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‎LICENSE

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Copyright GeneticAlgorithmPython Contributors
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Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
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1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
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2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
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3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

‎README.md

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Get started with the genetic algorithm by reading the tutorial titled [**Introduction to Optimization with Genetic Algorithm**](https://www.linkedin.com/pulse/introduction-optimization-genetic-algorithm-ahmed-gad) which is available at these links:
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* [LinkedIn](https://www.linkedin.com/pulse/introduction-optimization-genetic-algorithm-ahmed-gad)
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* [Towards Data Science](https://www.kdnuggets.com/2018/03/introduction-optimization-with-genetic-algorithm.html)
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* [KDnuggets](https://towardsdatascience.com/introduction-to-optimization-with-genetic-algorithm-2f5001d9964b)
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* [Towards Data Science](https://towardsdatascience.com/introduction-to-optimization-with-genetic-algorithm-2f5001d9964b)
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* [KDnuggets](https://www.kdnuggets.com/2018/03/introduction-optimization-with-genetic-algorithm.html)
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[![Introduction to Genetic Algorithm](https://user-images.githubusercontent.com/16560492/82078259-26252d00-96e1-11ea-9a02-52a99e1054b9.jpg)](https://www.linkedin.com/pulse/introduction-optimization-genetic-algorithm-ahmed-gad)
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‎__init__.py

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from .pygad import * # Relative import.
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__version__ = "2.16.3"
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__version__ = "2.18.3"

‎docs/Makefile

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# Minimal makefile for Sphinx documentation
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#
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# You can set these variables from the command line, and also
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# from the environment for the first two.
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SPHINXOPTS ?=
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SPHINXBUILD ?= sphinx-build
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SOURCEDIR = source
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BUILDDIR = build
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# Put it first so that "make" without argument is like "make help".
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help:
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@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
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.PHONY: help Makefile
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# Catch-all target: route all unknown targets to Sphinx using the new
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# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS).
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%: Makefile
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@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)

‎docs/make.bat

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@ECHO OFF
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pushd %~dp0
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REM Command file for Sphinx documentation
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if "%SPHINXBUILD%" == "" (
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set SPHINXBUILD=sphinx-build
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)
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set SOURCEDIR=source
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set BUILDDIR=build
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if "%1" == "" goto help
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%SPHINXBUILD% >NUL 2>NUL
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if errorlevel 9009 (
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echo.
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echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
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echo.installed, then set the SPHINXBUILD environment variable to point
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echo.to the full path of the 'sphinx-build' executable. Alternatively you
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echo.may add the Sphinx directory to PATH.
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echo.
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echo.If you don't have Sphinx installed, grab it from
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echo.http://sphinx-doc.org/
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exit /b 1
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)
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%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
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goto end
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:help
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%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
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:end
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popd

‎docs/source/Footer.rst

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.. _pygad-1020:
2020

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PyGAD 1.0.20
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------------
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-------------
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Release Date: 4 May 2020
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.. _pygad-200:
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PyGAD 2.0.0
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-----------
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------------
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Release Date: 13 May 2020
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.. _pygad-260:
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PyGAD 2.6.0
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-----------
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------------
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Release Date: 6 August 2020
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.. _pygad-290:
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PyGAD 2.9.0
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-----------
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------------
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Release Date: 06 December 2020
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.. _pygad-2130:
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PyGAD 2.13.0
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------------
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-------------
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Release Date: 12 March 2021
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``solutions_fitness`` array.
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https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/64
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1. There was an issue of getting the length of these 4 variables
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2. There was an issue of getting the length of these 4 variables
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(``solutions``, ``solutions_fitness``, ``best_solutions``, and
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``best_solutions_fitness``) doubled after each call of the ``run()``
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method. This is solved by resetting these variables at the beginning
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of the ``run()`` method.
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https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/62
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2. Bug fixes when adaptive mutation is used
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3. Bug fixes when adaptive mutation is used
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(``mutation_type="adaptive"``).
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https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/65
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exception is raised if something is wrong.
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https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/67
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.. _pygad-2170:
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PyGAD 2.17.0
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------------
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Release Date: 8 July 2022
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1. An issue is solved when the ``gene_space`` parameter is given a fixed
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value. e.g. gene_space=[range(5), 4]. The second gene's value is
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static (4) which causes an exception.
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2. Fixed the issue where the ``allow_duplicate_genes`` parameter did not
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work when mutation is disabled (i.e. ``mutation_type=None``). This is
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by checking for duplicates after crossover directly.
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https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/39
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3. Solve an issue in the ``tournament_selection()`` method as the
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indices of the selected parents were incorrect.
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https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/89
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4. Reuse the fitness values of the previously explored solutions rather
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than recalculating them. This feature only works if
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``save_solutions=True``.
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5. Parallel processing is supported. This is by the introduction of a
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new parameter named ``parallel_processing`` in the constructor of the
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``pygad.GA`` class. Thanks to
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`@windowshopr <https://github.com/windowshopr>`__ for opening the
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issue
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`#78 <https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/78>`__
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at GitHub. Check the `Parallel Processing in
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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-2180:
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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-2181:
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PyGAD 2.18.1
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------------
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Release Date: 19 September 2022
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1. A big fix when ``keep_elitism`` is used.
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https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/132
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.. _pygad-2182:
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PyGAD 2.18.2
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------------
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Release Date: 14 February 2023
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1. Remove ``numpy.int`` and ``numpy.float`` from the list of supported
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data types.
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https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/151
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https://github.com/ahmedfgad/GeneticAlgorithmPython/pull/152
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2. Call the ``on_crossover()`` callback function even if
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``crossover_type`` is ``None``.
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https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/138
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3. Call the ``on_mutation()`` callback function even if
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``mutation_type`` is ``None``.
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https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/138
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.. _pygad-2183:
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PyGAD 2.18.3
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------------
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Release Date: 14 February 2023
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1. Bug fixes.
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9661096
PyGAD Projects at GitHub
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========================
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`Multi-Input Multi-Output in Genetic algorithm (python) <https://stackoverflow.com/questions/64943711/multi-input-multi-output-in-genetic-algorithm-python>`__
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--------------------------------------------------------------------------------------------------------------------------------------------------------------
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https://www.linkedin.com/pulse/validation-short-term-parametric-trading-model-genetic-landolfi
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https://itchef.ru/articles/397758
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https://audhiaprilliant.medium.com/genetic-algorithm-based-clustering-algorithm-in-searching-robust-initial-centroids-for-k-means-e3b4d892a4be
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https://python.plainenglish.io/validation-of-a-short-term-parametric-trading-model-with-genetic-optimization-and-walk-forward-89708b789af6
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https://ichi.pro/ko/pygadwa-hamkke-yujeon-algolijeum-eul-sayonghayeo-keras-model-eul-hunlyeonsikineun-bangbeob-173299286377169
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https://ichi.pro/tr/pygad-ile-genetik-algoritmayi-kullanarak-keras-modelleri-nasil-egitilir-173299286377169
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https://ichi.pro/ru/kak-obucit-modeli-keras-s-pomos-u-geneticeskogo-algoritma-s-pygad-173299286377169
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https://blog.csdn.net/sinat_38079265/article/details/108449614
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Submitting Issues
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=================
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