9 September 2022
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1. Raise an exception if the sum of fitness values is zero while either
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roulette wheel or stochastic universal parent selection is used.
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https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/129
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2. Initialize the value of the ``run_completed`` property to ``False``.
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https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/122
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3. The values of these properties are no longer reset with each call to
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the ``run()`` method
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``self.best_solutions, self.best_solutions_fitness, self.solutions, self.solutions_fitness``:
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https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/123. Now,
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the user can have the flexibility of calling the ``run()`` method
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more than once while extending the data collected after each
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generation. Another advantage happens when the instance is loaded and
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the ``run()`` method is called, as the old fitness value are shown on
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the graph alongside with the new fitness values. Read more in this
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section: `Continue without Loosing
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Progress <https://pygad.readthedocs.io/en/latest/README_pygad_ReadTheDocs.html#continue-without-loosing-progress>`__
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4. Thanks `Prof. Fernando Jiménez
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Barrionuevo <http://webs.um.es/fernan>`__ (Dept. of Information and
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Communications Engineering, University of Murcia, Murcia, Spain) for
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editing this
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`comment <https://github.com/ahmedfgad/GeneticAlgorithmPython/blob/5315bbec02777df96ce1ec665c94dece81c440f4/pygad.py#L73>`__
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in the code.
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https://github.com/ahmedfgad/GeneticAlgorithmPython/commit/5315bbec02777df96ce1ec665c94dece81c440f4
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5. A bug fixed when ``crossover_type=None``.
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6. Support of elitism selection through a new parameter named
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``keep_elitism``. It defaults to 1 which means for each generation
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keep only the best solution in the next generation. If assigned 0,
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then it has no effect. Read more in this section: `Elitism
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Selection <https://pygad.readthedocs.io/en/latest/README_pygad_ReadTheDocs.html#elitism-selection>`__.
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https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/74
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7. A new instance attribute named ``last_generation_elitism`` added to
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hold the elitism in the last generation.
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8. A new parameter called ``random_seed`` added to accept a seed for the
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random function generators. Credit to this issue
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https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/70 and
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`Prof. Fernando Jiménez Barrionuevo <http://webs.um.es/fernan>`__.
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Read more in this section: `Random
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Seed <https://pygad.readthedocs.io/en/latest/README_pygad_ReadTheDocs.html#random-seed>`__.
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9. Editing the ``pygad.TorchGA`` module to make sure the tensor data is
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moved from GPU to CPU. Thanks to Rasmus Johansson for opening this
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pull request: https://github.com/ahmedfgad/TorchGA/pull/2
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PyGAD Projects at GitHub
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========================
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