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ahmedfgad merged 1 commit into from
Jun 11, 2026
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Refer to tutorials to use vilvik #365

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6 changes: 6 additions & 0 deletions README.md
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> Try [Vilvik](https://vilvik.com), a free cloud-based tool powered by PyGAD. It makes optimization easier by reducing or removing the need for coding, and it shows helpful visualizations.

> Run PyGAD in the cloud with [Vilvik](https://vilvik.com): push your PyGAD problem to Vilvik, let it run in the cloud, and get the results back.

![Run PyGAD in the cloud with Vilvik](https://github.com/ahmedfgad/GeneticAlgorithmPython/raw/master/docs/source/images/pygad_vilvik_cloud.png)

Push your PyGAD problem to [Vilvik](https://vilvik.com) and run it in the cloud. To get started, follow this tutorial: [Push your PyGAD problem to Vilvik in 10 minutes](https://vilvik.com/blog/@vilvik/pygad-to-vilvik-in-10-minutes).

Read the [PyGAD documentation](https://pygad.readthedocs.io/en/latest).

[![PyPI Downloads](https://pepy.tech/badge/pygad)](https://pepy.tech/project/pygad) [![Conda Downloads](https://img.shields.io/conda/dn/conda-forge/pygad.svg?label=Conda%20Downloads)](
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2 changes: 1 addition & 1 deletion docs/source/index.md
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Push your PyGAD problem to [Vilvik](https://vilvik.com) and run it in the cloud.
Push your PyGAD problem to [Vilvik](https://vilvik.com) and run it in the cloud. To get started, follow this tutorial: [Push your PyGAD problem to Vilvik in 10 minutes](https://vilvik.com/blog/@vilvik/pygad-to-vilvik-in-10-minutes).
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[PyGAD](https://github.com/ahmedfgad/GeneticAlgorithmPython) supports different types of crossover, mutation, and parent selection operators. It lets you optimize many types of problems with the genetic algorithm by writing your own fitness function. It works with both single-objective and multi-objective optimization problems.
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